METHODS OF USING TRIANGULATION TO LOCATE A MANHOLE EVENT IN A SYSTEM OF UNDERGROUND VAULTS

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U S Patent Application

No. 16/234,248, filed December 27, 2018, titled“Methods of Using

Triangulation to Locate a Manhole Event in a System of Underground Vaults,” U.S. Patent Application No. 16/219,137, filed on December 13, 2018, titled “Methods of Using Dilution of a Second Type to Calibrate One or More

Sensors,” U.S Patent Application No. 16/207,633, filed on December s, 2018, titled“Methods of Using Dilution of a First Type to Calibrate One or More Sensors,” U.S. Patent Application No. 16/190,832, filed November 14, 2018, titled“Methods of Using Component Mass Balance to Evaluate Manhole Events,” U.S. Patent Application No. 16/189,639, filed on November 13, 2018, titled“Methods of Using Component Mass Balance to Evaluate Manhole Events,” and U.S. Application Patent No. 16/162,260, filed on October 16,

2018, titled“Calibrationless Operation Method.” Each of these aforementioned applications is incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention is directed generally to methods of determining whether a manhole event has occurred.

Description of the Related Art

Sensor drift refers to a change in a sensor’s output signal that is independent of a property being measured by the sensor. Because of sensor drift, unless a sensor is calibrated frequently, absolute values obtained by that sensor cannot be relied upon. Sensor drift is particularly acute in sensors that detect analytes and/or particulates of many different compounds (e.g., H2, CO2, CO, O2, VOCs, H2S, etc.). Sensor drift is exasperated by a challenging environment, such as the environment present inside an underground electrical cable equipment vault, where high temperatures, substantial diurnal and annual temperature variations, high humidity, and corrosive chemistry are

commonplace.

Unfortunately, frequent calibration by technicians of sensors present inside underground vaults is impractical because in busy urban areas, traffic and safety considerations limit or prevent access to these environments. Such sensors are generally calibrated using calibration gases (“cai-gases"), which possess known concentrations (including zero) of a particular component of interest (analyte) in an inert carrier gas (e.g., nitrogen, argon, and the like). Unfortunately, including such cal-gases in a system designed for multi-year maintenance-free operation may be impractical as the required gas quantity may be substantial and the plumbing required carries its own reliability issues.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

Figure 1 is a side view of an exemplary manhole event suppression system installed in one of a plurality of manhole vaults

interconnected by a plurality of conduits or connections.

Figure 2 is a perspective view of a manhole cover.

Figure 3 is an enlarged perspective view of the monitor installed in the underground vault connected to a System Controller.

Figure 4 is an illustration of gases entering one of the manhole vaults of Figure 1 through a connection to the vault.

Figure 5 is a bar graph illustrating an accounting of different gaseous combustion-pyrolysis products of low density polyethylene (“LDPE") powder taken from Boettner et al,“Combustion Products from the Incineration of Plastics" Michigan University 1973, prepared for the Office of Research and Development U.S. Environmental Protection Agency, Washington D.C. 20480,

E PA-670/2-73-049.

Figure 6 is a bar graph of a residual gas analyzer (“RGA”) result that quantifies water evolved from combustion/pyrolysis of rubber compounds taken from Zhang, Boggs, et al,“The Electro-Chemical Basis of Manhole Events,’’ IEEE Electrical Insulation Magazine, Vol. 25, No 5, 9-10/2009.

Figure 7 A is a flow diagram of a method performed by the monitoring system of Figure 1.

Figure 7B is a flow diagram of a method performed by a monitor of Figure 1 .

Figure 7C is a first portion of a flow diagram of an evaluate method performed by the System Controller of Figure 1 .

Figure 7D is a second portion of the flow diagram of the evaluate method.

Figure /E is a third portion of the flow diagram of the evaluate method.

Figure 7F is a flow diagram of a highest notification method performed by the System Controller of Figure 1 .

Figure 7G is a flow diagram of an intermediate notification method performed by the System Controller of Figure 1 .

Figure 7H is a flow diagram of a lowest notification method performed by the System Controller of Figure 1 .

Figure 7i is a flow diagram of a corroborate method performed by the System Controller of Figure 1 .

Figure 7J is a flow diagram of a coordinate method performed by the System Controller of Figure 1 .

Figure 7K is a flow diagram of a calculate method performed by the System Controller of Figure 1

Figure 71 is a flow diagram of a validate method performed by the System Controller of Figure 1 .

Figure 7M is a flow diagram of a drift validation process performed by the System Controller of Figure 1 .

Figure 7N is a flow diagram of a persistence validation process performed by the System Controller of Figure 1 .

Figure 70 is a flow diagram of a desaturate method performed by the System Controller of Figure 1 . Figure 7P is a flow diagram of a calibrate method performed by the System Controller of Figure 1

Figure 7Q is a flow diagram of a relate method performed by the System Controller of Figure 1.

Figure 7R is a flow diagram of a dilution one test method performed by the System Controller of Figure 1.

Figure 7S is a flow diagram of a dilution two test method performed by the System Controller of Figure 1.

Figure 7T is a flow diagram of a dilution one calibration method performed by the System Controller of Figure 1.

Figure 7U is a flow diagram of a dilution two calibration method performed by the System Controller of Figure 1.

Figure 7V is a flow diagram of a dilution one range method performed by the System Controller of Figure 1.

Figure 7W is a flow diagram of a dilution two range method performed by the System Controller of Figure 1.

Figure 8A is a graph of exemplary sensor readings and a line illustrating sensor drift.

Figure 8B is a graph of a portion of the exemplary sensor readings of Figure 8A including the line illustrating the sensor drift and lines illustrating upper and lower confidence bounds.

Figure 9 is a flow diagram of a second method performed by the System Controller of Figure 1.

Figure 10 is a flow diagram of a third method performed by the System Controller of Figure 1.

Figure 11 is a flow diagram of a fourth method performed by the System Controller of Figure 1.

Figure 12 is a flow diagram of a fifth method performed by the System Controller of Figure 1.

Figure 13 is a flow diagram of a sixth method performed by the System Controller of Figure 1.

Figure 14 is a flow diagram of a seventh method performed by the System Controller of Figure 1. Figure 15 is a flow diagram of an eighth method performed by the System Controller of Figure 1.

Figure 16 is an illustration of a network of underground vaults in which a fire is occurring in a connection interconnecting two of the vaults.

Figure 17 is a diagram of a hardware environment and an operating environment in which the System Controller of Figures 1 and 3 may be implemented.

Figure 18 is a graph illustrating how oxidative decomposition and pyrolysis can create flammable atmospheres inside one or more vaults.

Figure 19 is a graph illustrating typical evolution of a manhole event from initiation to extinguishment.

Figure 20 is an illustration of an embodiment of a sample control sub-system.

Like reference numerals have been used in the figures to identify like components.

DETAILED DESCRIPTION OF THE INVENTION

Underground utilities, such as water, sewer, natural gas, electricity, telephone, cable, and steam, are a common means of delivering the essentials of modern life in a developed society. Referring to Figure 1 , such utilities are often routed through an underground system 100 that includes a plurality of substantially identical underground chambers or manhole

vaults 112-116 interconnected by one or more conduits or connections 118A- 118J. The vaults 112-116 may each be configured to house equipment 119, such as critical control equipment, monitoring equipment, transformers, and appropriate network connections. As shown in Figure 1 , the vaults 112-116 and the connections 118A-118J are positioned below a street or sidewalk level (identified as a surface 120) In Figure 1 , only the three vaults 112-116 of the system 100 have been illustrated. However, the system 100 may include any number of vaults each substantially similar to one of the vaults 112-116

Similarly, while the ten connections 118A-118J have been illustrated, the system 100 may include any number of connections each substantially similar to one of the connections 118A-118J. An external atmosphere 122 exists outside the vault 112 (e.g., above the surface 120) and an internal atmosphere 124 is present inside the vault 112. For ease of illustration, air entering the vault 112 from the external atmosphere 122 will be described as being fresh air and air from the internal atmosphere 124 exiting the vault 112 into the external atmosphere 122 will be described as being exhaust. Thus, both a flow FFA of fresh air into the vault 112 and a flow FE of exhaust from the vault 112 may be present. While active ventilation may be used to encourage a substantial flow (e.g., a vault turnover that is less than 10 minutes or a vault turnover that is less than 5 minutes) of exhaust and fresh air, the principles described herein are applicable to underground vaults in which active ventilation has not been implemented.

Where passive ventilation is utilized, the flow FE of exhaust and the flow FFA of fresh air may be estimated using empirical models that include factors. These factors may include, but are not limited to, local weather (including temperature and wind speed), waste energy generated in the vault 112 (e.g., where the variable Y represents the current of each cable 160 in the vault 112 and the variable“R” represents a respective impedance of the cable), the configuration of the vault 112, and the design of a manhole cover (e.g., like a manhole cover 144).

A flow Fc from one or more of the connections 118A-118J may flow into the vault 112. One or more gases created by a manhole event may travel into the vault 112 via the connection(s) flow Fc. When water W is present in the vault 112, an evaporation flow Fv may be present inside the vault 112.

The time constant t (tau) for any given underground vault (like the underground vault 112) varies with a water depth, the volume of the underground vault 112, and a flow rate of the exhaust flow FE. While the connections) flow Fc is illustrated as coming from the connection 118E in Figure 1 , one of ordinary skill in the art would recognize that the source of the connection(s) flow Fc could alternatively be located within one or more of the vaults 112-116. Because in excess of 90% of cables 160 typically lie within connections (such as the connections 118A-118J), the most likely source of the connection(s) flow Fc lies within one of the connections (e.g., the connection 118E) and hence this is what Figure 1 depicts. For the purposes of this application, the connectionfs) flow Fc may originate from a source within a vault (e.g., one or more of the vaults 1 12-1 16 illustrated in Figure 1 ). Thus, the connection(s) flow Fc may be characterized as being an event flow.

Figure 1 illustrates a monitoring system 102 that includes a monitor 126 configured to communicate with a System Controller 190 via a wireless and/or wired connection. The monitor 126 is installed in the

underground vault 1 12. The monitor 126 includes or is connected to one or more sensors 128. The monitor 126 includes other components 130 (e.g., hardware and software) that operate the sensor(s) 128. The components 130 may include one or more processors (e.g., a processor 130P) which is connected to memory 1 SOM that stores instructions 1301. The instructions 1301 are executable by the processor 130P. By way of a non-limiting example, the monitor 126 may be implemented as a data logger described in U.S. Patent Application No. 15/476,775, filed on March 31 , 2017, and titled“Smart System for Manhole Event Suppression System,” which is incorporated herein by reference in its entirety.

The System Controller 190 may be located remotely or collocated with respect to the monitor 126. The monitor 126 may be connected to the System Controller 190 across one or more networks (not shown).

The exhaust flow FE may be created as least in part by an air moving device 132 of a manhole event suppression system 140. The air moving device 132 may be configured to blow exhaust (as the flow FE) out through one or more of a plurality of through-holes 142 (see Figure 2) formed in the manhole cover 144 and/or to blow fresh air info the vault 1 12 through one or more of the through-holes 142. In the embodiment illustrated, the air moving device 132 is connected to the manhole cover 144 by a first section P1 of a ventilation pipe 148 An inner portion 142-E (see Figure 2) of the through-holes 142 (see Figure 2) are positioned inside the first section P1 and an outer portion 142-FA (see Figure 2) of the through-holes 142 are positioned outside the first section P1.

The monitor 126 may be positioned in the fresh air flow FFA. If the air moving device 132 is configured to exhaust air through the inner portion 142-E (see Figure 2) of the through-holes 142 (see Figure 2), the monitor 126 may be attached to an outer surface 150 of the air moving device 132 and/or the first section P1 In this manner, the monitor 126 is within the fresh air flow FFA as it enters the vault 112. On the other hand, if the air moving device 132 is drawing fresh air in through the inner portion 142-E (see Figure 2) of the through-holes 142 (see Figure 2), the monitor 126 may be attached to an inner surface 146 of the air moving device 132 and/or the first section P1 so that the monitor 126 is in intimate contact with the fresh air flow FFA entering the outer portion 142-FE (see Figure 2) of the through-holes 142. In this manner the monitor 126 is within the fresh air flow FFA as it enters the vault 112.

Alternatively, the monitor 126 may be mounted to the vault 112 (e.g., on a vault wall). Generally speaking, the fresh air flow FFA is always cooler than the exhaust flow FE. Electrical components of the monitor 126 may function better at lower temperatures. By way of a non-limiting example, the monitor 126 may be positioned between the fresh air flow FFA and the exhaust flow FE so that less plumbing is needed to sample both the fresh air flow FFA and the exhaust flow FE.

Alternatively, the monitor 126 may be positioned in the exhaust flow FE. If the air moving device 132 is configured to exhaust air through the inner portion 142-E (see Figure 2) of the through-holes 142 (see Figure 2), the monitor 126 may be attached to the inner surface 146 of the air moving device 132 and/or the first section P1. In this manner, the monitor 126 is within the exhaust flow FE before it leaves the vault 112. On the other hand, if the air moving device 132 is drawing fresh air in through the inner portion 142-E (see Figure 2) of the through-holes 142 (see Figure 2), the monitor 126 may be attached to the outer surface 150 of the air moving device 132 and/or the first section P1 so that the monitor 126 is in intimate contact with the exhaust flow FE exiting through the outer portion 142-FE (see Figure 2) of the through-holes 142. In this manner, the monitor 126 is within the exhaust flow FE before It leaves the vault 112. Alternatively, the monitor 126 may be mounted to the vault 112 (e.g., on a vault wail).

Referring to Figure 3, the sensor(s) 128 may include a wafer level sensor 214 and at least one fire detection sensor 216 together with hardware and software configured to operate the sensors 214 and 216. The fire detection sensor(s) 218 may include a temperature sensor, a humidity sensor, a visible light camera, an infra-red camera, a motion sensor, a particulate sensor, a smoke sensor or detector, and a chemical concentration sensor. Examples of chemical concentration sensors that may be used to implement one or more of the fire detection sensor(s) 216 include sensors configured to detect 02, CO2, CO, H2, VOCs, NO, NO2, particulates, and O3.

As one of ordinary skill in the art will recognize, where more than a single detection sensor is utilized, such sensors can belong to at least one sensor group. Each sensor group includes at least one sensor and is independently plumbed to (or is in communication with) the flow (e.g., an air stream) to be analyzed. For example, at least two sensor groups may be used to obtain parameter values for the exhaust flow FE, the fresh air flow FFA, and the connection(s) flow Fc (see Figures 1 and 4). A single sensor group may sample more than one flow simultaneously. For example, the same sensor group may be used to sample both the exhaust flow FE and the fresh air flow FFA. The samples obtained by different sensor groups may be diluted differently (e.g., using dilution of the second type described below). These different dilution levels may be used to operate each of the sensor groups within their respective ranges. For example, the sensor groups may be operated in the middle of their respective ranges. Additionally, different sensor groups may operate in different modes at the same time. For example, a first sensor group may be operating with its current modes set to CALIBRATE1 , while a second sensor group is operating with its current modet set to

ROUTINE.

By way of non-limiting examples, the fire detection sensor(s) 218 may detect one or more of the following conditions, which indicate a

corresponding fire or flammable gas accumulation (“FGA”) specified in parenthesis:

i. CO2 is elevated (oxidative decomposition); ii. CO is elevated (pyrolysis);

iii. VOCs are elevated (pyrolysis or FGA);

iv. H2 is elevated (pyrolysis); v. NO is elevated (evidence of plasma/electrical discharge or high temperature oxidative decomposition);

vi. NO2 is elevated (evidence of plasma/electricai discharge or high temperature oxidative decomposition);

vii. Os is elevated (evidence of plasma/electricai discharge or high temperature oxidative decomposition);

viii. H2O (absolute humidity) is elevated (oxidative decomposition);

ix. O2 is depressed (dilution by i - vii, and consumption by oxidative decomposition and partial pyrolysis);

x. Temperature is elevated (oxidative decomposition);

xi. Particulates are elevated (any or all oxidative decomposition, pyrolysis, plasma/electricai discharge); and

XII. Smoke is observed in visual or infra-red wavelengths by pattern recognition algorithms or by motion detection (any or all oxidative decomposition, pyrolysis, plasma/electricai discharge).

Referring to Figure 1 , the equipment 119 located in the underground vault 112 may include and/or be connected to the cables 180. Equipment (like the equipment 119) may be located in other vaults (e.g., the vaults 114 and 118) connected to the vault 112. The electrical equipment 119 may cause manhole events. Manhole events include both minor incidents (such as smoke or small fires) and/or major events (such as sustained fires and explosions). The manhole event suppression system 140 may be installed in the underground vault 112 to help prevent manhole events. The monitor 126 is illustrated integral with the manhole event suppression system 140, but the monitor 126 may also be independent of the manhole event suppression system 140.

As mentioned above, the air moving device 132 of the manhole event suppression system 140 is configured to exchange air between the external atmosphere 122 outside the vault 112 and the internal atmosphere 124 inside the vault 112. For example, the air moving device 132 of the manhole event suppression system 140 may blow fresh air from the external atmosphere 122 into the internal atmosphere 124 and/or may exhaust air from the internal atmosphere 124 into the external atmosphere 122. Such air exchange may be referred to as active ventilation. By way of non-limiting examples, the manhole event suppression system 140 may be implemented in accordance with any of the ventilation systems described in U S. Patent Application No. 15/084,321 filed on March 29, 2016 (titled“Ventilation System for Manhole Vault ^” ), U.S. Patent Application No. 15/173,633, filed June 4, 2016 (titled“Systems for Circulating Air Inside a Manhole Vault ^” ), and/or U.S. Patent Application No. 15/476,775, filed on March 31 , 2017 (titled“Smart System for Manhole Event Suppression System”). Each of the aforementioned patent applications is incorporated herein by reference in its entirety.

The internal atmosphere 124 may include an undesired (and potentially dangerous) gaseous composition 164. The gaseous composition 164 may be non-uniform ly distributed within an interior 166 of the vault 112.

For example, the gaseous composition 164 may be adjacent or near a floor 168 of the vault 112.

A sensor’s output signal or readings may be inaccurate for a number of reasons, including sensor drift, noise, and the like. Sensor drift is a change in a sensor’s output signal or readings that occurs over time and is independent of the thing (e.g., concentration of an analyte) being measured. Noise is random variations in the output signal or readings of a sensor.

Variations caused by sensor drift and/or non-drift variations (e.g., noise) will be referred to as inconsequential variations and variations caused by a manhole event will be referred to as consequential variations. At least some of the inconsequential variations can be removed by calibrating the sensor.

Unfortunately, it is not always practical to calibrate a sensor, such as one or more of the fire detection sensor(s) 216 installed in the underground vault 112. Therefore, a process referred to herein as“Calibrationiess Operation,” described below, may be implemented for one or more of the fire detection sensor(s) 216.

The useful life of a sensor may be extended using Calibrationiess Operation. For example, a sensor package may use Calibrationiess Operation to extend the life of one or more of its sensors. Calibrationiess Operation involves the statistical filtering of sensor drift, noise, and the like. Sensor drift occurs slowly and independently of random sensor noise. Sensor drift is generally only significant over a period of days. Events (such as fires or natural gas leaks) that increase analytes of interest, (such as VOCs, Fte, CO, H2O (relative humidity), NO, NO2, O3, and/or CO2), and sometimes cause

corresponding decreases in other analytes, such as O2, tend to exhibit much lower time constants - measureable in minutes or hours. Thus, increases in analytes of interest that occur within a short time period are typically not caused by sensor drift and are much more likely to indicate a manhole event is occurring.

Calibrationiess Operation models past behavior of a sensor to identify drift and/or noise and avoids acting upon identified drift and/or noise. A purely statistical approach to identifying drift and/or noise presents a direct trade-off between identifying false positives and false negatives. That is, a practitioner can set a very high bar for detecting a dangerous gas, which would reduce the number of false positives, but must as a result accept a higher probability of false negatives. To overcome this tradeoff, Calibrationiess Operation deploys at least one of the following three corroborating techniques: confirmatory measurement(s), complementary corroboration, and active dilution.

CONFIRMATORY MEASUREMENT(S)

When a suspected alarm condition is detected by a sensor, at least one confirmatory measurement is made quickly after the detection. For example, multiple confirmatory measurements may be made in rapid

succession to test for random variations (noise). Such confirmatory

measurement(s) may be collected from the same sensor (a first sensor) or at least one corroborating sensor. A corroborating sensor is not the first sensor, but may include an identical redundant sensor, a similar sensor, and/or a complementary sensor. Similar sensors measure the same thing as the first sensor, but using different properties. For example, CO can be measured electrochemically or by using infrared. Identical redundant sensors may use the same measuring technology as the first sensor but may be scaled differently and operated in different ranges. Complementary sensors measure different properties from the first sensor but may be used to reach, at least in part, the same conclusion as the first sensor. Corroborating sensors may be located in the same control box as the first sensor, in a different control box in the same vault as the first sensor, or in one or more adjacent vaults.

COMPLEMENTARY CORROBORATION

Where fires are suspected (not just the accumulation of VOCs or H2S) corroborating sensors may provide the corroboration to effectuate an alarm condition. As mentioned above, such corroborating sensors may be located in the same control box as the first sensor, in a different control box in the same vault as the first sensor, or in one or more adjacent vaults.

As mentioned above, complementary sensors measure different properties from the first sensor but may be used to reach, at least in part, the same conclusion as the first sensor. Thus, whether two or more sensors are complementary depends upon the conclusion being reached. For example, when trying to determine if a fire is present, a CO sensor is complementary to a CO2 sensor because carbon monoxide is created in any carbon dioxide (CO2) generating fire. By way of another non-limiting example, when trying to determine if a fire is present, a temperature sensor is complementary to a CO2 sensor because the temperature sensor may detect an increase in temperature at the same time the CO2 sensor detects an increase in CO2. Corroborating sensors can be collocated in a sensor package within a single vault, located in a least one other sensor package within the single vault, and/or located in adjacent vaults.

Table A lists gaseous compounds likely to be encountered in a manhole sorted from lowest to highest density along with their lower explosive limits (“LEL”) and upper explosive limits (“UEL”) for flammable materials.

Boettner et al,“Combustion Products from the Incineration of Plastics,”

Michigan University 1973, prepared for the Office of Research and

Development U.S. Environmental Protection Agency, Washington D.C. 20480. EPA-670/2 -73-049;“Gas Data Book,” 7th Ed. 2001 by Matheson Gas Products; and“Flammability Characteristics of Combustible Gases and Vapors,” 1965, U.S. Department of Interior, Bureau of Mines Bulletin 627. A leftmost column lists classes based on the compound’s density: lighter-than-air (“LTA”), similar- to-air (“STA”), and heavier-than-air (“HTA”). Carbon, which is listed on the last row at the bottom of Table A, is a special case. Carbon is a solid and has a density over three orders of magnitude higher than air, but has an outsized contribution to many manhole explosions.

Table A

The fourth column above, lists a specific gravity (“SG”) for each of the gaseous compounds. Figure 4 illustrates each of three classes of flammable vapors entering the vault 112 from the exemplary connection 118E (e.g., a duct). An arrow 170 illustrates one or more LTA compound, an arrow 172 illustrates one or more STA compound, and an arrow 174 illustrates one or more HTA compound entering the vault 112 Figure 4 also includes LTA zones ZL1 -ZL3, a central STA zone ZS, and HTA zones ZH1 -ZH3. The LTA compound(s) may gravitationally striate into the three LTA zones ZL1 -ZL3 and the HTA

compound(s) may gravitationally striate into the three HTA zones ZH1-ZH3.

The zones ZL2 and ZH2 are combustion zones where each flammable component is above its lower explosive limit (“LEL”), but below its upper explosive limit (“UEL”). The zones ZL1 and ZL3 are below and above the combustion zone ZL2, respectively, and the zones ZH1 and ZH3 are above and below the combustion zone ZH2, respectively. In each of the zones ZL3 and ZH3, there is not enough oxygen present (i.e., the mixture is too rich; the concentration is >UEL) for the flammable component(s) to burn. In each of the zones ZL1 and ZH1 , there is not enough fuel present (i.e , the mixture is too lean; the concentration is <LEL) for the flammable component(s) to burn. The STA compound(s) do not gravitationally striate. Instead, they intermix with the air. While there are dynamic concentration gradients, the STA compound(s) will equilibrate toward a uniform concentration throughout the central STA zone ZS.

Once outside a specific gravity range of about 0.5 to about 2.0 and absent convective air circulation, gases may separate into the striated layers illustrated in Figure 4 The HTA compound(s) tend to sink to the bottom of a structure (e.g., the vault 112). The LTA co pound(s) tend to float to the top of the structure. The STA compound(s) fill central portions between the top and bottom of the volume not filled by the LTA and HTA compound(s). Any gravitational striation is dynamic. Dynamic considerations include the following: new gases that may enter or exit from the connection(s) flow Fc, gases that diffuse or leak from or to the vault 112, and gases that diffuse from one zone to an adjacent zone driven by concentration gradients against gravitational striation. An explosion occurs when a gas or plasma expands at a rate that generates a shock wave. Fire is a complex set of physical and chemical reactions. Almost ail of the plastics, polymers, and rubbers that the electrical industry uses are dominated by a single repeating polymeric unit. A non- limiting example of such a polymeric unit is methylene, which includes a single carbon atom, two hydrogen atoms, and two unpaired electrons represented thusly: -GH2-. There is little difference between all of the different types of polyethylene (“PE”) including high molecular weight PE (“HMWPE”), cross- linked PE (“XLPE”), Linear-Low Density PE (“LLDPE"), Low Density PE

(“LDPE”), High Density PE (“HOPE”) and Tree-Retardant cross-linked PE

(“TRXLPE”) when it comes to their burn chemistry.

If electricity is not involved, there are only two kinds of burning: oxidative decomposition and pyrolysis. When electrical discharges are involved, a third kind of burning, plasmatization (and its reverse), may be present. These three kinds of burning usually occur in the following order: plasmatization, pyrolysis, and oxidative decomposition.

Oxidative decomposition is represented by Equation 1 below and is what most people think of when they contemplate the chemistry of fire.

2— CH2— + 302 (1 )

Pyrolysis is thermal anaerobic (in the absence of oxygen) decomposition of methylene. Pyrolysis may be represented by Equation 2 below.

In Equation 2 above, Greek letters represent integers that satisfy an atom balance that varies greatly depending on conditions. The variable“n” represents a small integer and the variable“m” represents a numerical value between 1 and 3 times the value of the variable“n.” However, the variable“m” may have a value of 4 for methane. Figure 5 is an accounting of different gaseous combustion- pyrolysis products of low density polyethylene (“LDPE”) powder taken from Boettner et ai,“Combustion Products from the Incineration of Plastics” Michigan University 1973, prepared for the Office of Research and Development U.S. Environmental Protection Agency, Washington D.C. 20480, E PA-870/2-73-049. Non-definitive compound designations listed on the y~axis indicate that more than a single species is included. For example, C2H4-6 includes ethane (C2H6) and ethylene (C2H4). Elemental carbon, water, and hydrogen were not measured by the researchers and are not shown in Figure 5.

Figure 6 is a residual gas analyzer (“RGA”) result that quantifies water evolved from combustion/pyrolysis of rubber compounds taken from Zhang, Boggs, et al,“The Electro-Chemical Basis of Manhole Events,” IEEE Electrical Insulation Magazine, Vol. 25, No. 5, 9-10/2009. RGA suffers from an inability to resolve CO if N2 is present as well as to resolve elemental carbon. Note that the x-axis of Figure 6 is not the same as Figure 5. Here the

abundance of each gas is a normalized volume. Differences between Figure 6 and Figure 5 include: fuel (which is SBR/EPR insulation in Figure 6),

temperature conditions, oxygen concentration, and the analytical technique. Additionally, the analytical technique employed to obtain the data of Figure 5 was blind to water vapor and the technique used to obtain the data of Figure 6 was blind to carbon monoxide when nitrogen was present. Both analytical techniques are blind to elemental carbon.

The data of Figures 5 and 8 are reconciled by acknowledging that neither representation is perfect, but both yield similar and complementary results.

Figures 5 and 6 show a relative abundance of the compounds that are formed by pyrolysis. Most likely, every compound that could be formed is formed, but some compounds are simply present in a concentration that is too low to be identified. A polymer, like XLPE, does not burn directly. Instead, the polymer undergoes pyrolysis when it is heated and thus generates gases like those implied by Equation 2. After pyrolysis occurs, the resulting gaseous compounds can mix with oxygen and undergo oxidative decomposition.

Equation 1 does a fine job of representing the net reaction if there is plenty of oxygen present. Incomplete combustion occurs when there is not enough oxygen present to produce the carbon dioxide and water of Equation 1 . Such incomplete combustion is partially represented by Equation 3 below.

Equation 3 properly balances for the combustion-pyrolysis case where there are precisely two oxygen molecules for every three methylene units. The fuel and the oxygen are not well mixed in duct-manhole scenarios. Less oxygen generates more carbon (the black in black smoke), more carbon monoxide, and more hydrogen at the expense of carbon dioxide and water. Figures 5 and 6 display the messy reality that occurs when oxidative decomposition, pyrolysis, and incomplete combustion occur simultaneously as represented by Equations 1 -3.

Turning now to the third kind of burning, namely plasmatization and its reverse, an electrical arc has a temperature of between 16,900°K (30,GQG°F) and 28,Q00°K (50,QQQ°F). At these temperatures, the chemistry is entirely different from what is described above. Every atom is torn from every other atom and many electrons are ripped from their nuclei. Equation 4 below shows the net result of these first two steps. where ...

e = Y + 2 +2v + 2o (5)

The precise charge of every atom on the right side of Equation 4 above is dependent on the temperature of the plasma and hence the value of epsilon. The number of free electrons balances the positive charges as shown by Equation 5 above. Hydrogen has only a single electron to contribute to the plasma cloud. Carbon, nitrogen, and oxygen have 6, 7, and 8 electrons respectively. Each incremental electron is more difficult to strip than the previous electron and requires a higher temperature to do so. Other atom(s) and/or moiecule(s) that is/are consumed in the arc flash are not shown in Figure 6. Clay fillers in EPR insulation, aluminum and copper conductors and neutrals, water, carbon black, and anything else nearby are broken into their respective constituent atoms and electrons are stripped from their outermost orbitals.

Plasma cannot burn. The atoms are too hot to react with each other.

Three lessons may be gained from the three kinds of burning.

The first lesson involves burning and explosion. All burning involves both pyrolysis and combustion as a minimum. Where combustion predominates, smoke is clear or white (water vapor). Where pyrolysis predominates, smoke is black (carbon) and includes substantial carbon monoxide. When electricity is involved, there is some level of plasma formation. For a primary cable failure where the voltage to ground is at least several thousand volts, the plasma may be the predominant route, but there will always be some combustion (unless the environment is completely anaerobic) and some pyrolysis. For secondary cable failures where the voltage to ground is typically just several hundred volts, plasma is present, but at a subdued level compared to a brief high current primary fault. Secondary“faults” can persist for days and while the

plasmatization, pyrolysis, and combustion proceed at a slow pace, the accumulation of flammable gases and solid carbon in confined spaces together with ample time to mix with atmospheric oxygen may create the conditions for the largest possible chemical explosions. Sun, Ma and Boggs,“Initiation of a Typical Network Secondary Manhole Event,” IEEE Electrical Insulation

Magazine, v.31.n.3, May/June 2015.

The second lesson involves carbon monoxide. Carbon monoxide is the largest contributor to secondary network explosions. Table A above shows carbon monoxide is an STA compound with a wide flammable range spanning 12.5% _v to 74.2% _v. Further, as shown in Figures 5 and 6, carbon monoxide is one of the most abundant gases created in the conditions likely to be encountered in a secondary network. While we cannot ignore the

hydrocarbons, they are not as abundant and hence are not of the greatest concern. The third lesson involves carbon. Carbon is the second largest contributor to secondary network explosions. As carbon plasma cools, it remains a gas until the temperature reaches about 4,098°K (6,917°F) where it becomes a liquid. The liquid state of carbon does not last long as it solidifies at about 3,823°K (6,422°F). After solidifying, atomic carbon has a very high surface energy as a result of its four unpaired electrons. Adjacent carbon atoms tend to agglomerate into dust particles several microns in diameter. The agglomerates have large surface areas and high porosity.

Even though the density of the solid phase of carbon is over 1 ,700 times the density of air, the agglomerates are predominantly gaseous voids filled with the very same gases that surround the particle. As a consequence, the bulk density places carbon agglomerates alongside HTA gases. The slightest convection currents keep the agglomerates aloft. These carbon agglomerates are what make black smoke black. Thus, although solid carbon is not gas, solid carbon agglomerates act as though they are a gas, and when the terms“gas,”“gases,” or“gaseous" are used herein, carbon agglomerates are included.

When mixed with air, these particles can be ignited and

participate in a dust explosion. A hetero-explosion occurs when these particles are mixed with air, carbon monoxide, hydrogen, and smaller amounts of hydrocarbon gases and ignited. The yield of the hetero-explosion depends upon one or more of the following:

1. quantities of each fuel;

2. relative quantity of oxygen to each fuel;

3. relative quantities of gaseous components that retard

combustion most notably including, nitrogen, carbon dioxide, and water vapor, the latter two being products of oxidative combustion;

4. uniformity of how the aforementioned items 1 , 2 and 3 are mixed (e.g., better mixing yields more explosive energy); 5. location of the ignition source relative to the center of mass of the cloud delineated by explosive limit concentration boundaries. ACTIVE DILUTION

Referring to Figure 3, as mentioned above, the manhole event suppression system 140 may ventilate the underground vault 112 Thus, the manhole event suppression system 140 may be used to implement variable active ventilation. However, such ventilation may occur by an alternate means.

Variable active ventilation is referred to as dilution of the first type.

Dilution of the first type is accomplished by changing an overall rate of atmospheric turnover in the underground vault 112. For example, doubling of the exhaust rate approximately halves a concentration of those gases that are rare in the internal atmosphere 124, but are entering the underground vault 112 from a fire event. Conversely doubling of the exhaust rate increases the concentration in the internal atmosphere 124 of those gases that are abundant in the external atmosphere 122, namely oxygen and nitrogen. It is preferable to be able to flexibly control the flow rate and direction sca!ab!y from zero to at least one hundred percent and zero to minus one hundred percent of an air movement device, but another alternative is to have two or more preset flows including for example any two values referred to as off, low, medium and high. Yet another alternative is to turn an air movement device on and off over periodic time spans (e.g. fan 100% on for 30 seconds, fan 0% for 30 seconds yields approximately a 50% flow over a 60 second period). In the event of an emergency or potentially pending emergency, it is preferred to be able to run the air movement device above its 100% design speed.

As a practical matter, a maximum exhaust rate during routine (or non-emergency) operation is constrained by public perception. A jet-like exhaust rate would be noisy and considered a nuisance. On the other hand, noise might be a desirable feature when preventing an imminent explosion. No matter what the maximum exhaust rate may be, there are circumstances where dilution of the first type will simply be unable to provide sufficient dilution to avoid the occurrence of a manhole event (e.g., a fire and/or explosion). In other words, enough of the undesired gaseous composition 164 (see Figure 1 ) cannot be exhausted from the underground vault 112 (e.g., via a high duct flow event) to provide readings from the fire detection sensor(s) 216 that are within desired sensor range(s) and/or prevent a buildup of flammable gases

approaching an effective lower explosive limit. Put another way, an active ventilation system (e.g., the manhole event suppression system 140) can be overwhelmed by a large influx of flammable gas(es).

The System Controller 190 may be configured to determine a percentage corrected lower explosive limit (“%CLEL") for at least one gas inside the underground vault 112 and instruct the air moving device 132 (see Figure 1 ) to increase the exhaust flow rate of the exhaust flow FE when the %CLEL is equal to or greater than a threshold value. The air moving device 132 (see Figure 1 ) may be configured to increase the exhaust flow rate in response to that instruction. The threshold value may be 100% times a safety factor (e.g., between 33% and 100%). By way of a non-limiting example, the safety factor may be 75%.

Direct sample dilution is referred to as dilution of the second type. Dilution of the second type refers to fresh air (from the external atmosphere 122) intermixing with a sample portion of the exhaust that passes by the fire detection sensor(s) 216. Thus, dilution of the second type is not constrained by the range of possible exhaust rates. However, dilution of the second type does nothing to change the internal atmosphere 124 inside the underground vault 112. When it is desirable to dilute potentially explosive gases within the underground vault 112, dilution of the first type may be used to exhaust the internal atmosphere 124 up to the maximum exhaust rate. The greatest flexibility is achieved by the combination of both dilution types.

While dilution of the first type is limited to 0% to 100% of a rated exhaust rate (or perhaps in emergency conditions a value greater than 100%), dilution of the second type is infinitely scalable. The rated exhaust rate is a maximum rate specified by the manufacturer of an air moving device. The manufacturer tested the air moving device operating at the rated exhaust rate. However, in an emergency, the rated exhaust rate may be exceeded. A sample air moving device 178 may be used to move fresh air from the external atmosphere 122 past the fire detection sensor(s) 216. An exhausted air moving device 179 may be used to move an exhausted gas mixture from the exhaust flow FE past the fire detection sensor(s) 216. In such embodiments, one end of a tube 180 or similar conveyance conduit may be placed in fluid communication with the external atmosphere 122 or the fresh air flow FFA. Similarly, one end of a tube 182 or similar conveyance conduit may be placed in fluid communication with the exhaust flow FE. The other end of the tube 180 may deliver a flow FD2 of fresh air to be ixed with a portion of the exhaust flow FE conducted by the tube 182, which is illustrated as a flow FPE. The flow FPE mixes with the flow FD2 in a controlled intermix ratio (“!MR”) that may range from zero to infinity. The flow rates of the flows FD2 and FPE may be controlled by the air moving devices 178 and 179, which may each be implemented using any of a large variety of means well known in the art. By way of a non-limiting example, the air moving devices 178 and 179 may be implemented as a pair of gas pumps and micro-flow control valves actuated by a pair of Proportional-Integral-Derivative (“PID”) controllers. The set-points of the PID controllers may be determined by the monitor 126 and/or the System Controller 190.

By way of another non-limiting example, the sample air moving devices 178 and 179 may be implemented as a pair of positive displacement pumps used to obtain the IMR established by the System Controller 190. The IMR is a ratio of a first volume of exhaust air to a second volume of fresh air. The IMR may be determined using relative displacements of the positive displacement pumps and their cycle frequencies. For example, if a first positive displacement pump is drawing the flow FPE, has a volume of 10 ml/cycle, and is operating at 10 cycles per minute, the first positive displacement pump pumps 100 mi of exhaust air every minute. If a second positive displacement pump is drawing the flow FD2, has a volume of 5 ml/cycle, and is operating at 10 cycles per minute, the second positive displacement pump pumps 50 ml of fresh air every minute. Thus, the IMR would be two-to-one (or 100 ml to 50 ml per minute). If the first positive displacement pump was increased to 30 cycles per minute and the second positive displacement pump remained at 10 cycles per minute, the IMR would be six-to-one (or 300 ml to 50 ml per minute).

The IMR is set by the System Controller 190 to achieve three fundamental ends: (1 ) to determine at least one analyte of interest is nearing a limit of detectability; (2) to validate that at least one of the fire detection sensor(s) 218 in an alarm state is not in that state because of drift; and (3) to calibrate at least one of the fire detection sensor(s) 216 If an analyte is at, near, or above its upper limit of detectability for the relevant sensor(s), the IMR can be reduced to a value as low as zero. If an analyte is at, near, or below its lower limit of detectability for the relevant sensor(s), the IMR can be increased to any value, even approaching infinity, to allow each of the relevant sensor(s) to operate within its acceptable or optimal range. A sensor group may include first and second sensors. There may be circumstances in which the first sensor would benefit from a low IMR, while the second sensor would benefit from a high !MR. In such circumstances, the System Controller 190 may alternate the IMR to get valid sensor readings from the first and second sensors within the same sensor group. In circumstances where the output from the first sensor is more critical to a current condition than the output from the second sensor, the System Controller 190 may choose an IMR that keeps the more critical sensor(s) (e.g., the first sensor) within the sensor group operating in an appropriate range.

As mentioned above, the sensor(s) 128 may be organized into one or more sensor groups. Each sensor group includes at least one of the sensor(s) 128 and is independently plumbed to (or is in communication with) the at least one flow (e.g., an air stream) to be analyzed. For example, more than one sensor group may be used to obtain parameter values for the exhaust flow FE, the fresh air flow FFA, and the connection(s) flow Fc. At least some of the different sensor groups may have different intermix ratios. The intermix ratios of the sensor groups may be established independently by the System Controller 190 so that each sensor group operates within its range.

For example, Figure 20 illustrates an exemplary sample control sub-system 192 that includes three sensor groups G1 , G2, and G3. Each of the sensor groups G1 , G2, and G3 is independently supplied with an IMR that includes a sample stream SFA of the fresh air flow FFA and a sample stream SE of the exhaust flow FE. The sample streams SFA and SE are delivered to the sensor groups G1 , G2, and G3 by pumps Pf and Px, respectively, in

accordance with the IMRs determined by the System Controller 190 for the sensor groups G1 , G2, and G3. The pumps Pf and Px may each be

implemented as a variable speed positive displacement pump.

Each of the sensor groups G1 , G2, and G3 corresponds to pair of valves. For example, the sensor group G1 corresponds to valve SV1 -F and SV1 -X, the sensor group G2 corresponds to valve SV2-F and SV2-X, and the sensor group G3 corresponds to valve SV3-F and SV3-X. The pump Pf is connected to the sensor groups G1 , G2, and G3 by the fresh air valves SV1 -F, SV2-F, and SV3-F, respectively. The pump Px is connected to the sensor groups G1 , G2, and G3 by the exhaust valves SV1 -X, SV2-X, and SV3-X, respectively. The sample control sub-system 192 also includes a pair of valves SV0-F and SV0-X. The pump Pf is connected to a fresh air vent F-V by the fresh air valve SV0-F, and the pump Px is connected to an exhaust vent X-V by the valve SV0-X. The valves SV0-X, SV1 -X, SV2-X, SV3-X, SV0-F, SV1 -F, SV2-F, and SV3-F may each be implemented as a solenoid valve.

Only one of the pairs of valves is open a time. For example, at any moment, only one of the exhaust valves SV0-X, SV1 -X, SV2-X, and SV3-X is in the open position and the other exhaust valves are in closed positions. Similarly, at any moment, only one of the fresh air valves SV0-F, SV1 -F, SV2-F, and SV3-F is in the open position and the other fresh air valves are in closed positions. Thus, the sample control sub-system 192 is configured to deliver the sample streams SFA and SE to only one of the sensor groups G1 , G2, and G3 at a time or to the vents F~V and X-V.

In addition to the vents X-V and F-V, the sample control sub- system 192 illustrated in Figure 20 includes vents G1 -V, G2-V, and G3-V. The vents G1 -V, G2-V, G3-V, X-V, and F-V provide a low pressure drop exhaust for the sample streams SE and SFA downstream of the pumps Px and Pf, respectively. The vents G1 -V, G2-V, and G3-V provide low pressure drop passive venting of ail sample gases (e.g., the sample streams SE and SFA) supplied to each of the sensor groups G1 , G2, and G3, respectively. The vents X-V and F-V provide controlled dumps for the sample streams SE and SFA, respectively, when the system controller 190 is not providing the sample streams SE and SFA to any of the sensor groups G1 , G2, and G3.

The sample control sub-system 192 is configured to provide the sample streams SE and SFA to the sensor groups G1 , G2, and G3

independently and using different intermix ratios for the different sensor groups. For example, if the System Controller 190 sets the IMR for the sensor group G1 to two, the System Controller 190 sends a first command to the pump Px and a second command to the pump Pf. The first command instructs the pump Px to deliver the sample stream SE in accordance with first operating parameters and the second command instructs the pump Pf to deliver the sample stream SFA in accordance with second operating parameters. The first and second operating parameters cause the pumps Px and Pf to deliver two parts exhaust and one part fresh air. By way of non-limiting examples, the first and second operating parameters may be first and second speeds with the first speed being twice the second speed. The System Controller 190 also sends commands to the valves SV0-X, SV1 -X, SV2-X, SV3-X, SV0-F, SV1 -F, SV2-F, and SV3-F. These commands cause the pair of valves SV1 -F and SV1 -X corresponding to the sensor group G1 to be in open positions and the other valves SV0-X, SV2-X, SV3-X, SV0-F, SV2-F, and SV3-F to be in closed positions. Thus, the sample streams SE and SFA delivered by the pumps Px and Pf, respectively, flow only through the valves SV1 -F and SV1 -X to the sensor group G1. Next, the

System Controller 190 may implement different IMRs, one at a time, for the sensor groups G2 and G3 in a similar manner

The exemplary sample control sub-system 192 allows the System Controller 190 to (1 ) independently use different intermix ratios for different sensor groups, (2) operate each of the sensor groups in different modes (e.g., the sensor group G1 may be operating with a current modet equal to ROUTINE, while the sensor group G2 is operating with a current modet equal to

CALIBRATE1 ), (3) utilize different sample rates for different sensor groups, and (4) limit the cumulative exposure of a sensor group to analytes that degrade the long-term sensor performance. For example, some electrochemical sensors have a sensing element that is consumed by exposure to a target analyte or non-target compounds. The System Controller 190 may expose these sensors only when required and subsequently flush the sensors with fresh air (e.g., for the remainder of the sampling interval). By way of another non-limiting example, the System Controller 190 may set a sample rate that limits a cumulative exposure of a particular sensor group to exhaust.

While an exemplary implementation of the sample control sub system 192 has been illustrated in Figure 20, through application of ordinary skill to the present teachings, many alternate implementations may be constructed. For example, the sample control sub-system 192 may include other types or numbers of pumps and/or valves. Additionally, alternate plumbing designs may be used to construct the sample control sub-system 192. Non-limiting examples of these variations include the following:

1. the IMR (or the ratio of the sample streams SE and SFA) delivered to one of the sensor groups G1 -G3 may be set by varying an amount of time that the pair of valves corresponding the sensor group is open instead of varying the first and second operating parameters (e.g., speeds) of the pumps Px and Pf;

2. the IMR (or the ratio of the sample streams SE and SFA) delivered to one of the sensor groups G1 -G3 may be set by employing a pair of proportionai-integral-derivative (“RID”) controllers each together with a variable flow control valve;

3. a single pump design with additional solenoids may be utilized to draw the sample streams SFA and SE from the fresh air and exhaust flows FE and FFA, respectively; and

4. redundant valves and pumps can be employed to add robustness to the sample control sub-system 192.

All of the above changes and others can be employed without departing from the spirit of the present description.

Validation is a quick check for sensor drift. Because drift is independent of dilution and the IMR, any significant perturbation of the IMR will either quickly manifest itself by a change in the sensor output of the analyte or not. The former indicates the perturbation is not caused by sensor drift. On the other hand, the later indicates the perturbation is caused at least in part by sensor drift. Since the output of the sensor of interest is moving either to greater or lesser values, the IMR may be increased or decreased to exasperate rather than mitigate that movement. For example, if a CO sensor detects that the CO is increasing, which suggests that combustion has started, the System Controller 190 may increase the IMR (thus, decreasing fresh air). After the IMR is increased, if the output of the CO sensor merely drifts upwards, this perturbation would have no discernabie impact. On the other hand, if there is a fire, the CO reading would increase by a significant amount. A threshold value may be used to determine whether the increase is significant. Thus, the

System Controller 190 may instruct the sample air moving devices 178 and 179 to make meaningful changes to the IMR to assure that the impact on sensor output is well above a noise level for the sensor. The slope (which is the change in analyte concentration divided by the time interval) can be applied to scale a change in the IMR that will be easy to discern from the historical slope. The noise level for each of the fire detection sensor(s) 216 is continuously calculated and consequential variations are easily recognized as those sensor readings above the noise level. Perturbations of the IMR can be repeated and reversed as many times as required until the System Controller 190 has enough statistical confidence in each of the relevant sensor(s) to take action based on its output.

The third form is direct calibration. Using direct calibration the IMR is set to zero (i.e , 100% fresh air is fed to the fire detection sensor(s) 216) and either assumed atmospheric levels or measured atmospheric levels are used to calibrate the fire defection sensor(s) 216. For example CO2 is generally about 400 ppm in the troposphere. Therefore, 400 ppm may be used as an assumed atmospheric level of CO2. Thus, those of the fire detection sensor(s) 216 configured to measure CO2 concentration may be calibrated to measure 400 ppm when the IMR is set to zero. Alternatively, other sensors that are not inside the vault 112 and can be directly calibrated using well-known and/or conventional methods can provide an actual or measured CO2 level !n this manner, those of the fire detection sensor(s) 216 configured to measure CO2 concentration may be calibrated to the measured CO2 level when the IMR is set to zero. The measured CO2 level is provided to the System Controller 190 via a wired or wireless data connection (not shown).

Dilution of both the first and second types are referred to as “active dilution.” The time constant (T tau) of dilution of the first type is quite long, generally at least several minutes. On the other hand, the time constant (T tau) of dilution of the second type is quite short, generally on the order of less than 60 seconds.

Sensor drift is independent of active dilution. This independence from dilution means that it is possible to confirm drift when Calibrationless Operation uses active dilution.

Since drift is independent of dilution, actively altering the dilution rate can test the hypothesis that the alarm condition is the result of a sudden drift. A negative result to this hypothesis confirms the concentration change is bona fide.

CALIBRATIONLESS OPERATION

Figure 7 A is a flow diagram of a method 200-A that implements Calibrationless Operation of the fire detection sensor(s) 216 installed inside the underground vault 112 (see Figure 1 ). The method 200-A is performed by the monitoring system 102.

As mentioned above, the sensor(s) 128 may include the water level sensor 214 and the fire detection sensor(s) 216. The Calibrationless Operation implemented by the method 200-A may not be applicable to the water level sensor 214. In such embodiments, the method 200-A may be performed with respect to only the fire detection sensor(s) 216. For ease of illustration, the method 200-A will be described as being performed with respect to only a sensor 128A (see Figure 3), which is one of the fire detection sensor(s) 216. However, the fire detection sensor(s) 216 may include any number of sensors and the method 200-A may be performed with respect to any number of sensors.

The System Controller 190 (see Figures 1 and 3) records a mode associated with the sensor 128A (see Figure 3) each time block 215-C (see Figure 7C) is performed for the sensor 128A in an evaluate method 200-C (see Figure 7G). Thus, a number of mode values may be stored for the sensor 128A (see Figure 3). For example, the System Controller 190 (see Figures 1 and 3) stores a current modet and a previous moden for the sensor 128A (see Figure 3). The previous moden stores the mode value immediately preceding the current modet. In first block 210-A, the System Controller 190 (see Figures 1 and 3) sets both the current modet and the previous moden of the sensor 128A (see Figure 3) equal to INITIALIZE

In block 220-A, the monitor 126 sends a request to the System Controller 190 (see Figures 1 and 3) for flag values and system parameters. In alternative embodiments, the System Controller 190 may push the flag values and system parameters to the monitor 126 In such embodiments, the block 220-A may be omitted.

In block 230-A, the System Controller 190 sends the flag values and system parameters to the monitor 126. For example, the System

Controller 190 sends the current modet is equal to INITIALIZE to the monitor 126 The monitor 126 stores these values in the memory 130M.

The flag values may include the current modet, the previous modet-i, a Trigger Condition (“TC"), a trip state (“TS”), a report time, an event type indicator, and an Alarm State (“AS”) associated with each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). The current modet and the previous moden may each be set to one of a plurality of mode values. By way of a non-limiting example, the plurality of mode values may include INITIALIZE, ROUTINE, TRIPPED, CALIBRATED CALIBRATE2, DRIFT1 , and DRIFT2

The TC may be set to one of a plurality of Trigger Condition values. By way of a non-limiting example, the TC may be set to a triggered value (e.g., one) or a not triggered value (e.g., zero). Non-limiting illustrative examples of the kinds of events that might trigger alarm condition(s) include the following:

1. Oxidative Decomposition (“OD”);

2. Pyrolysis (“PY”);

3. Plasmatization (“PL”); and

4. Flammable gas accumulation (“FA”) Two or more of the above alarm condition(s) may be combined or collapsed for user simplicity. For example, OD, PY, and PL may be combined into a single alarm condition called Fire (“FI”).

The TS may be set to one of a plurality of Trip State values. By way of a non-limiting example, the TS may be set to a not tripped value (e.g., zero), a single trip value (e.g., one), or a consecutively tripped value (e.g., two). The not tripped value (e.g., zero) indicates the sensor has not detected any potential alarm conditions (or no-event operation). The single trip value (e.g., one) indicates a first time that the single sensor 128A (see Figure 3) has detected a single potential alarm condition. The consecutively tripped value (e.g., two) indicates that the sensor 128A (see Figure 3) has repeatedly detected the same potential alarm condition.

The event type indicator stores one of a plurality of event type values. By way of a non-limiting example, the event type values may include a no event value, a combustion value, and an FGA (i.e. , flammable gas

accumulation) value.

The AS stores an alarm state value and an associated time for each of the fire detection sensor(s) 216 (e.g , the sensor 128A illustrated in Figure 3). The alarm state value may each store one of a plurality of alarm state values. By way of a non-limiting example, the alarm state values may include a low value, an intermediate value, and a high value.

The report time may be set to one of a plurality of report time values. By way of a non-limiting example, the report time may be set to a routine value (e.g., 15 minutes) or a non-routine value (e.g., 30 seconds).

The system parameters may include a baseline Co for each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3), a baseline time for each of the fire detection sensor(s) 216 , and a fan speed for an air moving device 132, an air moving device 178, and/or an air moving device 179. The fan speed may be set to one of a plurality of fan speed values. By way of a non-limiting example, the fan speed may be set to off, full (or 100%), and a numeric value corresponding to a number of consecutive seconds that the fan is on over a predetermined time period (e.g., 60 seconds). In block 240-A, the monitor 126 performs a method 200-B (see Figure 7B). Thus, the instructions 1301, when executed by the processor 130P, are configured to instruct the processor 1 SOP to perform the method 200-B (see Figure 7B). The instructions 1301, when executed by the processor 130P, may be configured to instruct the processor 130P to perform block 22G-A, when present, and block 230-A.

In block 2S0-A, the System Controller 190 performs the evaluate method 200-C (see Figures 7C-7E).

Then, the method 20G-A terminates.

Figure 7B is a flow diagram of the method 20Q-B performed by the monitor 126. For ease of illustration, the fire detection sensor(s) 216 will be described as including only the sensor 128A (see Figure 3). Thus, the method 200-B will be described as being performed with respect to only the sensor 128A (see Figure 3). However, the fire detection sensor(s) 216 may include any number of sensors and the method 200-B may be performed with respect to any number of sensors.

In first block 2G5-B, the monitor 126 polls the sensor 128A (see Figure 3) for a sensor value C’ and adds the sensor value C’ to a collection of sensor values collected from the sensor 128A By way of a non-limiting example, the monitor 126 may poll the sensor 128A for a new sensor value C’ periodically with a frequency of about 1 Hz.

Then, in decision block 210-B, the monitor 126 determines whether the current modes is equal to INITIALIZE.

When the current modet is equal to INITIALIZE, in block 215-B, the monitor 126 sets a corrected value C equal to the sensor value C’ collected in block 205-B and adds the corrected value C to a collection of corrected sensor values for the sensor 128A (see Figure 3).

When the current modet is not equal to INITIALIZE, in block 220- B, the monitor 126 corrects the sensor value C’ for drift to obtain the corrected value C and adds the corrected value C to the collection of corrected sensor values for the sensor 128A (see Figure 3). The corrected value C may be calculated as a function of time, temperature, and the sensor value C’. Next, in block 225-B, the monitor 128 calculates statistics in real time for the collection of corrected sensor values accumulated for the sensor 128A (see Figure 3). The statistics may include a mean, a standard deviation, and a linear least squares slope and intercept.

In block 230-B, the monitor 126 determines an integral value for the collection of corrected sensor values accumulated for the sensor 128A (see Figure 3). The data may be numerically integrated in real time as the summation of each trapezoidal area above and/or below a baseline value (e.g., integral value = å½(Ct-Ct-i)*At).

In decision block 235-B, the monitor 126 determines whether the current modet is equal to ROUTINE or TRIPPED.

When the current modet is not equal to either ROUTINE or TRIPPED, the monitor 126 advances to decision block 240-B.

On the other hand, when the current modet is equal to ROUTINE or TRIPPED, in block 245-B, the monitor 128 sets the Trigger Condition (“TC”) for the sensor 128A (see Figure 3). The monitor 126 may set the TC to the triggered value (e.g., one) when the corrected value C has exceeded a threshold value. The threshold value may be a proportional threshold, a derivative threshold, or an integral threshold. The monitor 128 may set the TC to the not triggered value (e.g., zero) when the corrected value C has not exceeded the threshold value.

The corrected value C is an instantaneous concentration of a single analyte, åC is the instantaneous concentration of a group of analytes, and t is time. As mentioned above, Co is the baseline of the sensor 128A (see Figure 3). In block 245-B, the monitor 126 may determine the corrected value C has exceeded the threshold value when a proportional measurement estimate (C/Co or åC/Co), its integral (.fCAt or /lCAt, respectively), or its derivative (AC /At or åAåC/At, respectively), or any combination thereof (a) falls outside of one of upper and lower confidence bounds UB and LB (see Figure 8B) and lies toward a more dangerous condition, or (b) passes an absolute boundary (e.g., exceeds a particular threshold value).

At block 245-B, the monitor 126 may determine the upper and lower confidence bounds UB and LB (see Figure 8B) for each of the fire detection sensor(s) 218 (e.g., the sensor 128A illustrated in Figure 3). As one of ordinary skill in the art will recognize, there is no mathematical distinction between removing sensor drift and accommodating sensor drift and the subsequent examples may use either formulation to mean the same thing. To illustrate the foregoing, consider a first sensor that is reading a true

concentration value of 300 ppm and a newly calibrated second sensor that also reads about 300 ppm. After some time, the second sensor is reading 310 ppm, while the actual concentration remains at 300 ppm. In other words, the output of the second sensor has drifted by +10 ppm. The +10 ppm drift can be either be removed or accommodated. If removal is chosen, the reading is adjusted downward by 10 ppm. On the other hand, if accommodation is chosen, the new calibration level is simply set to 310 ppm.

In block 245-B, the System Controller 190 may address drift by applying a variant of the“Random Walk” model to the sensor’s historical data. Using this approach, a difference between any data point and its prior value (called the series“first difference”) is calculated, transformed, and modeled to determine the upper and lower confidence bounds UB and LB (see Figure 8B) for the change in any two sequential measurements.

!n addition, the upper and lower confidence bounds UB and LB (see Figure 8B) for cumulative changes of subsequent measurements over time, and absolute values (actual sensor readings) are also developed (as illustrated in Figure 8B). The upper and lower confidence bounds UB and LB are based on different confidence levels, and the latter is varied depending on the reliability of the sensor. The upper and lower confidence bounds UB and LB are updated periodically by including new data.

In decision block 250-B, the monitor 126 determines whether the TC of the sensor 128A (see Figure 3) is set to the not triggered value (e.g., zero).

When the Trigger Condition is set to other than the not triggered value (e.g., zero), in block 255-B, the monitor 128 sets the trip state (“TS”) of the sensor 128A (see Figure 3). For example, if the TS of the sensor 128A is the not tripped value (e.g., zero), the monitor 126 may increase (or increment) that TS to the single trip value (e.g., one). Similarly, if the TS of the sensor 128A is set to the single trip value (e.g., one), the monitor 126 may set the IS equal to the consecutively tripped value (e.g., two), which is the highest possible TS for a single sensor. The monitor 126 may also set the report time associated with the sensor 128A equal to the non-routine value (e.g. , 30 seconds).

!n decision block 260-B, the monitor 126 determines whether the current modet is equal to ROUTINE. When the current modet is equal to ROUTINE, in block 265-B, the monitor 126 sets the current modet to TRIPPED. On the other hand, when the current modet is not equal to ROUTINE, the monitor 126 advances to decision block 240-B.

In decision block 240-B, the monitor 126 determines whether the report time has elapsed. When the report time has not elapsed, the monitor 126 advances to block 270-B. On the other hand, when the report time has elapsed, in block 275-B, the monitor 126 uploads the collection of corrected sensor values, the collection of sensor values, and the TS for the sensor 128A (see Figure 3) to the System Controller 190. Then, the monitor 126 advances to block 270-B.

In block 270-B, the monitor 126 checks (e.g., a download buffer) for new flag values and sensor parameters received from the System Controller 190. If new values are available, the monitor 126 stores them in the memory 1 SOM. The monitor 126 may over-write its previous values with the new values. Then, the monitor 126 returns to block 205-B to continue the polling loop.

When the monitor 126 determines in decision block 250-B that the Trigger Condition is set to the not triggered value (e.g., zero), the monitor 126 advances to decision block 28Q-B. In decision block 2S0-B, the monitor 126 determines whether the current modet is equal to TRIPPED.

When the current modet is not equal to TRIPPED, the monitor 126 advances to decision block 240-B.

When the current modet is equal to TRIPPED, in block 285-B, the monitor 126 sets the current modet equal to ROUTINE and sets the report time equal to the routine value (e.g., 15 minutes) for the sensor 128A (see Figure 3). Then, the monitor 126 advances to decision block 240-B. Thus, the monitor 126 may use the method 200-B to supply, to the System Controller 190, the collection of corrected sensor values, the collection of sensor values, and the TS for each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3) at each expiration of the report time for the sensor. In other words, the monitor 126 may use the method 200-B to continuously supply information to the System Controller 190 collected from each of the fire detection sensor(s) 216 (see Figure 3).

Figures 7C-7E are a flow diagram of the evaluate method 20Q-C performed by the System Controller 190.

Referring to Figure 7C, in first block 205-C, the System Controller 190 receives the information uploaded by the monitor 126 in block 275-B (see Figure 7B) in method 200-B (see Figure 7B).

In decision block 210-C, the System Controller 190 determines whether the current modet is equal to INITIALIZE.

When the current modet is equal to INITIALIZE, the System Controller 190 advances to block 215-C. In block 215-C, the System Controller 190 records the information uploaded to the System Controller 190 by the monitor 126 in block 275-B (see Figure 7B) in method 200-B (see Figure 7B). For example, the System Controller 190 records the current modet, the fan speed, and the report time. Then, in block 273, the System Controller 190 may communicate (e.g., push) to the monitor 126 any operational flag changes including the current modet, the previous modet-i, the fan speed, and the report time.

When the current modet is not equal to INITIALIZE, the System Controller 190 advances to decision block 220-C. In decision block 220-C, the System Controller 190 determines whether the current modet is equal to DRIFT!

When the current modet is equal to DRIFT! the System

Controller 190 advances to block 225-C. In block 225-C, the System

Controller 190 performs a dilution one test method 200-R (see Figure 7R).

Then, the System Controller 190 advances to the block 215-C. When the current modet is not equal to DRIFT! the System Controller 190 advances to decision block 230-C In decision block 230-C, the System Controller 190 determines whether the current modet is equal to DRIFT2

When the current modet is equal to DRIFT2, the System

Controller 190 advances to block 235-C. In block 235-C, the System

Controller 190 performs a dilution two test method 2Q0-S (see Figure 7S).

Then, the System Controller 190 advances to the block 215-C.

When the current modet is not equal to DRIFT2, the System Controller 190 advances to decision block 240-C. In decision block 240-C, the System Controller 190 determines whether the current modes is equal to TRIPPED. The decision in decision block 240-C is“YES” when the current modet is equal to TRIPPED. Otherwise, the decision in decision block 240-C is “NO.”

When the decision in decision block 240-C is“YES," the System Controller 190 advances to block 20S-D (see Figure 7D). Referring to Figure 7D, in block 205-D, the System Controller 190 performs a corroborate method 200-I (see Figure 7I). The System Controller 190 calculates a weighted TS sum value when the System Controller 190 performs the corroborate method 200-I (see Figure 7I). Then, in block 210-D, the System Controller 190 performs a coordinate method 200-J (see Figure 7J). The weighted TS sum value may be modified (e.g., increased) when the System Controller 190 performs the coordinate method 200-J (see Figure 7J). Next, the System Controller 190 advances to decision block 215-D.

In decision block 215-D, the System Controller 190 determines whether the weighted TS sum value is greater than or equal to an alarm threshold (“AT”). By way of a non-limiting example, the AT may be 3.5. If the weighted TS sum value is greater than or equal to the AT, validation is warranted. Otherwise, validation is not warranted. The decision in decision block 215-D is“YES” when the weighted TS sum value is greater than or equal to the AT. Otherwise, the decision in decision block 215-D is“NO.”

When the decision in decision block 215-D is“NO,” in block 220- D, the alarm state value of the AS for the current time (t) is set to the low value (e.g., zero). The event type indicator may also be set to the no event value (e.g. to zero). Then, in block 225-D, the System Controller 190 performs a lowest notification method 200-H (see Figure 7H). Next, the System

Controller 190 advances to block 215-C.

When the decision in decision block 215-D is“YES,” in block 230- D the System Controller 190 performs a calculate method 200-K (see Figure 7K). Then, in decision block 235-D, the System Controller 190 determines whether the alarm state value of the AS for the current time (t) is greater than the low value (e.g , zero). The decision in decision block 235-D is“YES,” when the alarm state value of the AS for the current time (t) is greater than the low value. Otherwise, the decision in decision block 235-D is“NO.”

When the decision in decision block 235-D is“NO,” in block 225- D, the System Controller 190 performs the lowest notification method 200-H (see Figure 7H). Then, the System Controller 190 advances to block 215-C.

When the decision in decision block 235-D is“YES,” in block 240- D, the System Controller 190 performs a validate method 200-L (see Figure 7L). Then, the System Controller 190 advances to decision block 245-D whereat the System Controller 190 determines whether the current modet is set to DRIFT1 or DRIFT2. The decision in decision block 245-D is“YES,” when the current modet is set to DRIFT1 or DRIFT2. Otherwise, the decision in decision block 245-D is“NO.”

When the decision in decision block 245-D is“YES,” the System Controller 190 advances to block 215-C.

When the decision in decision block 245-D is“NO,” the System Controller 190 advances to decision block 250-D In decision block 250-D, the System Controller 190 determines whether a validity indicator (obtained in block 240-D) is greater than a validation threshold. The decision in decision block 250-D is“YES,” when the validity indicator is greater than the validation threshold. Otherwise, the decision in decision block 250-D is“NO.”

When the decision in decision block 250-D is“NO,” in block 225- D, the System Controller 190 performs the lowest notification method 200-H (see Figure 7H). Then, the System Controller 190 advances to block 215-C (see Figure 7C). When the decision in decision block 250-D is“YES,” in decision block 255-D, the System Controller 190 determines whether the alarm state value of the AS for the current time (t) is greater than the intermediate value (e.g., one). The decision in decision block 255-D is“YES,” when the alarm state value of the AS for the current time (t) is greater than the intermediate value. Otherwise, the decision in decision block 255-D is“NO.”

When the decision in decision block 255-D is“YES,” in block 280- D, the System Controller 190 performs a highest notification method 200-F (see Figure 7F). Then, the System Controller 190 advances to block 215-C (see Figure 7C).

When the decision in decision block 255-D is“NO,” in block 265- D, the System Controller 190 performs an intermediate notification method 200- G (see Figure 7G). Then, the System Controller 190 advances to block 215-C (see Figure 7C).

Referring to Figure 7 C, when the decision in decision block 240-C is“NO,” the System Controller 190 advances to decision block 24S-C In decision block 245-C, the System Controller 190 determines whether the current modet is equal to CALIBRATE1 or CALIBRATE2.

When the current modet is equal to CALIBRATE1 or CALIBRATE2, the System Controller 190 advances to block 250-C In block 250-G, the System Controller 190 performs a desaturate method 200-0 (see Figure 70). Then, the System Controller 190 advances to block 255-C and performs a calibrate method 20G-P (see Figure 7P). Next, the System

Controller 190 advances to block 260-C and performs a relate method 200-Q (see Figure 7Q). Then, the System Controller 190 advances to block 215-C

Referring to Figure 7E, when the current modet is not equal to CALIBRATE1 or CALIBRATE2, the System Controller 190 advances to decision block 210-E. In decision block 210-E, the System Controller 190 determines whether the elapsed time exceeds a calibration cadence (“CC”) value (e.g., determined by the relate method 200-Q illustrated in Figure 7Q).

When the elapsed time does not exceed the CC value, the System Controller 190 advances to block 220-E. When the elapsed time exceeds the CC value, in block 230-E, the System Controller 190 advances to decision block 230-E whereat the System Controller 190 determines whether dilution of the second type is available.

When dilution of the second type is available, in block 240-E, the System Controller 190 sets the current modet equal to CALIBRATE2. Otherwise, in block 250-E, the System Controller 190 sets the current modet equal to

CALIBRATE1. Then, the System Controller 190 advances to block 220-E

In block 220-E, the System Controller 190 performs the calculate method 2G0-K (see Figure 7K).

Then, in decision block 260-E, the System Controller 190 determines whether the elapsed time exceeds the baseline time for the sensor 128A (see Figure 3). Referring to Figure 7C, when the elapsed time exceeds the baseline time, in block 260-C, the System Controller 190 performs the relate method 200-Q (see Figure 7Q). Then, the System Controller 190 advances to block 215-C.

Referring to Figure 7C, when the elapsed time does not exceed the baseline time, the System Controller 190 advances to block 215-C.

Figure 7F is a flow diagram of the highest notification method 200- F, which the System Controller 190 may perform in block 26G-D (see Figure 7D) of the evaluate method 200-C illustrated in Figures 7C-7E. Referring to Figure 7F, in first decision block 210-F, the System Controller 190 determines whether the alarm state value of the AS for the current time (t) is equal to the alarm state value of the AS for the previous time (t-1 ). When these two alarm state values are equal, the decision in decision block 210-F is“YES."

Otherwise, the decision in decision block 210-F is“NO.”

When the decision in decision block 210-F is“YES,” the highest notification method 200-F terminates.

When the decision in decision block 210-F is“NO,” in decision block 220-F, the System Controller 190 determines whether the event type indicator of the sensor 128A (see Figure 3) is set to the combustion value. The decision in decision block 220-F Is“YES” when the event type indicator of the sensor 128A is set to the combustion value. Otherwise, the decision in decision block 220-F is“NO.”

When the decision in decision block 220-F is“YES,” in block 230-

F, the System Controller 190 sends a severe fire alarm notification to one or more users to thereby notify the user(s). As used herein, the term“user” may refer to an operator of the System Controller 190, an authority (e.g., a

governmental agency), a vault owner, a circuit owner, a first responder, and the like. Then, the highest notification method 2Q0-F terminates.

When the decision in decision block 220-F is“NO,” in block 240-F, the System Controller 190 sends a severe gas alarm notification to the one or more users to thereby notify the user(s). Then, the highest notification method 200-F terminates.

Figure 7G is a flow diagram of the intermediate notification method 200-G, which the System Controller 190 may perform in block 265-D (see Figure 7D) of the evaluate method 20Q-C illustrated in Figures 7C-7E. Referring to Figure 7G, in first decision block 210-G, the System Controller 190 determines whether the alarm state value of the AS for the current time (t) is equal to the alarm state value of the AS for the previous time (t-1 ). When these two alarm state values are equal, the decision in decision block 210-G is“YES.” Otherwise, the decision in decision block 210-G is“NO.”

When the decision in decision block 210-G is“YES,” the

intermediate notification method 200-G terminates.

When the decision in decision block 210-G is“NO,” in decision block 22Q-G, the System Controller 190 determines whether the event type indicator of the sensor 128A (see Figure 3) is set to the combustion value. The decision in decision block 220-G is“YES” when the event type indicator of the sensor 128A is set to the combustion value. Otherwise, the decision in decision block 220-G is“NO.”

When the decision in decision block 220-G is“YES,” in block 230-

G, the System Controller 190 sends a moderate fire alarm notification to the one or more users to thereby notify the user(s). Then, the intermediate notification method 200-G terminates. When the decision in decision block 220-G is“NO,” in block 240-

G, the System Controller 190 sends a moderate gas alarm notification to the one or more users to thereby notify the user(s). Then, the intermediate notification method 200-G terminates.

Figure 7H is a flow diagram of the lowest notification method 200-

H, which the System Controller 190 may perform in block 225-D (see Figure 7D) of the evaluate method 200-C illustrated in Figures 7C-7E. Referring to Figure 7H, in first decision block 210-H, the System Controller 190 determines whether the alarm state value of the AS for the current time (t) is equal to the alarm state value of the AS for the previous time (t-1 ). When these two alarm state values are equal, the decision in decision block 210-H is“YES.”

Otherwise, the decision in decision block 210-H is“NO.”

When the decision in decision block 210-H is“YES,” the lowest notification method 200-H terminates.

When the decision in decision block 210-H is“NO,” in decision block 220-H, the System Controller 190 determines whether the event type indicator of the sensor 128A (see Figure 3) is set to the combustion value. The decision in decision block 220-H is“YES” when the event type indicator of the sensor 128A is set to the combustion value. Otherwise, the decision in decision block 220-H is“NO.”

When the decision in decision block 220-H is“YES,” in block 230- H, the System Controller 190 sends an all clear notification to the one or more users to thereby notify the user(s). Then, the lowest notification method 200-H terminates.

When the decision in decision block 220-H is“NO,” in block 240- H, the System Controller 190 sends a no gas leak notification to the one or more users to thereby notify the user(s). Then, the lowest notification method 200-H terminates.

Figure 7! is a flow diagram of the corroborate method 200-I, which the System Controller 190 may perform in block 205-D (see Figure 7D) of the method 200-C (see Figures 7C-7E). In first block 210-1, the System Controller 190 increases the trip state (TS) for the sensor 128A (see Figure 3). For example, the TS may be increased by one for each sequential alarm condition. As mentioned above, the TS is capped at the consecutively tripped value (e.g., two).

Then, in block 220-I, the System Controller 190 determines the weighted TS sum value for the sensor 128A (see Figure 3). The System

Controller 190 may calculate the weighted TS sum value by totaling the product of the individual TS value and its associated weight for each of the fire detection sensor(s) 216 (e.g., weighted TS sum value = å(TS(N)*W(N))). The weight(s) may be determined in block 245-Q (see Figure 7Q) of the relate method 200-Q (see Figure 7G).

Then, the corroborate method 200-I terminates.

Figure 7J is a flow diagram of the coordinate method 200-J, which the System Controller 190 may perform in block 210-D (see Figure 7D) of the method 200-C (see Figures 7C-7E).

In first block 210-J, the System Controller 190 identifies adjacent vaults (e.g., using a user-defined radius and the geo-coordinates of all of the vaults).

Then, in decision block 220-J, the System Controller 190 determines whether any of the adjacent vaults are in an alarm condition. The decision in decision block 220-J is“YES,” when at least some of the adjacent vaults are in an alarm condition. Otherwise, the decision in decision block 220- J is“NO” and the coordinate method 200-J terminates.

When the decision in decision block 220-J is“YES,” in block 230- J, the System Controller 190 identifies any redundant or complementary sensors in an alarm state that are within the adjacent vaults in an alarm condition. Such sensors are reading corroborating perturbations.

Then, in block 240-J, the System Controller 190 adds the TS of the sensors identified in block 230-J to the weighted TS sum value of each of the vaults identified in block 210-J and to the weighted TS sum of the vault 112. Then, the coordinate method 200-J terminates. Figure 7K is a flow diagram of the calculate method 200-K, which the System Controller 190 may perform in blocks 23Q-D (see Figure 7D) and 220-E (see Figure 7E) of the evaluate method 200-C (see Figures 7C-7E).

The System Controller 190 performs the calculate method 200-K to determine the event type indicator for the sensor 128A (see Figure 3) at the current time (t) and delineate between small and large events. The System Controller 190 may use either a component mass balance or a delineation method and concentration thresholds to estimate event magnitude. The concentration thresholds may include the following values:

1. A burn nuisance threshold (e.g., 0.1 g/s for the component mass balance and 1000 ppm for the delineation method),

2. A burn level delimiter (e.g., 1.0 g/s the component mass

balance and 2000 ppm for the delineation method),

3. A FGA nuisance threshold (e.g., 0.1 g/s the component mass balance and 2000 ppm for the delineation method), and

4. A FGA level delimiter (e.g., 1.0 g/s the component mass

balance and 4000 ppm for the delineation method).

The concentration thresholds may be preset default values, user specified values, or values set by an artificial intelligence algorithm. The concentration thresholds may be specified for all of the vaults or different values may be specified for at least some of the vaults.

In decision block 202-K, the System Controller 190 determines whether VOCs are present inside the vault 112. For example, the decision in decision block 202-K may be“YES” when the System Controller 190

determines VOCs are present, but fire by-products, such as CO, CO2, NO, NO2, and O3, are at non-fire levels. The System Controller 190 may determine that VOCs are present when the concentration of VOCs is greater than 2000 ppm. The System Controller 190 may determine that CO, CO2, NO, NO2, and O3 are at non-fire levels when their concentrations total less than 1000 ppm.

When the decision in decision block 202-K is“YES, ^” in block 204- K, the System Controller 190 sets the event type indicator for the current time (t) and the sensor 128A (see Figure 3) to the FGA value (e.g., two). Then, in block 206-K, the System Controller 190 determines a flammable gas accumulation (“FGA”). Flammable gas accumulation is a rate at which the flammable gas(es) (e.g., VOCs and FteS) are being introduced into the vault 112. The System Controller 190 may perform either a component mass balance or a delineation method to determine the FGA. The component mass balance, energy balance, and water balance are described below. The delineation method may include calculating the FGA using the following

Equation 6:

FGA = Cco + CH ₂ + Cvoc (6)

Next, in decision block 210-K, the System Controller 190 decides whether the FGA is greater than the FGA nuisance threshold. The decision in decision block 210-K is“YES” when the FGA is greater than the FGA nuisance threshold. Otherwise, the decision in decision block 210-K is“NO.”

When the decision in decision block 210-K is“NO,” in block 212- K, the System Controller 190 sets the alarm state value to the low value (e.g., zero). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 210-K is“YES,” in block 230- K, the System Controller 190 decides whether the FGA is greater than the FGA level delimiter. The decision in decision block 230-K is“YES” when the FGA is greater than the FGA level delimiter. Otherwise, the decision in decision block 230-K is“NO.”

When the decision in decision block 230-K is“YES,” in block 232- K, the System Controller 190 sets the alarm state value equal to the high value (e.g., two). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 230-K is“NO,” in block 234- K, the System Controller 190 sets the alarm state value equal to the

intermediate value (e.g., one). Then, the System Controller 190 advances to block 220-K.

In block 220-K, the System Controller 190 stores the alarm state value, the burn rate, and the FGA.

Then, the calculate method 200-K terminates. When the decision in decision block 202-K is“NO,” in block 240- K, the System Controller 190 sets the event type to the combustion value (e.g., one).

Then, in block 242-K, the System Controller 190 determines the burn rate. In block 242-K, the System Controller 190 may perform either the component mass balance (described below) or the delineation method to determine the burn rate. When a component mass balance is used, the burn rate may be expressed as a unit mass consumed per unit time. The delineation method may include calculating the burn rate using the following Equation 7:

Burn Rate = Cco + Cco ₂ ⁺ CNO + CNO - ¹ · Co ₃ + max(G, 10G0 ^* (2G.95% - Co ₂ %)) (7)

When Equation 7 is used, the burn rate may be expressed in ppm.

Next, in decision block 250-K, the System Controller 190 decides whether the burn rate is greater than the burn nuisance threshold. The decision in decision block 250-K is“YES” when the burn rate is greater than the burn nuisance threshold. Otherwise, the decision in decision block 250-K is“NO.”

When the decision in decision block 250-K is“NO,” in block 254- K, the System Controller 190 sets the alarm state value for the current time (t) and the sensor 128A (see Figure 3) to the low value (e.g., zero). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 250-K is“YES,” in decision block 256-K, the System Controller 190 decides whether the burn rate is greater than the burn level delimiter. The decision in decision block 256-K is “YES” when the burn rate is greater than the burn level delimiter. Otherwise, the decision in decision block 256-K is“NO."

When the decision in decision block 256-K is“NO,” in block 260- K, the System Controller 190 sets the alarm state value for the current time (t) and the sensor 128A (see Figure 3) to the intermediate value (e.g., one). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 256-K is“YES,” in block 262- K, the System Controller 190 sets the alarm state value for the current time (t) and the sensor 128A (see Figure 3) to the high value (e.g., two). Then, the System Controller 190 advances to block 220-K.

Then, the calculate method 200-K terminates. Figure 7L is a flow diagram of the validate method 200-L, which the System Controller 190 may perform in block 240-D (see Figure 7D) of the evaluate method 2Q0-G (see Figures 7C-7E). The validate method 200-L may Include two parallel validation processes labeled“DRIFT” and“PERSISTENCE” in Figure 7L. The first (“DRIFT”) validation process confirms that drift has not caused those sensor readings in alarm condition to be in that condition. The second (“PERSISTENCE”) validation process confirms that the alarm condition meets user-defined persistence. As a non-limiting example of persistence, imagine that a truck stops directly over the fresh air inlet of a manhole cover and spews combustion products info the manhole. If that situation persists for only the length of time of a single stop light cycle, an alarm would be a false positive alarm.

In block 210-L, the System Controller 190 performs a drift validation process 200-M (see Figure 7M) and obtains a validity value (“W”).

!n block 220-L, the System Controller 190 performs a persistence validation process 200-N (see Figure 7N) and obtains a persistence value.

In block 230-L, the System Controller 190 totals the persistence value and the W to obtain a validity indicator. Then, the validate method 200-L terminates. Figure 7M is a flow diagram of the drift validation process 2G0-M, which the System Controller 190 may perform in block 210-L (see Figure 71) of the validate method 2GG-L (see Figure 7L).

!n first block 205-M, the System Controller 190 initializes the VV. For example, in block 205-M, the System Controller 190 may set the VV equal to zero.

In decision block 210-M, the System Controller 190 determines whether dilution of the second type is available. The decision in decision block 210-M is“YES” when dilution of the second type is available. Otherwise, the decision in decision block 210-M is“NO.”

When the decision in decision block 210-M is“YES,” in block 215- M, the System Controller 190 performs the dilution two test method 2QG-S (see Figure 7S) and obtains the drift test result. Then, the System Controller 190 advances to decision block 220-M.

When the decision in decision block 210-M is“NO,” in decision block 225-M, the System Controller 190 determines whether dilution of the first type is available. The decision in decision block 225-M is“YES” when dilution of the first type is available. Otherwise, the decision in decision block 225-M is “NO.”

When the decision in decision block 225-M is“NO,” the drift validation process 2Q0-M terminates.

When the decision in decision block 225-M is“YES,” in block 230- M, the System Controller 190 performs the dilution one test method 200-R (see Figure 7R) and obtains the drift test result. Then, the System Controller 190 advances to decision block 220-M.

In decision block 220-M, the System Controller 190 determines whether the TS of the sensor 128A (see Figure 3) is set to the consecutively tripped value (e.g., two). The decision in decision block 220-M is“YES" when the TS of the sensor 128A is set to the consecutively tripped value. Otherwise, the decision in decision block 220-M is“NO.”

When the decision in decision block 220-M is“NO,” the drift validation process 200-M terminates.

When the decision in decision block 220-M is“YES,” in decision block 235-M, the System Controller 190 determines whether the drift test result indicates that the sensor 128A (see Figure 3) has passed. The decision in decision block 235-M is“YES” when the drift test result indicates that the sensor 128A has passed. Otherwise, the decision in decision block 235-M is “NO.”

When the decision in decision block 235-M is“YES,” in block 240- M, the System Controller 190 updates the W. For example, the System

Controller 190 may add one to the W By way of another non-limiting example, the drift test result may be a first value (e.g., one) when the sensor 128A (see Figure 3) passed and a different second value (e.g , zero) when the sensor 128A failed. In such embodiments, the drift test result may be added to the VV. Then, the System Controller 190 returns to decision block 220-M.

When the decision in decision block 23S-M is“NO," in decision block 245-M the System Controller 190 determines whether dilution of the second type is available. The decision in decision block 245-M is“YES" when dilution of the second type is available. Otherwise, the decision in decision block 245-M is“NO."

When the decision in decision block 245-M is“NO,” the System Controller 190 returns to decision block 220-M.

When the decision in decision block 245-M is“YES,” in decision block 25Q-M, the System Controller 190 determines whether the sensor 128A (see Figure 3) should be calibrated. By way of a non-limiting example, the System Controller 190 may determine it is time to calibrate the sensor 128A when at least a predetermined portion (e.g., 10%) of the calibration cadence (“CC”) time has transpired since the previous calibration of the sensor 128A (see Figure 3) The predetermined portion may be specified by a user.

When the decision in decision block 250-M is“NO,” the System Controller 190 returns to decision block 220-M.

When the decision in decision block 250-M is“YES,” in block 255- M, the System Controller 190 performs the calibrate method 20Q-P (see Figure 7P). Then, the System Controller 190 returns to decision block 220-M.

Figure 7N is a flow diagram of the persistence validation process 200-N, which the System Controller 190 may perform in block 220-L (see Figure 71) of the validate method 2Q0-L (see Figure 71).

!n first block 210-N, the System Controller 190 determines the event time for the sensor 128A (see Figure 3). By way of a non-limiting example, the event time may be the sample time minus the event start time.

The event start time is the time when the first sensor tripped (e.g., when any TS(N) > 0). Then, in decision block 220-IM, the System Controller 190 determines whether the alarm state value at the current time is greater than the intermediate value (e g. , one), meaning the event is large. The decision in decision block 220-N is“YES” when the event is large. Otherwise, the decision in decision block 220-N is“NO.”

When the decision in decision block 220-N is“YES,” in block 230- N, the System Controller 190 sets the persistence value equal to the event time (determined in block 210-N) divided by a large persistence divisor. The large persistence divisor may be user defined or calculated by the System

Controller 190. The greater the persistence divisor, the greater persistence is required to trigger an alarm state. For example, if the event is large, the large persistence divisor is equal to 80 seconds, and the event time is 30 seconds, the persistence value would equal 0.5 (30 / 80 = 0.5). Then, the persistence validation process 200-N terminates.

When the decision in decision block 220-N is“NO,” the event is small. In block 240-N, the System Controller 190 sets the persistence value equal to the event time (determined in block 210-N) divided by a small persistence divisor. The small persistence divisor may be user defined or calculated by the System Controller 190. For example, when the event is small, the small persistence divisor is equal to 300 seconds, and the event time is 30 seconds, the persistence value would equal 0.1 (30 / 300 = 0.1 ). Then, the persistence validation process 200-N terminates.

Figure 70 is a flow diagram of the desaturate method 200-0, which the System Controller 190 may perform in block 250-C (see Figure 7C) of the evaluate method 200-C (see Figures 7C-7E). For sensors that are at or near their saturation limits, the System Controller 190 may perform the desaturate method 200-0, which allows perturbations in dilution to bring the sensor back into its operational range.

In first block 210-0, the System Controller 190 may record the statistics determined in blocks 225-B and 230-B (see Figure 7B) of the method 200-B (see Figure 7B). In decision block 220-0, the System Controller 190 determines whether dilution of the second type is available. The decision in decision block 220-0 is“YES” when dilution of the second type is available. Otherwise, the decision in decision block 220-0 is“NO.”

When the decision in decision block 220-0 is“YES,” in block 230- 0, the System Controller 190 performs a dilution two range method 200-W (see Figure 7W). Then, the desaturate method 200-0 terminates.

When the decision in decision block 220-0 is“NO,” in decision block 240-0, the System Controller 190 determines whether dilution of the first type is available. The decision in decision block 240-0 is“YES” when dilution of the first type is available. Otherwise, the decision in decision block 240-0 is “NO.”

When the decision in decision block 240-0 is“NO,” the desaturate method 200-0 terminates.

When the decision in decision block 240-0 is“YES,” in block 250- 0, the System Controller 190 performs a dilution one range method 2Q0-V (see Figure 7V). Then, the desaturate method 200-0 terminates.

Figure 7P is a flow diagram of the calibrate method 200-P, which the System Controller 190 may perform in block 25S-C of the evaluate method 200-G (see Figures 7C-7E) and in block 255-M of the drift validation process 200-M (see Figure 7M). The System Controller 190 may use the calibrate method 200-P to calibrate the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). The fire detection sensor(s) 216 (see Figure 3) may be recalibrated routinely when the calibration cadence time is exceeded (and the current modet is set to CALIBRATE2 in block 240-E or CALIBRATE1 in block 25Q-E of Figure 7E) or on demand to confirm accurate values when an event is detected or an unusual circumstance suggests an additional calibration may be prudent.

In first block 210-P, the System Controller 190 may record the statistics determined in blocks 225-B and 230-B (see Figure 7B) of the method 200-B (see Figure 7B). In decision block 22G-P, the System Controller 190 determines whether dilution of the second type is available. The decision in decision block 220-P is“YES” when dilution of the second type is available. Otherwise, the decision in decision block 220-P is“NO.”

When the decision in decision block 220-P is“YES," in block 230- P, the System Controller 190 performs a dilution two calibration method 200-U (see Figure 7U). Then, the calibrate method 20G-P terminates.

When the decision in decision block 220-P is“NO,” in decision block 240-P, the System Controller 190 determines whether dilution of the first type is available. The decision in decision block 240-P is“YES ^” when dilution of the first type is available. Otherwise, the decision in decision block 240-P is “NO.”

When the decision in decision block 240-P is“NO,” the calibrate method 200-P terminates.

When the decision in decision block 240-P is“YES,” in block 250- P, the System Controller 190 performs a dilution one calibration method 20G-T (see Figure 7T). Then, the calibrate method 200-P terminates.

Figure 7Q is a flow diagram of the relate method 200-Q, which the System Controller 190 may perform in block 280-C (see Figure 7C) of the evaluate method 20G-C (see Figures 7C-7E). The System Controller 190 performs the relate method 200-Q to find statistical relationships between each sensor’s values (C(N)) and both time and temperature (t and T, respectively). Relationships may be determined for proportional, derivative, and/or integral trends.

In first block 205-Q, the System Controller 190 reads sensor values over statistically relevant historical periods (e g. , the baseline time or greater). In block 205-Q, the System Controller 190 may ignore data

associated with alarm state values other than the low value (e.g., zero) and/or data associated with a current modet other than ROUTINE.

In block 210-Q, the System Controller 190 fits the relevant sensor data to a model. For example, the System Controller 190 may fit the relevant sensor data to a linear equation, such as Equation 8 below: Y = ml + m’T + b (8)

!n Equation 8, a variable m is time-based DRIFT slope, a variable m’ is a temperature-based slope, a variable b is the Y-axis intercept, and a variable Y is the difference between a sensor reading and its assumed (calibrated or imputed) value. While Equation 8 may be used to model the data, other equations may also be used. For example, if a linear function of C to time (t) or temperature (T) does not adequately fit the data, additional terms, different equation forms, or variable transformations may be used to reflect such non- linearities.

In block 215-Q, the System Controller 190 determines a threshold concentration limit (e.g , using a user or A! chosen confidence level) for each sensor.

In block 220-Q, the System Controller 190 determines a threshold concentration derivative limit (e.g , using a user or A! chosen confidence level) for each sensor. The derivative (or slope) is with respect to concentration over time.

In block 225-Q, the System Controller 190 determines a threshold concentration integral limit (e.g., using a user or Al chosen confidence level) for each sensor.

In block 230-Q, the System Controller 190 identifies a time of day (e.g., in the diurnal cycle) when the temperature is likely to be lowest.

In block 235-Q, the System Controller 190 determines a calibration cadence (“CC”) value. By way of a non-limiting example, the calibration cadence value may be set to 24 hours. Calibration is best done at the lowest temperature, which is determined in block 230-Q. The coolest part of the day in the manhole may depend greatly on the local weather because the temperature of the vault 112 is driven by outside air temperature and load on cables and equipment. Historical values, weather forecasts, and/or load forecasts can be referenced to choose the best time. The slope of the drift is another factor in setting the calibration cadence value. If the drift is not material, the calibration cadence value can be lengthened. On the other hand, if drift is a material issue, the calibration cadence value can be shortened.

Calibration with dilution of the second type essentially takes the sensors off-line during a short calibration period. Therefore, maximizing the calibration cadence value provides the most robust monitoring when calibration with dilution of the second type is used.

!n block 240-Q, the System Controller 190 determines a baseline cadence (“BLC”) value. By way of a non-limiting example, the BLC value may be set to 24 hours. The BLC value is a length of time that elapses between the recalculation of the sensor baseline and threshold values. If the slope of the drift and the noisiness of the data are consistent across two baselines, the BLC value may be increased. The converse suggests a shortening of the BLC value.

In block 245-G, the System Controller 190 determines a weight for each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). For example, each of the fire detection sensor(s) 216 (see Figure 3) may be assigned a weight between zero and one. A weight of zero causes that sensor to be ignored. A weight of zero may be appropriate for a sensor that has failed. A weight of one indicates that the sensor is working as designed and is believed to be providing reliable data. The System Controller 190 may use one or more of the following considerations when assigning a weight to each of the fire detection sensor(s) 216 (see Figure 3):

1. Sensor signal to noise

a. time-based

b. temperature-based

2. Sensor drift

a. absolute drift

b drift stability (second derivative)

3. Sensor within design range

4. Time since calibration

5. Complementary/redundant sensors corroboration a. Co-located

b. Adjacent vaults In block 250-Q, the System Controller 190 records at least some of the values obtained during the performance of the relate method 2G0-G (e.g., baseline values and trigger parameters). The System Controller 190 may download at least some of the values obtained during the performance of the relate method 20Q-G to the monitor 126. Then, the relate method 2G0-Q terminates.

Figure 7R is a flow diagram of the dilution one test method 200-R, which the System Controller 190 may perform in block 225-C (see Figure 7C) of the evaluate method 2QG-C (see Figures 7C-7E) and in block 2304/1 (see Figure 7M) of the drift validation process 200-M (see Figure 7M). When performing the dilution one test method 200-R, the System Controller 190 adjusts the speed of the air moving device 132 to test if concentrations are perturbed. No perturbation means drift is implicated. On the other hand, perturbations mean measurement is real.

In first decision block 204-R, the System Controller 190 determines whether the previous modet-i is set to DRIFT! When the previous modet-i is set to DRIFT1 , in block 206-R, the System Controller 190 increments a driftl iteration counter (e.g., adds one to the driftl iteration counter). Then, the System Controller 190 advances to decision block 210-R

When the previous modet-i is not set to DRIFT1 , in block 208-R, the System Controller 190 initializes the driftl iteration counter to an

initialization value (e.g., zero). Then, the System Controller 190 advances to decision block 210-R.

In decision block 210-R, the System Controller 190 determines if the driftl iteration counter is equal to the initialization value. The decision in decision block 210-R is“YES” when the driftl iteration counter equals the initialization value. Otherwise, the decision in decision block 210-R is“NO. ^”

When the decision in decision block 210-R is“YES,” in block 220- R, the System Controller 190 saves the previous fan speed then reduces fan speed by half. The System Controller 190 also sets the current modes equal to DRIFT 1 . The fan speed may refer to the speed of the air moving device 132. Then, the System Controller 190 advances to decision block 230-R. When the decision in decision block 21 0-R is“NO,” in block 240- R, the System Controller 190 performs tests to identify perturbations. The System Controller 190 may evaluate the concentration of one or more of following components to determine whether statistically convincing

perturbations have occurred within Mi (tau = time constant for dilution of the first type) of the fan speed being decreased in block 220-R. By way of a non limiting example, the value of M may be set initially to two and the value of t may be set initially to 300 seconds. Thus, the System Controller 190 may evaluate the concentration of one or more of following components about 600 seconds after the fan speed is decreased in block 220-R. The following are examples of statistically convincing perturbations:

1 . CH _J should increase from V toward 2V-Cfresh;

2. Cco ₂ should increase from W toward 2W-Cfresh;

3. Cco should increase from X toward 2X-Gfresh;

4. Cvoc should increase from Y toward 2Y-Cfresh;

5. Co ₂ should decrease from Z toward 2Z-Cfresh;

6. dC/dt should be positive for CO2, CO, and VOC; and

7. dC/dt should be negative for O2.

In the above tests, Ctresh is the concentration of the component in fresh air. For example, the value of Cfresh may be 400 ppm for CO2, 10 ppm for CO, 0 ppm for VOC, and 21.2% for O2. The variables“V,”“W,”“X,”“Y,” and“Z” above are the concentrations of H2, CO2, CO, VOC, and O2, respectively, before or at the time the fan speed is decreased in block 220-R.

Thus, if the concentration of one of the above listed components changes by less than the amount indicated, drift is implicated. Otherwise, the perturbation(s) is/are not caused by drift and may indicate that a manhole event (e.g., a fire or flammable gas accumulation) is occurring.

When block 240-R is complete, the System Controller 190 advances to decision block 230-R.

In decision block 230-R, the System Controller 190 determines whether the drift test is complete. The drift test is continued until perturbation is confirmed or not. For example, the drift test may continue until all or a portion of the components identified above have been evaluated. The decision in decision block 230-R is“YES” when the drift test is complete. Otherwise, the decision in decision block 230-R is“NO.”

When the decision in decision block 230-R is“NO,” the current modet remains set at DRIFT1 and the dilution one test method 2Q0-R

terminates.

When the decision in decision block 230-R is“YES,” in block 250- R, the System Controller 190 returns the fan speed to the previous value and sets the current modet equal to ROUTINE.

The dilution one test method 200-R returns a drift test result. For example, the System Controller 190 may have an atmospheric value for a gas (e.g. , CO2) measured by a selected one of the fire defection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). The System Controller 190 may receive a first sensor reading from the selected gas sensor 128A before the fan speed is decreased in block 220-R. After the fan speed is decreased in block 220-R, the System Controller 190 may receive a second reading from the selected gas sensor 128A. The System Controller 190 may determine a first rate at which the first reading changed with respect to the atmospheric value and a second rate at which the second reading changed with respect to the first reading. The System Controller 190 may determine the selected gas sensor 128A is not exhibiting sensor drift when the second rate is different from (e.g., greater than) the first rate. Thus, the drift test result indicates that drift is not the cause of the sensor reading(s). In other words, the sensor reading(s) being reported is/are confirmed and may be used by the System Controller 190 to enter an alarm condition and/or take actions to avert a dangerous

accumulations of gas(es). On the other hand, the System Controller 190 may determine the selected gas sensor 128A is exhibiting sensor drift when the first and second rates are equal. When this occurs, the drift test result indicates that drift is likely. In other words, the sensor reading(s) is/are questionable and should not be counted upon to actuate an alarm state

Then, the dilution one test method 200-R terminates.

Figure 7S is a flow diagram of the dilution two test method 200-S, which the System Controller 190 may perform in block 235-C (see Figure 7C) of the evaluate method 200-C (see Figures 7G-7E) and block 215-M (see Figure 7M) of the drift validation process 200-M (see Figure 7M). When performing the dilution two test method 200-S, the System Controller 190 adjusts the RID control settings of one or both of the air moving devices 178 and 179 (see Figure 3) to adjust the IMR and test if concentrations are perturbed. No perturbation means drift is implicated. On the other hand, perturbations mean measurement changes are confirmed.

In first decision block 204-S, the System Controller 190

determines whether the previous moden is set to DRIFT2. When the previous modet-i is set to DRIFT2, in block 208-S, the System Controller 190 increments a drift2 iteration counter (e.g., adds one to the drift2 iteration counter). Then, the System Controller 190 advances to decision block 210-S.

When the previous moden is not set to DR1FT2, in block 208-S, the System Controller 190 initializes the drift 2 iteration counter to an

initialization value (e.g., zero). Then, the System Controller 190 advances to decision block 210-S.

In decision block 210-S, the System Controller 190 determines if the drift 2 iteration counter is equal to the initialization value. The decision in decision block 210-S is“YES” when the drift 2 iteration counter is equal to the initialization value. Otherwise, the decision in decision block 210-S is“NO.”

When the decision in decision block 210-S is“YES,” in block 220- S, the System Controller 190 saves the previous IMR and increases the IMR. The System Controller 190 also sets the current modet equal to DRIFT2. The IMR is a mass ratio of vault exhaust air to fresh air and may range from zero to infinity. By way of a non-limiting example, the System Controller 190 may double the IMR. The !MR may be adjusted by adjusting the set point of one or both of the RID controllers and air moving devices 178 and 179. Then, the System Controller 190 advances to decision block 230-S.

When the decision in decision block 210-S is“NO,” in block 240- S, the System Controller 190 performs tests to identify perturbations. The System Controller 190 may perform one or more of the following tests until statistically convincing perturbations are recognized within MT (tau = time constant for dilution of the second type). By way of a non-limiting example, the value of M may be set initially to two and the value of t may be set initially to 30 seconds.

1 . CH _J should decrease from V toward (V+Cfresh)/2;

2. Cco ₂ should decrease from W toward (W+Cfresh)/2;

3. Cco should decrease from X toward (X+Cfresh)/2;

4. Cvoc should decrease from Y toward (Y+Cfresh)/2;

5. Co ₂ should increase from Z toward (Z+ Cfresh)/2;

6. dC/dt should be negative for C02, CO, Ffe, and VOC; and

7. dC/dt should be positive for O2.

In the above tests, Ctresh is the concentration of the component in fresh air. For example, the value of Ctresh may be 400 ppm for CO2, 10 ppm for CO, 0.5 ppm for H2, 0 ppm for VOC, and 21.2% for O2. When block 24G-S is complete, the System Controller 190 advances to decision block 230-S.

In decision block 230-S, the System Controller 190 determines whether the test is complete. The drift test is continued until perturbation is confirmed or not. The decision in decision block 230-S is“YES” when the test is complete. Otherwise, the decision in decision block 230-S is“NO.”

When the decision in decision block 230-S is“NO,” the current modet remains set to DRIFT2 and the dilution two test method 200-S

terminates.

When the decision in decision block 230-S is“YES,” in block 250- S, the System Controller 190 returns the IMR to the previous value and sets the current modet equal to ROUTINE. Then, the dilution two test method 20G-S terminates.

Figure 7T is a flow diagram of the dilution one calibration method 200-T, which the System Controller 190 may perform in block 25G-P (see Figure 7P) of the calibrate method 200-P (see Figure 7P).

In first decision block 2Q4-Y, the System Controller 190

determines whether the previous modet-i is set to CALIBRATE1. When the previous moden is set to CALIBRATED in block 206-T, the System

Controller 190 increments a calibrationl iteration counter (e.g., adds one to the calibrationi iteration counter). Then, the System Controller 190 advances to decision block 210-T.

When the previous moden is not set to CALIBRATED in block 208-T, the System Controller 190 initializes the calibrationi iteration counter to an initialization value (e.g., zero). Then, the System Controller 190 advances to decision block 210-T.

In decision block 210-T, the System Controller 190 determines whether the calibrationi iteration counter is equal to the initialization value. The decision in decision block 210-T is“YES" when the calibrationi iteration counter is equal to the initialization value. Otherwise, the decision in decision block 210-T Is“NO.”

When the decision in decision block 210-T is“YES,” in block 220- T, the System Controller 190 saves the fan speed of the air moving device 132 then sets the fan speed of the air moving device 132 to full (or 100%) or its maximum setting. Then, the System Controller 190 advances to block 230-T.

When the decision in decision block 210-T is“NO," the System Controller 190 advances to block 230-T.

In block 230-T, the System Controller 190 performs an assumed fresh air calibration. In block 230-T, the System Controller 190 calibrates the fire detection sensor(s) 216 (see Figure 3) to fresh air conditions.

In decision block 240-T, the System Controller 190 determines whether the assumed fresh air calibration is complete. The decision in decision block 240-T is“YES” when the assumed fresh air calibration is complete.

Otherwise, the decision in decision block 240-T is“NO.”

When the decision in decision block 240-T is“NO," the current modes remains set to CALIBRATE1 and the dilution one calibration method 200-T terminates.

When the decision in decision block 240-T is“YES,” in block 250- T, the System Controller 190 sets the fan speed equal to Its previous value and sets the current modet equal to ROUTINE. Then, the dilution one calibration method 200-T terminates. Figure 7U is a flow diagram of the dilution two calibration method 200-U, which the System Controller 190 may perform in block 23G-P (see Figure 7P) of the calibrate method 200-P (see Figure 7P). When performing the dilution two calibration method 200-U, the System Controller 190 uses 100% fresh air to calibrate the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3).

In first decision block 204-U, the System Controller 190

determines whether the previous modet-i is set to CALIBRATE2. When the previous moden is set to CALIBRATE2, in block 206-U, the System

Controller 190 increments a calibration2 iteration counter (e.g., adds one to the caiibration2 iteration counter). Then, the System Controller 190 advances to decision block 210-U.

When the previous moden is not set to CALIBRATE2, in block 20S-U, the System Controller 190 initializes the calibration2 iteration counter to an initialization value (e.g., zero). Then, the System Controller 190 advances to decision block 210-U.

In decision block 210-U, the System Controller 190 determines whether the calibration2 iteration counter is equal to the initialization value. The decision in decision block 210-U is“YES” when the ca!ibration2 iteration counter is equal to the initialization value. Otherwise, the decision in decision block 210-U is“NO.”

When the decision in decision block 210-U is“YES,” in block 220- U, the System Controller 190 saves the IMR then reduces the IMR to zero. The IMR may be reduced by adjusting the PID control setting of one or both of the air moving devices 178 and 179. Then, the System Controller 190 advances to block 230-U.

When the decision in decision block 210-U is“NO," the System Controller 190 advances to block 230-U.

In block 230-U, the System Controller 190 performs a fresh air calibration using atmospheric values for the component gases.

In decision block 24G-U, the System Controller 190 determines whether the fresh air calibration is complete. The decision in decision block 240-U is“YES” when the fresh air calibration is complete. Otherwise, the decision in decision block 240-U is“NO.”

When the decision in decision block 240-U is“NO,” the current modet remains set to CALIBRATE2 and the dilution two calibration method 200- U terminates.

When the decision in decision block 240-U is“YES,” in block 250- U, the System Controller 190 sets the I MR equal to the previous IMR value and sets the current modet equal to ROUTINE. Then, the dilution two calibration method 200-U terminates.

Figure 7V is a flow diagram of the dilution one range method 200- V, which the System Controller 190 may perform in block 250-0 (see Figure 70) of the desaturate method 200-0 (see Figure 70). When performing the dilution one range method 2G0-V, the System Controller 190 adjusts the fan speed to compensate for sensors out of range. The fan speed may refer to the speed of the air moving device 132.

In first block 205-V, the System Controller 190 obtains a design range for each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). Thus, in block 205-V, the System Controller 190 obtains an upper sensor range and a lower sensor range for each of the fire detection sensor(s) 216 (see Figure 3).

In next block 210-V, the System Controller 190 obtains the sensor values collected over the baseline time for each of the fire detection sensor(s) 216 (see Figure s).

In block 215-V, the System Controller 190 calculates statistics for the sensor values obtained in block 210-V. The statistics may include the mean, standard deviation, a maximum value, and a minimum value.

!n block 220-V, the System Controller 190 calculates a first probability for each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3) that the sensor values collected over the baseline time are greater than the upper sensor range for the sensor.

In block 225-V, the System Controller 190 calculates a second probability for each of the fire detection sensor(s) 216 (see Figure 3) that the sensor values collected over the baseline time are less than the lower sensor range for the sensor.

In decision block 230-V, the System Controller 190 determines whether the first probability is greater than a first probability threshold. The decision in decision block 230-V is“YES” when the first probability is greater than the first probability threshold. Otherwise, the decision in decision block 230-V is“NO."

When the decision in decision block 230-V is“YES, ^” in block 235- V, the System Controller 190 calculates an increase in dilution required to target the sensor readings within the sensor range. For example, in block 235- V, the System Controller 190 may calculate an increase in the fan speed. By way of a non-limiting example, if the sensor 128A (see Figure 3) is near its upper limit, the System Controller 190 may calculate an increase in the fan speed that will keep the sensor 128A within its sensor range. The fan speed may refer to the speed of the air moving device 132. Then, the System

Controller 190 advances to block 24G-V

When the decision in decision block 230-V is“NO,” the System Controller 190 advances to decision block 245-V In decision block 24S-V, the System Controller 190 determines whether the second probability is greater than a second probability threshold. The decision in decision block 245-V is “YES” when the second probability is greater than the second probability threshold. Otherwise, the decision in decision block 245-V is“NO.”

When the decision in decision block 245-V is“YES,” in block 250- V, the System Controller 190 calculates a decrease in dilution required to target the sensor readings within the sensor range. For example, in block 250-V, the System Controller 190 may calculate a decrease in the fan speed required to move the sensor readings within the sensor range. The fan speed may refer to the fan speed of the air moving device 132. By way of a non-limiting example, if the CO sensor is always reading zero, the System Controller 190 may calculate a decrease in the fan speed that explores whether CO is present below diluted sensitivity. Then, the System Controller 190 advances to block 240-V. When the decision in decision block 245-V is“NO,” the dilution one range method 2G0-V terminates.

In block 240-V, the System Controller 190 adjusts the dilution (e.g., adjusts the fan speed of the air moving device 132). Then, the dilution one range method 2Q0-V terminates.

It is possible that a condition could exist where one of the fire detection sensor(s) 216 (see Figure 3) needs a lower fan speed and another one of the fire detection sensor(s) 216 needs a higher fan speed. When this occurs, the dilution one range method 200-V may sequentially increase and decrease the fan speed to accommodate the needs of both sensors or attempt to strike a balance. Additionally, some of the fire detection sensor(s) 216 are more important than others, which may be partially reflected in their weights W(N). The weights may be determined in block 245-G (see Figure 7Q) of the relate method 2G0-Q (see Figure 7Q).

Figure 7W is a flow diagram of the dilution two range method 200- W, which the System Controller 190 may perform in block 230-0 (see Figure 70) of the desaturate method 200-0 (see Figure 70) When performing the dilution two range method 2QG-W, the System Controller 190 adjusts the IMR to compensate for sensors out of range. The IMR may be adjusted by adjusting the set points of the RID controllers of one or both of the air moving devices 178 and 179.

In first block 205-W, the System Controller 190 obtains the design range for each of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). Thus, in block 205-W, the System Controller 190 obtains the upper sensor range and the lower sensor range for each of the fire detection sensor(s) 216 (see Figure 3).

In block 210~W, the System Controller 190 obtains the sensor values collected over the baseline time for each of the fire detection sensor(s) 216 (see Figure 3).

In block 215-W, the System Controller 190 calculates statistics for the sensor values obtained in block 210-W. The statistics may include the mean, standard deviation, a maximum value, and a minimum value. In block 220-W, the System Controller 190 calculates a third probability for each of the fire detection sensor(s) 216 (see Figure 3) that the sensor values collected over the baseline time are greater than the upper sensor range for the sensor.

In block 225-W, the System Controller 190 calculates a fourth probability for each of the fire detection sensor(s) 216 (see Figure 3) that the sensor values collected over the baseline time are less than the lower sensor range for the sensor.

In decision block 230-W, the System Controller 190 determines whether the third probability is greater than a third probability threshold. The decision in decision block 230-W is“YES” when the third probability is greater than the third probability threshold. Otherwise, the decision in decision block 230-W is“NO.”

When the decision in decision block 230-W is“YES,” in block 235- W, the System Controller 190 calculates an increase in dilution required to target the sensor readings within the sensor range. For example, in block 235-

V, the System Controller 190 may calculate an increase in the IMR. The IMR may be adjusted by varying the RID set points on one or both of the air moving devices 178 and 179. By way of a non-limiting example, if the sensor 128A (see Figure 3) is near its upper limit, the System Controller 190 may calculate an increase in the IMR that will keep the sensor 128A within its sensor range. Then, the System Controller 190 advances to block 24G-W

When the decision in decision block 230-W is“NO,” the System Controller 190 advances to decision block 245-W. In decision block 245-W, the System Controller 190 determines whether the fourth probability is greater than a fourth probability threshold. The decision in decision block 245-W Is“YES” when the fourth probability is greater than the fourth probability threshold.

Otherwise, the decision in decision block 245-W Is“NO.”

When the decision in decision block 245-W is“YES,” in block 250-

W, the System Controller 190 calculates a decrease in dilution required to remain the sensor readings within the sensor range. For example, in block 250-W, the System Controller 190 may calculate a decrease in the IMR required to target the sensor readings within the sensor range. The IMR is adjusted by varying the set points of the PID controllers of one or both of the air moving devices 178 and 179 By way of a non-limiting example, if the CO sensor is always reading zero, the System Controller 190 may calculate a decrease in the IMR that explores whether CO is present below diluted sensitivity. Then, the System Controller 190 advances to block 240-W

When the decision in decision block 245-W is“NO,” the dilution two range method 2GG-W terminates.

In block 240-W, the System Controller 190 adjusts the dilution (e.g., adjusts the IMR). The IMR may be adjusted by adjusting the PID controller set points of one or both of the air moving devices 178 and 179.

Then, the dilution two range method 2G0-W terminates.

It is possible that a condition could exist where one of the fire detection sensor(s) 216 (see Figure 3) needs a lower IMR and another one of the fire detection sensor(s) 216 needs a higher IMR. When this occurs, the dilution two range method 2QG-W may sequentially increase and decrease the IMR to accommodate the needs of both sensors or attempt to strike a balance. Additionally, some of the fire detection sensor(s) 216 (see Figure 3) are more important than others, which may be partially reflected in their weights W(N). The weights may be determined in block 245-G (see Figure 7Q) of the relate method 200-G (see Figure 7Q)

Figures 8A and 8B illustrate the exemplary sensor readings (identified by the squares 206) obtained from one of the fire detection sensor(s) 216 (e.g., the sensor 128A illustrated in Figure 3). In the example presented in Figures 8A and 8B, the sensor is a carbon dioxide concentration sensor configured to measure part-per-miliion (“ppm") of carbon dioxide in the internal atmosphere 124 (see Figure 1 ). In both Figures 8A and 8B, the x~axis is time and the y-axis is ppm of carbon dioxide.

Figure 8A illustrates sensor readings received from the carbon dioxide concentration sensor over a 63-day period from May 10, 2018, to about July 12, 2018. In this example, the underground vault 112 is located in the northeast coast of North America. A triple line NNN shows the approximate sensor drift over the 63-day period starts around 700 ppm on May 10 and ends at about 1 ,400 ppm on July 9. Large positive variations (e.g., readings V1 and V2) indicate burning events within or adjacent to the manhole vault 112.

The triple line NNN is a time weighted moving average of non- event data. Non-event data are data collected when the alarm trigger state was “AS0” Time weighting assigns lessor weights to older data points. Time weighting factors are determined statistically. For computational efficiency, those data points collected when the alarm trigger state was“AS0” with time weightings below a threshold value (e.g., determined based on sensor experience) are dropped from the moving average.

Figure 8B is a subset of the data of Figure 8A over a single 24 hour time period on May 24, 2018. The y-axis has been enlarged and shows only a range of 400 ppm to 800 ppm. As mentioned above, the triple line NNN shows approximate sensor drift. Over the 24 hour period of Figure 8B, the sensor drift is insignificant and the triple line NNN has a slope that is essentially zero. Thus, Figure 8B illustrates a time period during which variations in the data were primarily caused by something other than sensor drift (referred to as “non-drift variations”). Non-limiting examples of non-drift variations include stochastic variations within the sensor mechanism, stochastic variations within the hardware systems where analog signals are converted to digital signals, and natural and man-made perturbations to the analyte or property being measured. Man-made perturbations may include, for example, a running car parked over a manhole cover, which will perturb the level of CO2 inside the manhole upward (or increase the level of CO2) until the car drives away.

During this same time period, the aforementioned non-drift variations yield sensor readings between about 600 ppm and 725 ppm. The upper and lower confidence bounds UB and LB are established by a maximum likelihood estimate or similar statistical technique and provide a defined level of confidence that a value outside those bounds is quite unlikely (e.g., less than 5% or perhaps less than 1 %) to be caused by drift or non-drift variations, but rather is very likely (e.g. greater than 95% or perhaps greater than 99%) a perturbation worthy of corroboration.

For example, the upper and lower confidence bounds UB and LB may be determined by adding and subtracting a noise threshold from an average sensor reading. The average sensor reading and a standard deviation may be determined for the sensor from historicai sensor readings. Additionally, the upper and lower confidence bounds UB and LB may be determined from percentile values and/or upper-tile averages on distributions that are highly skewed. New sensor readings falling between the upper and lower confidence bounds UB and LB are identified as noise. The historicai sensor readings include a number of past samples collected over a past time period. The past time period and number of past samples depends on the characteristics of the sensor and the environment in which it operates. Typically sensor

measurements are recorded every 15 minutes and, thus, about 96

measurements are recorded every day. The past time period may include one day, two days, or more. The noise threshold may be determined by the System Controller 190 using maximum-likelihood statistics or similar means to achieve a user-defined probability threshold. By way of non-limiting examples, 90%, 95%, and 99% may be used as user-defined probability thresholds. Thus, the noise threshold may include all values that are statistically within a user selected confidence interval (e.g., 90%, 95%, and 99%) of the average sensor reading. Older measurements in the historicai sensor readings may be weighted less than or equal to more contemporary measurements when the average sensor reading is calculated. Unequal weighting is most appropriate where the sensor drift is mathematically significant over the length of time chosen to calculate the average and standard deviation.

Using the sample data of Figures 8A and 8B, if is clear that over any single day the drift is very small but, over the 63-day period, the impact of the drift is about a factor of two. Thus, a 24-hour period is about right to determine a baseline, the average sensor reading, and the standard deviation for this sensor. Longer time periods can improve the statistical veracity of the estimations. Therefore, an appropriate time period to calculate the baseline, the average sensor reading, and the standard deviation for this sensor in this environment may be about 24 hours to 48 hours. Longer times are possible, but including more historical data provides diminishing returns of statistical veracity and suffers from additional computational demands. While the triple line NNN, the upper confidence bound UB, and the lower confidence bound LB shown in Figure 8B appear to be horizontal because of the scale choice, they in fact each have a small positive slope, AC/At. For example, the average slope from Figure 8A over the 83 day time period is the difference between about 1200 ppm (on July 11 ^lh ) and about 700 ppm (on May 10 ^th ) divided by 63 days, which is about 7.9 ppm/day. Inspection of Figure 8A for the 24 hour time period illustrated in Figure 8B reveals that the slope on May 24 ^ih is less than 7.9 ppm/day. The drift slope can be used to refine an anticipated data point, but such a refinement is generally unnecessary as the noise exemplified in Figure 8B is generally much greater than the drift.

In the 24 hour period illustrated in Figure 8B, the span of the noise is about 125 ppm or more than an order of magnitude greater than the drift.

COMPONENT MASS BALANCE

As mentioned above, a component mass balance may be used in block 206-K (see Figure 7K) of the calculate method 200-K (see Figure 7K) to determine a FGA rate and/or in block 242-K (see Figure 7K) of the calculate method 200-K (see Figure 7K) to determine a burn rate.

For brevity in the discussion that follows, all input values and estimates are described as single deterministic values. Of course, all measurements are estimates of reality and ail estimates include error.

Therefore, probabilistic inputs may be used for each input described in deterministic terms below and a Monte Carlo simulation of those inputs may be used to provide probabilistic outputs. This probabilistic approach allows the end user of the information to judge the veracity of the results. For example, both a deterministic percentage lower explosive limit (“%LEL”) and a

probabilistic %LEL may be determined. %LEL is a fraction of flammable components relative to that fraction which would support an explosion. If the deterministic %LEL is determined to be 75%, the user might fake comfort that an explosion is unlikely. However, if the same result were reported

probabilistically as 75% MLE (maximum likelihood estimate) with 95% confidence levels at 71 % (lower) and 103% (upper), the user is more likely to have a higher level of alarm and make a better decision. Referring to Figure 1 , even if the absolute output values of the fire detection sensor(s) 216 (see Figure 3) are reliable, the dynamics of these systems are indeterminate. With passive ventilation, the flow of gases in and out of the underground vault 112 is practically unknowable. Only with active ventilation, where the exhaust flow rate can be measured or estimated and the concentrations of the analytes in the exhaust can be measured or estimated, is it possible to perform a robust component mass and energy balance on the vault environment. The mass balance allows an assessment of the size of a fire or other source of dangerous gases. For example, a smoldering cigarette would be of little concern, but a fire that is consuming 100 grams of polymer per minute would constitute a substantial event. The former requires no action while the later demands immediate action to protect the public.

The System Controller 190 may use component mass balance to determine one or more of the following:

1. relevant alarm condition(s);

2. the alarm state level for an associated alarm condition;

3. the lower explosive limit (“LEL”) of the mixture of flammable gases in air;

4. a corrected lower explosive limit (“CLEL”) of the mixture of flammable gases that accounts for an abundance of non- flammable gases introduced by oxidative decomposition;

5. anticipated dilution of O2 and N2;

6. an amount of energy being dissipated by active ventilation;

7. a quantity of energy from a manhole event (e.g., a fire); and

8. an amount of water being transported from the vault 112 by evaporation.

Regarding determining relevant alarm condition(s), manhole events may include oxidative decomposition, pyrolysis, and/or plasmatization. The component mass balance allows the event to be labeled. The benefit of this knowledge may be critical to respond properly to the manhole event. For example, oxidative decomposition is exothermic and potentially self-sustaining, meaning it requires different intervention than pyrolysis and plasmatization, which are endothermic and can be halted by shutting the power off to burning equipment.

Regarding determining the alarm state level for an associated alarm condition, the System Controller 190 may use component mass balance to determine the size of a combustion event. Large events have greater urgency than smaller events and very small events would represent nuisance alarms (or an alarm where no action is required.)

Figure 18 illustrates how various burning (oxidative decomposition and pyrolysis) cases can create flammable atmospheres in vaults. The logarithmic x-axis is burn rate expressed in grams per minute. The y-axis is the gas mixture concentration expressed as a percentage of the CLEL (%CLEL) Ignition and explosion are not possible until the %CLEL is greater than 100%. The LEL (by definition in air) of a mixture of flammable gases is calculated using Equation 9 (below), which is Le Chatelier’s formula:

In Equation 9, variables ci , C2, C3, ... c _n are mole fractions of n component gases in the mixture having lower explosive limits of LELi, LEL.2, LELa, . .

LEU respectively. The sum of the mole fractions, ci , 02, C3, ... c _n , is unity.

The mixture LEL (i.e., LEL™) is corrected for dilution by inert gases above the levels found in the atmosphere by Equation 10 (below), which is Kondo ^' s equation (S. Kondo, K. Takizawa, A. Takahashi, K. Tokuhashi, “Extended Le Chaie!iers formula for carbon dioxide dilution effect on

flammability lim its,” Journal of Hazardous Materials A138 (2006) 1 -8):

Cmix/CLEL = Cmix/LELmix + p*(1 -Cmix) (10)

In Equation 10, variable Cmix is the mole fraction of the flammable gases in the fuel-inert gas mixture, variable CLEL is the mixture LEL corrected for the inert gases (e.g. CO2, H2O) in excess of normal atmospheric inert gases, variable LELmix is the LEL of the mixture in air, and variable p is an experimentally determined parameter with a typical value of about -0.01. In Figure 18, the dependent variable is plotted for each burn rate, each fire type, and a specified exhaust rate. A dotted line 950 (corresponding to H2 max pyrol; 0.1 m ³ /s DHί=28 kJ/m) and a dashed line 952 (corresponding to hte max pyrol; 0.2 m ³ /s DHί=28 kJ/m) demonstrate a hypothetical worst-case scenario where 100% of the hydrogen in the polymer is pyroiyzed to H2. In the first case shown by the dotted line 950, active ventilation is exhausting 0.1 rrr/sec and, in the second case shown by the dashed line 952, the exhaust is doubled. This hypothetical worst-case scenario is not possible because such pyrolysis cannot occur until temperatures are about 500°C Such temperatures are not possible (because emergency overload design temperatures for electrical equipment are less than 200°C) without an oxidative combustion process, because pyrolysis is endothermic. For each case in Figure 18, a legend 960 includes the approximate net heat of formation (DHί) for the burn. Positive values are endothermic and cannot sustain; negative values are exothermic and are potentially sustainable in the duct-vault environment. The aforementioned dotted and dashed lines 950 and 952 are entirely hypothetical. Four solid compound lines 971 -974 illustrate where combustion and pyrolysis are mixed from 20% to 90% oxidation. The solid compound lines 971-974 illustrate 20% oxidation, 50% oxidation, 80% oxidation, and 90% oxidation respectively. Each of the solid compound lines 971 -974 depicts an example with negative (favorable) net heat of formation and represents a realistic burn scenario.

To distinguish nuisance fires from fires of consequence, consider some examples. A smoking cigarette weights about 1 gram and is consumed in about 5 minutes. Its burn rate is thus about 0.2 g/min. A cigarette in a vault is obviously a nuisance. A typical candle burns about 0.1 g/min and hence 100 candles would yield 10 g/min. Thus, even 100 candies do not have a significant burn rate. On the other hand, a typical auto traveling at 60 mph consumes about 119 g/min. This value is illustrated with a vertical line 976 labeled“119 Auto @60” in Figure 18. The example automobile is consuming considerable fuel and, therefore, may be considered a fire of consequence.

A fire having a burn rate of 100 g/min or greater is a pretty serious fire. On the other hand, burn rates that are less than 1 g/min can be largely ignored unless they persist for long periods or grow with time. The character of a fire has a large impact on its severity. For example, fires with high oxidative character are much less likely to lead to an explosion. Vault owners will want to deal with large fires in any case. One of ordinary skill in the art would recognize that the size of the fire (or its pyrolysis-burn rate) and the oxidative character of the fire impact both the %LEL and likelihood of an explosion.

Regarding an amount of energy being dissipated by active ventilation vault, owners are faced with equipment that ages at least partially based upon the temperature at which the equipment operates. As a general rule of thumb, each 10°C of temperature doubles the rate of oxidation or aging. Understanding how much energy is dissipated by active ventilation allows the vault owner to adjust their expectations for scheduled maintenance of equipment.

Regarding determining anticipated dilution of O2 and M2, when it is desirable to dilute potentially explosive gases within the underground vault 112, dilution of the first type may be used to exhaust the internal atmosphere 124 up to the maximum exhaust rate. Atmospherically rich components O2 and IM2 decrease in concentration by dilution when there is an increase in combustion by-products or an increase in flammable gases by dilution. The magnitude of the dilution can be estimated when the exhaust rate is known. Performing a component mass balance (discussed below) yields the anticipated dilution of O2 and N2.

Regarding determining an amount of water being transported from the vault 112 by evaporation, there are reliability and convenience benefits in keeping manholes dry. In conjunction with water level measurement, the effectiveness of water control features can be evaluated.

Figure 19 illustrates typical evolution of a manhole event from initiation to extinguishment. Events in a manhole generally follow a somewhat predictable progression with time. As a non-limiting example of such a progression and using a secondary network as an example, a manhole event most likely starts as surface tracking on an old/damaged cable. During a first phase 982, the predominate mechanism is plasmatization, which creates compounds like NO, NO2, and O3. Of course, the temperature of plasma is 30,000°F so some pyrolysis and oxidation also occur. Piasmatization and pyrolysis are both endothermic so they cannot grow or maintain themselves without oxidation. At this stage of the fire, oxygen is plentiful in the duct.

Oxidation creates carbon dioxide and water, is exothermic, and is a prerequisite for a growing fire. A second phase 984 begins when oxidative decomposition becomes self-sustaining. This second phase continues as the fire grows until the fresh supply of oxygen is exhausted. A third phase 986 is represented by a plateau 988. The plateau 988 represents the maximum burn rate based upon the amount of oxygen available. A fourth phase 990 occurs when the vault owner shuts power off to the circuit. The piasmatization has been marked by stochastic behavior as electrical paths are destroyed and reinitiated during the event. Once the power is turned off, piasmatization terminates immediately. With less energy supplied to the event, a small decrease in the plateau 988 may occur. A fifth phase 992 of the event will not occur until an extinguishing medium is introduced or the polymer is entirely consumed. During this fifth phase 992 the fire subsides. Knowing where a particular manhole event is along this event development continuum allows the circuit owner to take appropriate action - urgent or not so urgent.

Figure 9 is a flow diagram of a method 300 of conducting a component mass balance that may be performed by the System Controller 190. Component mass balance may be used to calculate flows into and out of the underground vault 112. Active ventilation allows the underground vault 112 to be considered a continuous stirred tank (“GST”). The exhaust flow FE equals the fresh air flow FFA of gases and particulates from the external atmosphere 122, the connection(s) flow Fc of gases and particulates into the internal atmosphere 124 from another source (e.g., one or more connections 1 1 8A- 118J connected to the underground vault 112), the evaporation flow Fv of evaporating liquids, and a change in water depth (referred to as ADepthwater). Thus, this relationship may be described using Equation 11 , which is a total gaseous mass balance equation:

FE - FFA + Fc + Fv + ADepthwater (1 1 )

fb Each value in the total gaseous mass balance equation is expressed in gaseous mass (or equivalent for water depth) per unit time. The System Controller 190 may estimate the change in water depth (referred to as ADepthwater) with time using data received from the water level sensor 214.

Influx of water is positive flow and outflow is negative flow. The System

Controller 190 may estimate a volume of air displaced by the water influx. The volume of displaced air is approximately equal to a product of the water depth and the cross-sectional area of the vault 112, minus the volume of any submerged equipment. Failure to calculate ADepthwater would create an error in the overall mass balance. The change in water depth is often negligible and may be ignored in many cases. However, in some vaults near sea coasts, tidal conditions create twice daily flooding and reverse flooding of vaults that should not be ignored.

The connection(s) flow Fc includes net gas flows from a fire regardless of where the fire is located. There is much more cable located within the connections 1 18A-1 18J connected to the vaults 112-116 than there is cable in the vaults, and hence the connection(s) flow Fc is most likely from one of the connections. However, the fire may also originate in one of the vaults 112-116. For the purpose of this component mass balance, where the fire is located (e.g., in one of the connections 1 18A-1 18J or vaults 1 12-1 16) is a distinction without a difference.

In first block 310, the System Controller 190 obtains vault parameters. By way of a non-limiting example, the System Controller 190 may perform a method 350 (see Figure 10) to obtain the vault parameters. In this example, the vault parameters include a dry vault volume and an atmospheric pressure.

In block 320, the System Controller 190 obtains exhaust flow parameters for the exhaust flow FE. By way of a non-limiting example, the System Controller 190 may perform a method 400 (see Figure 11 ) to obtain the exhaust flow parameters. In this example, the exhaust flow parameters include the following:

1. an exhaust flow rate,

2. an exhaust temperature value TE, 3. a vault turnover (e.g., in seconds), and

4. exhaust component parameters.

The exhaust component parameters may include one or more of the following values for each component of the exhaust flow FE:

1. Concentration of the exhaust component (see second column of Table B); and

2. Mass flow rate (g/s) of the exhaust component (see rightmost column of Table B).

For example, if the exhaust flow rate is about 0.047 m ³ /s, the exhaust temperature value TE is about 25°C (77°F), and turnover is about 428 seconds, Table B lists exemplary exhaust component parameters.

!n block 330, the System Controller 190 obtains fresh air flow parameters for the fresh air flow FFA. By way of a non-limiting example, the System Controller 190 may perform a method 500 (see Figure 12) to obtain the fresh air flow parameters. In this example, the fresh air flow parameters include the following:

1. a fresh air flow rate, 2. a fresh air temperature value TFA, and

3. fresh air component parameters.

The fresh air component parameters may include one or more of the following values for each component of the fresh air flow FFA:

1. Concentration of the fresh air component (see second column of Table C); and

2. Mass flow rate (g/s) of the fresh air component (see rightmost column of Table C).

For example, if the fresh air flow rate is about 0.0463981 m ³ /s and the fresh air temperature value is about 25°C (77°F), Table C lists exemplary fresh air component parameters.

!n block 340, the System Controller 190 obtains connection(s) flow parameters for the connection(s) flow Fc. By way of a non-limiting example, the System Controller 190 may perform a method 600 (see Figure 13) to obtain the connection(s) flow parameters. In this example, the connection(s) flow parameters include the following:

1. a connection(s) flow rate, 2. a connection(s) temperature value Tc, and

3. connection(s) component parameters.

The connection(s) component parameters may include one or more of the following values for each component of the connection(s) flow Fc:

1. Concentration of the connection(s) component (see third

column of Table D); and

2. Mass flow rate (g/s) of the connection(s) component (see

fourth column of Table D).

For example, if the connection(s) flow rate is about 0.000228 m ³ /s and the connection(s) temperature value is about 25°C (77°F), Table D lists exemplary connection(s) component parameters.

Determining the connection(s) flow parameters requires the fresh air flow parameters and vice versa. Thus, as will be described below, portions of blocks 330 and 340 may be performed together. For example, the connection(s) and fresh air flow parameters may be determined iteratively using a method well known in the art, such as direct substitution, IMewton-Raphson, and the like. Using such a method, a mass balance error value may be driven to zero by adjusting the fresh air flow rate. The mass balance error value may be equal to a sum of the mass flow rate of the exhaust components (e.g., last row in rightmost column of Table B) minus a sum of the mass flow rate of the fresh air components (e.g., last row in rightmost column of Table C) and a sum of the mass flow rates of the connection(s) components (e.g., last row in fourth column of Table D).

In block 342, the System Controller 190 performs an energy balance and calculates enthalpies (a first exhaust value“he,” a second fresh air value“hf,” and a third conneclion(s) value“he”) and energy exhausted“Ah” for each of the components shown in the leftmost columns of Tables B~D. By way of a non-limiting example, the energy balance may be implemented by a method 700 (see Figure 14).

In block 344, the System Controller 190 calculates a rate of net wafer removal“Aw” by the evaporation Fv. By way of a non-limiting example, the rate of net water removal“Aw” may be calculated using a method 800 (see Figure 15).

In block 348, the System Controller 190 provides (e.g., displays) a value of interest to the user. For example, the conneclion(s) flow Fc may include nitrogen dioxide as a connection(s) component. The connection(s) component parameters for the nitrogen dioxide may be provided as a metric of the size of a combustion event. Thus, these parameters may be used to determine alarm state level for an associated alarm condition. For example, the System Controller 190 may provide the burn rate and/or the FGA.

By way of another example, the connection(s) components of the connection(s) flow Fc may include soot. The connection(s) component parameters for the soot may be provided as a metric of an amount of energy being dissipated by active ventilation. For example, the energy exhausted“Ah" calculated for soot using the energy balance of the method 700 (see Figure 14) may be used as a metric of the amount of energy dissipated by active ventilation.

By way of another example, the System Controller 190 may provide an estimate of a net heat of reaction of at least one of plasmatization, pyrolysis, and oxidative decomposition. Before a fire begins, referring to Figure 1 , there is an energy balance for non-fire operation where net energy input is driven primarily by impedance losses of the cables 160 and the equipment 119 This base energy EB is dispersed in the exhaust flow FE and is approximately a difference of exhaust and fresh air products. The exhaust product is a temperature TE of the exhaust flow FE multiplied by a mass MASSE of the exhaust flow FE and a heat capacity CE of the exhaust flow FE. The fresh air product is a temperature TFA of the fresh air flow FFA multiplied by a mass MASSFA of the fresh air flow FFA and a heat capacity CFA of the fresh air flow FFA. Thus, the base energy EB may be calculated using the following Equation 12:

EB = TE*MASSE*CE - TFA-MASSFA-CFA (12)

Because of the nature of an electrical grid’s distributed loads, the base energy EB changes slowly with time and in predictable ways. For example, the fresh air temperature TFA and the time of day can be used to predict the likely trajectory of the base energy EB of networks dominated by air conditioning loads. The System Controller 190 utilizes previous periods to model the anticipated trajectory and calculate an anticipated base energy EB' . When a fire event begins and is recognized by the System Controller 190 as described elsewhere in this application (e.g., plasmatization is observed, pyrolysis is observed, and/or combustion by-products are recognized as being above their threshold levels), the System Controller 190 subtracts the anticipated base energy EB' from the actual base energy EB (e.g., calculated using the Equation 12 above) to obtain the estimate of the net heat of reaction (or the quantity of energy from the manhole event). When the net heat of reaction is negative, it is an estimate of a net energy release (e.g., a net exothermic reaction). In this way, an extent of combustion and a ratio of oxidation to pyrolysis can be estimated independently of the component mass balance. Since both this energy balance and the component mass balance incur some measurement errors, both are estimates and the System Controller 190 may use the two estimates to provide a blended estimate that may be superior to either estimate alone. Further, while this non-limiting exemplary description is deterministic, the System Controller 190 may alternatively perform a Monte Carlo analysis on input measurements and assumptions such that a probabilistic output can be reported by the System Controller 190.

By way of another example, in block 348, the System Controller 190 may provide the rate of net water removal“Aw” by the evaporation Fv calculated in block 344.

By way of another example, the System Controller 190 may provide one or more of the enthalpies (e.g., the first exhaust value“he”, the second fresh air value“hf”, and the third connection(s) value“he”) and/or the energy exhausted“Ah” for at least one of the component of the flows FE, FFA, and Fc.

By way of another example, the System Controller 190 may provide a percentage lower explosive limit of one or more flammable gases present in block 348. The System Controller 190 may alter (e.g., increase or decrease) the turnover rate of the atmospheric turnover in the vault 112 based at least in part on the percentage lower explosive limit of the flammable gas(es) present.

Then, the method 300 terminates.

Figure 10 is a flow diagram of the method 350 of determining vault parameters performed by the System Controller 190. In first block 360, the System Controller 190 obtains a dry vault volume of the vault 112. For example, the System Controller 190 may estimate the dry vault volume by multiplying a vault length by a vault width and a vault height. The System Controller 190 may add a chimney volume, if present, to the dry vault volume.

If the chimney is generally cylindrical in shape and has a height“h” and a radius “r," the chimney volume may be calculated as the volume of a cylinder, which may be calculated with the formula h * ur ² The System Controller 190 may subtract an equipment volume of the equipment 119 (e.g., cables, transformers, components, etc.), if present, from the dry vault volume. If water is in the vault 112, the System Controller 190 may subtract a volume of wafer from the dry vault volume.

In block 370, the System Controller 190 obtains atmospheric pressure Patm. For example, the System Controller 190 may assume isobaric conditions and use an atmospheric pressure obtained from weather data, an atmospheric pressure obtained from one or more of the sensor(s) 128, or use 14.696 pounds per square inch, absolute (“psia”) as the atmospheric pressure.

In block 380, the System Controller 190 obtains parameter values to use when determining a water vapor saturation pressure value with sufficient accuracy between 0°C and 373°C using a method described by W. Wagner and A. PruB,“The IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use,” Journal of Physical and Chemical Reference Data, June 2002 , Volume 31 , Issue 2, pp. 387535 (copy available at

https://vvww.vaisaia.com/sites/default/files/documents/Hu midity Conversion Po rmulas B21 Q973EN-F.pdf).

The parameters values obtained in block 380 may include values for parameters“A,”“n,” and“Tn.” The values of these parameters vary depending upon temperature. The parameter“A” may equal a first constant (e.g., 6.089613) if the temperature is less than 0°C. The parameter“A” may equal a second constant (e.g., 6.116441 ) if the temperature is greater than or equal to 0°C and less than 50°C. Otherwise, the parameter“A” may equal a third constant (e.g., 6.004918). Similarly, the parameter“n” may equal a first constant (e.g., 9.7787073) if the temperature is less than G°C. The parameter “n” may equal a second constant (e.g., 7.591386) if the temperature is greater than or equal to 0°C and less than 50°C. Otherwise, the parameter“n” may equal a third constant (e.g., 7.337936). Additionally, the parameter“Tn” may equal a first constant (e.g., 273.1466) if the temperature is less than 0°C. The parameter“Tn” may equal a second constant (e.g., 240.7263) if the temperature is greater than or equal to 0°C and less than 50°C. Otherwise, the parameter “Tn” may equal a third constant (e.g., 229.3975). These values are summarized in Table E below.

Table E

In block 390, the System Controller 190 obtains molecular weights for use in calculations. For example, the System Controller 190 may obtain a molecular weight MWFS for a potential fuel source (e.g., one or more polymers used to construct cable insulation) that may burn in the connection(s) 118A- 118J By way of additional non-limiting examples, the System Controller 190 may obtain a molecular weight for each of components shown in the leftmost columns of Tables B-D

Then, the method 350 terminates.

Figure 11 is a flow diagram of the method 400 of determining flow parameters for the exhaust flow FE that may be performed by the System Controller 190.

In first block 410, the System Controller 190 obtains an exhaust temperature value TE for the exhaust flow FE from one or more of the fire detection sensor(s) 218 (see Figure 3).

In block 415, the System Controller 190 obtains a volumetric exhaust flow rate for the exhaust flow FE. For example, the System

Controller 190 may obtain the volumetric exhaust flow rate from the manhole event suppression system 140 For example, the System Controller 190 may empirically correlate current drawn by the air moving device 132 to a volumetric exhaust flow rate. If the air moving device 132 is implemented as a rotary fan, the System Controller 190 may empirically correlate revolution-per-minute (“RPM”) of the fan and/or current drawn by the fan to the volumetric exhaust flow rate. By way other non-limiting examples, the System Controller 190 may obtain the volumetric exhaust flow rate from one or more of the fire detection sensor(s) 216 (see Figure 3) configured to measure volumetric flow and/or air velocity in the first section P1 of the ventilation pipe 148.

In block 420, the System Controller 190 calculates a turnover rate. The turnover rate is the vault volume divided by the volumetric exhaust flow rate

In block 425, the System Controller 190 obtains a concentration measurement for each of a plurality of exhaust components that may be present in the exhaust flow FE. Exemplary exhaust components are listed in the left-most column of Table B (above) and exemplary exhaust concentration measurements are provided in the second column labeled“Volume” of Table B.

The System Controller 190 may obtain concentrations of oxygen, carbon dioxide, carbon monoxide, and the volatile organic compounds in the exhaust flow FE from one or more of the fire detection sensor(s) 216 (see Figure 3). The System Controller 190 may obtain concentrations of hydrogen sulfide and/or sulfur dioxide from one or more of the fire detection sensor(s) 216 (see Figure 3) or assume each has a concentration of zero. The System Controller 190 may obtain concentrations of nitric oxide, nitrogen dioxide, and/or ozone from one or more of the fire detection sensor(s) 216 (see Figure 3), assume each has a concentration of zero, or assume each has a

concentration equal to an amount of pollution provided by a third party.

Optionally, the concentrations of nitric oxide and/or nitrogen dioxide may be obtained by measuring a concentration of NOx.

The System Controller 190 may obtain the concentration of hydrogen in the exhaust flow FE from the fire detection sensor(s) 216 or estimate the concentration of hydrogen from the concentrations of carbon dioxide (CO2) and carbon monoxide (CO) according to Equation 13 below:

H2 = a · CO + b · CO2 (13)

In Equation 13, the concentrations of carbon dioxide (CO2) and carbon monoxide (CO) may be equal to their respective amounts present in the fresh air. The variable“a" may equal 1 77 and the variable“b" may equal 0, which were determined from experimental data.

The System Controller 190 may obtain the concentration of nitrogen in the exhaust flow FE by subtracting the concentrations of all other exhaust components, expressed as a percentage, from 100%. The System Controller 190 may obtain the concentration of particulates and aerosols in the exhaust flow FE from one or more of the fire detection sensor(s) 216 (see Figure 3) and apportion between soot and ash (e.g., based upon the fire type). If there is no fire, these values can be ignored. The System Controller 190 may obtain a relative humidity from one or more of the sensor(s) 128 and use it to determine a concentration of water vapor in the exhaust flow FE. TO determine the concentration of water vapor, the System Controller 190 may calculate a water vapor saturation pressure“PWSE” for the exhaust flow FE using Equation 14 below:

PWSE = A*10« ^m ‘ ^TE ' ⁽ TE ⁺ Tn)) ( ₁ 4)

In Equation 14 above, the values of the parameters“A,”“m,” and “T _n ” are taken from Table E for the exhaust temperature value TE. Then, the System Controller 190 may calculate a water vapor pressure PWE for the exhaust flow FE using Equation 15 below:

PWE = PWSE * RH * 1 00 (1 5)

Next, the System Controller 190 may calculate a water density WDE (e.g., in g/m ³ ) using Equation 16 below:

WDE = 2.16679* PWE /(TE + 273.15) (16)

Finally, the System Controller 190 may calculate the water vapor concentration (e.g., ppm) for the exhaust flow FE using Equation 17 below.

WE = 1 ,000,000 ^* (WDE/MWW) ^* 0.00008205745*(TE +273.15)/Patm (17)

In Equation 17 above, a variable MWW is the molecular weight of water and the variable“Patm” is atmospheric pressure (measured in

atmospheres).

In optional block 430, if the exhaust components are not expressed in mass per unit volume (e.g., g/m ³ ), the System Controller 190 converts them. For example, if the concentrations of the exhaust components are expressed as volume-percent at absolute pressure, the System Controller 190 may convert them to moles per unit volume (see fourth column of Table B) using the exhaust temperature value TE and the ideal gas law.

Then, the System Controller 190 may use the molecular weight of each component to convert the moles per unit volume to mass per unit volume (see fifth column of Table B). By way of a non-limiting example, the mass may be expressed as grams (“g”) and the unit volume may be a cubic meter (m ³ ) shown in the fifth column of Table B).

In block 435, the System Controller 190 totals the exhaust components (e.g., expressed in g/m ³ ) to obtain an exhaust total (see last row of fifth column of Table B).

In block 438, the System Controller 190 may utilize the component volume and molar flow rates to calculate mixture lower explosive limits (i.e., LELmix) and mixture corrected lower explosive limits (i.e., CLELmix).

In optional block 440, the System Controller 190 may divide the mass per unit volume of each of the exhaust components by the exhaust total to obtain exhaust percentages.

In block 445, the System Controller 190 multiplies the mass per unit volume of each of the exhaust components (e.g., expressed in g/m ³ ) by the exhaust flow rate (expressed in m ³ /s) to obtain exhaust component mass flow rates (e.g , g/s) shown in the rightmost column of Table B

In block 450, the System Controller 190 totals the exhaust component mass flow rates to obtain a total exhaust component flow rate (e.g., g/s) shown in last row of rightmost column of Table B.

Then, the method 400 terminates.

Figure 12 is a flow diagram of the method 500 of determining flow parameters for the fresh air flow FFA that may be performed by the System Controller 190.

In first block 510, the System Controller 190 obtains a fresh air temperature value TFA from one or more of the fire detection sensor(s) 216 (see Figure 3) and/or real-time weather data.

In block 515, the System Controller 190 obtains an estimated fresh air flow rate for the fresh air flow FFA. AS mentioned above, the System Controller 190 may adjust the fresh air flow rate until the mass balance error value is zero.

In block 525, the System Controller 190 obtains a concentration measurement for each of a plurality of fresh air components that may be present in the fresh air flow FFA Exemplary fresh air components are listed in the left-most column of Table C (above) and exemplary fresh air concentration measurements are provided in the second column labeled“Volume” of Table B.

The System Controller 190 may obtain the concentration of oxygen (O2) in the fresh air flow FFA from one or more of the fire detection sensor(s) 218 (see Figure 3), from a third party data source, and/or use a typical tropospheric level adjusted for known variations of non-nitrogen, non oxygen components. For example, the System Controller 190 may express the fresh air components as a percentage of the fresh air flow FFA, subtract all components that are not nitrogen or oxygen from 100%, and multiply the difference by a percentage of oxygen that is typical in the troposphere.

The System Controller 190 may obtain the concentration of carbon dioxide (CO2) in the fresh air flow FFA from one or more of the fire detection sensor(s) 216 (see Figure 3), from a third party data source, and/or use a typical tropospheric level adjusted for known variations of non-nitrogen, non-oxygen components.

The System Controller 190 may obtain the concentration of carbon monoxide (CO) in the fresh air flow FFA from one or more of the fire detection sensor(s) 216 (see Figure 3), from a third party data source, and/or use a typical local level.

The System Controller 190 obtains the relative humidity“RH” of the fresh air flow FFA from one or more of the fire detection sensor(s) 216 (see Figure 3), from a third party data source, and/or use a typical seasonal and/or local level. The System Controller 190 uses the relative humidity“RH” of the fresh air flow FFA to calculate the water vapor concentration (e.g., ppm). To do so, the System Controller 190 may calculate a water vapor saturation pressure “PWSFA” for the fresh air flow FFA using Equation 18 below:

PWSFA = A*1 Q« ^{m* TFA)/(} TFA ÷ ^T n ⁾⁾ ( ₁ 8) In Equation 18 above, the values of the parameters“A,”“m,” and “Tn” are taken from Table E for the fresh air temperature value TFA. Then, the System Controller 190 may calculate a water vapor pressure PWFA for the fresh air flow FFA using Equation 19 below:

PWFA = PWSFA ^* RH ^* 100 (19)

Next, the System Controller 190 may calculate a water density WDFA (e.g., in g/m ³ ) using Equation 20 below:

WDFA = 2.16679* PWFA /(TFA + 273.1 5) (20)

Finally, the System Controller 190 may calculate the water vapor concentration (e.g., ppm) for the fresh air flow FFA using Equation 21 below.

WFA = 1 ,000,000 * (WDFA/MWW) * Q.000082Q5745*(TFA +273.15)/Patm

(21 ) In Equation 21 above, the variable MWW is the molecular weight of water and the variable“Patm” is atmospheric pressure (measured in atmospheres).

The System Controller 190 may obtain the concentration of each of hydrogen sulfide, sulfur dioxide, VOCs, nitric oxide, nitrogen dioxide, and ozone in the fresh air flow FFA from one or more of the fire detection sensor(s) 216 (see Figure 3), from a third party data source, or assume the concentration is zero.

The System Controller 190 may assume the concentration of hydrogen (Fb) in the fresh air flow FFA is zero.

The System Controller 190 may estimate the concentration of nitrogen using the typical tropospheric level adjusted for known variations of non-nitrogen, non-oxygen components. For example, the System Controller 190 may express the fresh air components as a percentage of the fresh air flow FFA, subtract all components that are not nitrogen or oxygen from 100%, and multiply the difference by a percentage of nitrogen that is typical in the troposphere.

The System Controller 190 may obtain the concentration of soot (or particulates) in the fresh air flow FFA from one or more of the fire detection sensor(s) 218 (see Figure 3) and/or a third party data source (e.g., pollution data).

The System Controller 190 may assume the concentration of ash in the fresh air flow FFA is zero.

in optional block 530, if the fresh air components are not expressed in mass per unit volume (e.g., g/m ³ ), the System Controller 190 converts them. For example, if the concentrations of the fresh air components are expressed as volume-percent at absolute pressure, the System

Controller 190 may convert them to moles per unit volume (see fourth column of Table C) using the fresh air temperature value TE and the ideal gas law.

Then, the System Controller 190 may use the molecular weight of each component to convert the moles per unit volume to mass per unit volume (see fifth column of Table C). By way of a non-limiting example, the mass may be expressed as grams (“g”) and the unit volume may be a cubic meter (m ³ ) shown in the fifth column of Table C)

In block 535, the System Controller 190 totals the mass per unit volume of the fresh air components (e.g., expressed in g/m ³ ) to obtain a fresh air total (see last row of fifth column of Table C).

In optional block 540, the System Controller 190 may divide the mass per unit volume of each of the fresh air components by the fresh air total to obtain fresh air percentages.

In block 545, the System Controller 190 multiplies the mass per unit volume of each of the fresh air components (e.g., expressed in g/m ³ ) by the fresh air flow rate (expressed in m ³ /s) to obtain fresh air component mass flow rates (e.g., g/s) shown in the rightmost column of Table C.

In block 550, the System Controller 190 totals the fresh air component mass flow rates to obtain a total fresh air component flow rate (e.g., g/s) shown in the last row of the rightmost column of Table C. Then, the method 500 terminates.

Referring to Figure 1 , if there is no fire in the system 100, the concentrations (shown in the second column of Table B) of each of the exhaust components are approximately equal to the concentrations (shown in the second column of Table C) of the fresh air components with the exception of water vapor. The concentration of water vapor may increase due to

evaporation when liquid water is present in the vault 112. However, if a fire is present, these concentrations will not be equal. In other words, the evaporation flow Fv and/or the connection(s) flow Fc is/are contributing to the exhaust flow FE.

Figure 13 is a flow diagram of the method 600 of determining flow parameters for the connection(s) flow Fc that may be performed by the System Controller 190 (e.g., when these concentrations are not equal).

In first block 610, the System Controller 190 obtains a connection(s) temperature value Tc. The System Controller 190 may obtain the connection(s) temperature value Tc from one or more of the fire detection sensor(s) 216 (e.g., a thermistor, an infrared sensor, and the like).

Alternatively, the System Controller 190 may estimate the connection(s) temperature value Tc from cable load data and/or heat of combustion, when present. By way of another non-limiting example, the System Controller 190 may assume the connection(s) temperature value Tc is the same as the exhaust temperature value TE.

In block 615, the System Controller 190 obtains an estimated connection flow rate for the connection(s) flow Fc. As mentioned above, the System Controller 190 determines the connection(s) flow rate by adjusting the fresh air flow rate until the mass balance error value is zero.

In block 620, the System Controller 190 estimates component mass flow rates (shown in the fourth column of Table D above) for at least some of the connection(s) components. For example, the component mass flow rates of the carbon dioxide (CO2), carbon monoxide (CO), hydrogen (H2), sulfur dioxide (SO2), VOCs, nitric oxide (NO), nitrogen dioxide (NO2), ozone (O3), Soot, and ash may be obtained by subtracting their respective component mass flow rates in the fresh air flow FFA from their respective component mass flow rates in the exhaust flow FE.

The System Controller 190 may use the component mass flow rate of carbon dioxide to estimate a first (CO2 based) rate at which moles of a polymer are being consumed (shown in in the third row of the rightmost column of Table D above). Oxidative decomposition of a single repeating polymer unit yields a single molecule of carbon dioxide. Therefore, the first (CO2 based) rate (e.g., expressed as moles/second) at which the polymer is consumed by oxidative decomposition is approximately equal to the component mass flow rate of carbon dioxide divided by the molecular weight of carbon dioxide.

The System Controller 190 may use the component mass flow rate of carbon monoxide to estimate a second (CO based) rate at which moles of a polymer are being consumed (shown in the fourth row of the rightmost column of Table D above). Oxidative decomposition (with insufficient oxygen for complete combustion) of a single repeating polymer unit yields a single molecule of carbon monoxide. Thus, the second (CO based) rate (e.g., expressed as moles/second) at which the polymer is consumed by oxidative decomposition is approximately equal to the component mass flow rate of carbon monoxide divided by the molecular weight of carbon monoxide.

Hydrogen is a pyrolysis product of polymers. If hydrogen is present in the exhaust flow FE, the hydrogen likely came from pyrolysis.

Sulfur dioxide is a combustion product of hydrogen sulfide or sulfur used as curing agents or anti-oxidants in polymers. If any sulfur dioxide is present in the exhaust flow FE, the sulfur dioxide likely came from

combustion. Where hydrogen sulfide gas is ubiquitous, sulfur dioxide will accompany most combustion events. The System Controller 190 may ignore the sulfur dioxide because sulfur concentration is low in polymers.

The System Controller 190 may assume the VOCs are methane (CH4). If refined measurements are available for other hydrocarbons, the System Controller 190 may refine the analysis using the same method. The System Controller 190 may use the component mass flow rate of VOCs to estimate a third (CH ₄ based) rate at which moles of a polymer are consumed (shown in the eighth row of the rightmost column of Table D above). Burning a single repeating polymer unit yields a single molecule of methane. Therefore, the third (CHU based) rate (e.g., expressed as moles/second) is approximately equal to the component mass flow rate of VGCs divided by the molecular weight of methane.

Nitric oxide is formed as a result of many combustion events and is particularly prevalent where plasmatization occurs and hence is a marker for electrical arcing. It is not useful directly to estimate burn rate.

Nitrogen dioxide is formed as a result of many combustion events and is particularly prevalent where plasmatization occurs. Therefore, nitrogen dioxide is a marker for electrical arcing but is not useful directly to estimate burn rate.

Ozone is formed as a result of many combustion events and is particularly prevalent where plasmatization occurs. Therefore, ozone is a marker for electrical arcing but is not useful directly to estimate burn rate.

Soot may be primarily carbon. A portion of soot is deposited on surfaces or settles and may not be measured in the exhaust flow FE. The System Controller 190 may ignore such carbon. Alternatively, the System Controller 190 may use the component mass flow rate of soot to estimate a fourth (soot based) rate at which moles of a polymer are consumed (shown in the fourteenth row of the rightmost column of Table D above). The fourth (soot based) rate (e.g., expressed as moles/second) is approximately equal to the component mass flow rate of soot divided by the molecular weight of carbon.

Ash may be primarily silicon dioxide.

Much of the water vapor produced as a result of combustion condenses. When the hot combustion products, including water vapor, enter the vault 112, they cool to the temperature of the vault 112 and condense into liquid water. The System Controller 190 ignores this liquid water. Therefore, the relative humidity RH is assumed to be 100% at the exhaust temperature value TE.

The System Controller 190 uses the relative humidity“RH” of the connection(s) flow Fc to calculate the water vapor concentration (e.g., % of mass). To do so, the System Controller 190 may calculate a water vapor saturation pressure“Pwsc” for the connection(s) flow Fc using Equation 22 below:

Pwsc = A*10« ^{m* TE} ^ ^{TE +Tn} » (22)

!n Equation 22 above, the values of the parameters“A,”“m,” and “Tn” are taken from Table E for the exhaust temperature value TE. Then, the System Controller 190 may calculate a water vapor pressure Pwc for the connection(s) flow Fc using Equation 23 below:

Pwc = Pwsc ^* RH ^* 100 (23)

In Equation 23 above, the relative humidity RH is one. Next, the System Controller 190 may calculate a water density WDc (e.g., in g/m ³ ) using Equation 24 below:

WDc = 2.16879 ^* Pwc /(TE + 273.15) (24)

Finally, the System Controller 190 may calculate the water vapor concentration (e.g., % of mass) for the connection(s) flow Fc using Equation 25 below.

Wc = (WDc/MWW) * 0.00008205745*(TE +273.15)/Patm (25) In Equation 25 above, the variable MWW is the molecular weight of water and the variable“Patm” is atmospheric pressure (measured in atmospheres).

Then, the System Controller 190 may calculate the component mass flow rate of the wafer vapor based on the water vapor concentration.

The component mass flow rate of the oxygen (O2) may be calculated based on the component mass flow rates of the nitrogen (N2), carbon dioxide, hydrogen, and carbon monoxide. Much available oxygen is consumed by oxidative decomposition. However, no combustion is perfect and some oxygen will always remain. To estimate the component mass flow rate of oxygen (O2) the System Controller 190 may multiply the component mass flow rate of nitrogen by both first and second values. The first value is atmospheric O2 divided by atmospheric N2 (e.g., 20.95/78.09). The second value is the component mass flow rate of carbon monoxide (e.g., expressed in moles per second) divided by the component mass flow rate of carbon dioxide (e.g., expressed in moles per second), one is added to this quotient, and the sum is divided by two. Ample carbon dioxide indicates a sufficient supply of oxygen to support oxidative decomposition. The presence of ample carbon monoxide indicates a dearth of oxygen.

The component mass flow rate of the hydrogen (H2) may be measured by the fire detection sensor(s) 216 or calculated based on the component mass flow rates of the carbon dioxide and carbon monoxide. In oxygen rich aerobic environments, hydrogen evolution is close to zero. During high temperature anaerobic pyrolysis, ail of the hydrogen atoms in a polymer are converted to hydrogen gas. Most manhole events fail between these two extremes. The System Controller 190 may calculate the component mass flow rate of the hydrogen (H2) using an aerobic estimate (e.g., about 1.770834) and an anaerobic estimate (0). Then the System Controller 190 multiplies the anaerobic estimate by the first (CO2 based) rate and adds this value to the aerobic estimate multiplied by the second (CO based) rate. Next, the System Controller 190 multiplies this value by the molecular weight of hydrogen (H2) to obtain the component mass flow rate of the hydrogen (H2).

The component mass flow rate of the nitrogen (N2) may be calculated based on the component mass flow rates of the carbon dioxide, carbon monoxide, nitric oxide (NO), and nitrogen dioxide (NO2). Each mole of CO2 and each two moles of CO entrain 3.727 moles of N2. Thus, the System Controller 190 obtains a first value by adding the first (CO2 based) rate to the second (CO based) rate divided by two. NO and NO2 consume diatomic nitrogen in ratios of 1 :1 and 1 :2, respectively to diatomic oxygen. Thus, the System Controller 190 obtains second and third values. The second value is obtained by subtracting from the first value the component mass flow rate of the nitric oxide (NO) divided by the molecular weight of the nitric oxide (NO). The third value is obtained by subtracting from the second value the component mass flow rate of the nitrogen dioxide (NO2) divided by twice the molecular weight of the nitrogen dioxide (NO2). Oxidative decomposition entrains nitrogen with oxygen (N2/O2) in a volume and molar proportion of 78.09/20.95, respectively. Thus, the System Controller 190 obtains the component mass flow rate of the nitrogen (N2) by multiplying the third value by 78.09/20.95 and the molecular weight of nitrogen (N2).

In block 625, the System Controller 190 obtains a consumption rate by totaling the first (CO2 based), second (CO based), third (CH ₄ based), and fourth (soot based) rates at which the polymer is consumed.

In block 630, the System Controller 190 estimates a burn rate for the potential fuel source. The System Controller 190 may calculate the burn rate by multiplying the consumption rate by the molecular weight MWFS (e.g., about 14.03) of the potential fuel source. The burn rate may be expressed in grams per minute or second. The burn rate estimated in block 630 may be used as the burn rate in block 242-K (see Figure 7K) of the calculate method 200-K (see Figure 7K). Alternatively, where there is no fire, the burn rate estimated in block 630 may be used as the FGA in block 2G6-K (see Figure 7K).

In block 635, the System Controller 190 obtains an estimated temperature increase“DT” caused by the burn components reaching the vault 112. For example, the System Controller 190 may obtain the estimated temperature increase from one or more of the fire detection sensor(s) 216 (see Figure 3). The estimated temperature increase“DT” represents a temperature increase above the vault ambient temperature and is required to apply the ideal gas law to the connection(s) flow Fc to complete a robust energy balance.

In block 640, the System Controller 190 may convert the component mass flow rates (e.g., grams per second) to component volume flow rates (cubic meters per second) for each of the connection(s) components. Exemplary component volume flow rates are provided in the second column of Table D above.

Then, the method 600 terminates. Figure 14 is a flow diagram of the method 700 of performing the energy balance. In first block 710, the System Controller 190 obtains a heat capacity (e.g., expressed as joules per gram ^» °K) for each of the exhaust components (see leftmost column of Table B). The heat capacity for each of the exhaust components may be found in relevant literature.

!n next block 720, the System Controller 190 calculates the energy exhausted“Ah” (J/s) by each component. To do so, the System

Controller 190 calculates the first exhaust value“he” by multiplying the heat capacity of the exhaust component by both the component mass flow rate of the exhaust component and absolute temperature (e.g., the exhaust

temperature value TEexpressed in Kelvin). Then, the System Controller 190 calculates, for each fresh air component, the second fresh air value“hf” by multiplying the heat capacity of the fresh air component by both the component mass flow rate of the fresh air component and absolute temperature (e.g., the fresh air temperature value TFA expressed in Kelvin). Next, the System

Controller 190 calculates, for each connection(s) component, the third connection(s) value“h _c ” by multiplying the heat capacity of the connection(s) component by both the component mass flow rate of the connection(s) component and absolute temperature estimated above (e.g., the connection(s) temperature value Tc expressed in Kelvin). Finally, for each component, the System Controller 190 subtracts both the third connection(s) value and the second fresh air value“hr” from the first exhaust value“he” to obtain the energy exhausted“Ah” for the component. In other words, for each component, the energy exhausted“Ah” equals the first exhaust value“he” minus both the fresh air value“hr” and the third connection(s) value“he".

Then, the method 700 terminates.

Figure 15 is a flow diagram of the method 800 of calculating a rate of net water removal“Aw" from the vault 112. It is desirable to keep water out of the vault 112. When the vault 112 does not experience tidal inflows and outflows of water, water can depart the vault 112 in four ways: (a) ieak/diffuse through the concrete, (b) flow out through one or more conduits connected to the vault 112, (c) evaporate and be carried into the external atmosphere 122 by the manhole event suppression system 140, and (d) be pumped out by the vault owner. Depending upon the implementation details, the System

Controller 190 may not able to determine an amount of the water being pumped from the vault 112 because doing so generally requires the removal of the manhole cover 144.

However, the System Controller 190 may utilize the method 800 to calculate an amount of the water leaving the vault 112 by evaporation in the evaporation flow Fv. In first block 810, the System Controller 190 obtains the component mass flow rate“w _e ” of water vapor (see fifth row of rightmost column of Table B above) in the exhaust flow FE, the component mass flow rate“wf" of water vapor (see fifth row of rightmost column of Table C above) in the fresh air flow FFA, and the component mass flow rate“w _c ” of water vapor (see fifth row of fourth column of Table B above) in the connection(s) flow Fc.

Then, in block 820, the System Controller 190 calculates the rate of net water removal“Aw” by subtracting the component mass flow rate“wf” and the component mass flow rate“w _c ” from the component mass flow rate“w _e .” Active ventilation evaporates a great deal of water and transports that water out of the vault 112 and into the atmosphere. By way of non-limiting examples, the System Controller 190 may calculate the rate of net water removal“Aw" in g/min, liter/hr, and/or liter/day.

Then, the method 800 terminates.

The water level sensor 214 may be used to determine a depth of the water present on the floor 188 of the vault 112. In periods when there is no precipitation, any decrease in the depth of the water beyond that attributable to the evaporation flow Fv of evaporating water is caused by water

leaking/diffusing through the concrete and/or flowing out through the conduit(s) connected to the vault 1 12. The component mass flow rate“wc” may be a combination of water leaking/diffusing through the concrete and/or flowing out through the conduit(s) connected to the vault 112. If the System Controller 190 knows the height of connections 118A-118J, the System Controller 190 can calculate how much of the decrease in the depth of the water was caused by water leaking/diffusing through the concrete and water flowing out through the conduit(s) connected to the vault 112. For example, the amount of water leaking/diffusing through the concrete may be empirically modeled with seasonal considerations. Also, visual or infrared cameras may be used to observe water flowing through the conduit(s), and, where it is significant, the System Controller 190 may use this information to estimate an amount of water flowing out through the conduit(s) connected to the vault 112.

On the other side of the coin, the depth of the water can only increase by one of four analogous mechanisms: (A) ieak/diffuse through concrete, (B) flow in from conduit(s), (C) flow through the manhole cover when there is precipitation or (D) human induced irrigation. Human induced irrigation may occur, for example, when city employees wish to enter a storm drain to conduct maintenance and pump water from the storm drain onto city streets. The water pumped from the storm drain flows down the street and enters the vault 112. The System Controller 190 may use weather data to determine when precipitation is occurring. During a precipitation event, the System Controller 190 can monitor the increase in the depth of the water associated with the precipitation event and create a model of water ingress by precipitation rate and precipitation type (e.g , rain, snow, etc.). If more water is entering the vault 112 during a precipitation event than is desirable, the vault owner can take steps to reduce this flow, such as checking that installation seals are proper, diverting run-off flow away from the manhole, and the like.

Dry vaults save their owners money. Vault owners have to pump out water before entering their vaults and such water typically has to be disposed of as hazardous waste. Thus, it is desirable to keep the vaults dry as much as possible (e.g., for a greater portion of the year). Additionally, some industries, such as the U.S. nuclear industry, require that plant owners maintain dry vaults.

The System Controller 190 may use the time constant t to extrapolate into the future. For example, if a CO2 concentration sensor is positioned on the north side of the vault 112 and a propane torch with a constant burn rate is ignited on the south side of the vault 112, at time zero, the CO2 concentration sensor has not yet detected any of the CO2 produced by the propane torch. As time progresses, the CO2 concentration sensor detects more and more CO2 produced by the propane torch. The CO2 produced by the propane torch will reach a plateau after some time. The plateau value of the CO2 concentration is an indication of the size of the fire. When the CO2 concentration has reached its plateau value, the System Controller 190 may determine the time constant t based on geometry of the vault 112 and the turnover rate calculated in block 420 (see Figure 11 ). The time constant t (tau) is the quotient of the vault volume and the exhaust rate. For well mixed vaults (e.g., where active ventilation is deployed) about 63.2% (i.e. 1 -1/e) of a contaminant gas will be removed after one time constant. The turnover rate may be either a rate of dilution of the first type or a predetermined fixed interchange rate. Thus, the System Controller 190 may measure and/or calculate the time constant t using the turnover rate and the geometry of the vault 112. Because the geometry of the vault 112 is constant, the System Controller 190 may associate the time constant t with the turnover rate. The next time the CO2 concentration sensor begins detecting an increase in the CO2 concentration, the System Controller 190 may use the time constant t associated with the current turnover rate in the vault 112 to extrapolate the CO2 concentration detected by the CO2 concentration sensor to its future plateau value. Alternatively, the System Controller 190 may set the rate of dilution of the first type equal to the turnover rate and use the time constant t to

extrapolate the CO2 concentration detected by the CO2 concentration sensor to its future plateau value.

As mentioned above, the plateau value of the CO2 concentration indicates the size of the fire. Thus, the System Controller 190 may determine the size of a new propane fire shortly after the CO2 concentration sensor begins detecting an increase, rather than waiting for the asymptote to be approached.

In a real fire situation, this means quicker indication of fire magnitude.

Each of the flows FE, FFA, FC, and Fv include one or more gases. Typically, the exhaust flow FE will include O2, CO, CO2, H2O, and VOC. The fresh air flow FE and the connection(s) flow Fc may contribute any of these gases to the exhaust flow FE. However, the evaporation flow Fv may contribute only H2O and/or VOC to the exhaust flow FE.

The System Controller 190 may obtain concentrations of O2, CO, CO2, H2O, and/or VOC from third-party atmospheric data (e.g., www.aclima.io, which provides almost real time local data), dedicated sensors connected wirelessly or via wired connections to the System Controller 190, or the fire detection sensor(s) 218 (see Figure 3) where dilution of the second type is available. The System Controller 190 may obtain the concentrations of the components of the fresh air flow FFA by using dilution of the second type to supply 100% fresh air to the fire detection sensor(s) 216 (see Figure 3). Then, the System Controller 190 simply obtains the sensor readings from the fire detection sensor(s) 216 (see Figure 3) and uses them to determine the concentrations of the components of the fresh air flow FFA.

The methods 300, 350, 400, 500, 600, 700, and 800 as well as the equations described above are valid at steady state regardless of the size of the underground vault 112.

In the case of an unventilated environment, sensor drift means that the fire detection sensor(s) 216 (see Figure 3) cannot be relied upon and the System Controller 190 must make a trade-off between falsely alerting the user (e.g., an owner of the underground vault 112) of a condition (a false positive) or setting the alarm level at a dangerously high value and thus failing to alert the user of a potentially dangerous condition (suffering false negatives). Various statistical methods can be used to optimize the required trade-off between false positives and false negatives. Neither false positives nor false negatives are desirable.

Some of these shortcomings can be overcome by using

Calibrationless Operation method 200 described above.

By way of non-limiting examples, any of the following may indicate a fire:

i. CO2 is elevated;

ii. CO is elevated;

iii. VOCs are elevated;

iv. H2O (absolute humidity) is elevated;

v. NO is elevated;

vi. NO2 is elevated;

vii. O3 is elevated;

viii. SO2 is elevated; ix. O2 is depressed (dilution by i - iv);

x. Temperature is elevated;

xi. Particulates are elevated; and/or

xii. H2 is elevated.

Another non-limiting example of an alarm state may indicate that flammable vapors are accumulating. By way of non-limiting examples, any of the following conditions may indicate that flammable vapors are accumulating:

i. CO is elevated;

ii. H2 is elevated;

iii. VOCs are elevated; and/or

iv. H2S is elevated.

DILUTION BY THE SYSTEM CONTROLLER

The System Controller 190 is configured to use an algorithm, heuristics, human input, and/or artificial intelligence to achieve the desired measurements and to exercise the desired controls. Active and continuous ventilation enjoys benefits beyond the primary purpose of explosion prevention. Non-limiting examples of such benefits include cooling and drying the manhole environment, both of which contribute to improved equipment reliability and life.

The System Controller 190 may control or throttle the exhaust rate over limited periods of time for calibration purposes. The System Controller 190 may calculate the time constants t (for associated turnover rates) for the underground vault 112, the time constants t for the manhole event suppression system 140, and the time constants t for the two types of dilution using methods that are well known in the art. Alternatively, the System Controller 190 may empirically deduce these time constants t by throttling (to adjust the dilution of the first type) and by altering the IMR (to adjust the dilution of the second type). Non-limiting examples of such purposeful dilution adjustments follow.

The System Controller 190 may frequently and automatically calibrate the fire detection sensor(s) 216 (see Figure 3) utilizing one or more of the following three tools:

1. a source of fresh air from the external atmosphere 122, 2. the ability to vary a ratio of exhausted air and the fresh air, and

3. the ability to spike the fresh air with at least one pure calibration gas (“cai-gas”).

The fresh air from the external atmosphere 122 may be used to dilute a sample. For example, if an amount of a component gas of interest in a sample (e.g., concentration of the component gas) approaches an upper limit in the sensing range of a sensor, the System Controller 190 may use dilution of the first type and/or the second type to reduce the amount of the component gas of interest in the sample. Conversely, if the amount of the component gas of interest in the sample is at or below a lower limit in the sensing range of the sensor, the System Controller 190 may decrease dilution (at least temporarily) to increase the amount of the component gas of interest in the sample. In this way, the System Controller 190 may use dilution of the first type and/or the second type to ensure the sensor is able to detect the amount of the

component gas of interest by keeping the amount of the component gas of interest inside the sensors sensing range.

If at least one flammable component gas is approaching an amount (e.g., a concentration) that is dangerous (e.g., explosive or poisonous), the System Controller 190 may use dilution of the first type to reduce the amount of the at least one flammable component gas until the maximum exhaust flow rate is realized.

The System Controller 190 may calibrate one of the fire defection sensor(s) 218 (see Figure 3) by delivering to that sensor any IMR (zero to infinity) of the exhaust flow FE and fresh air from the external atmosphere 122. For example, the fresh air may contain about 21 % oxygen. The System

Controller 190 may direct the monitor 126 to supply an IMR of zero, which includes 0% exhaust flow and 100% fresh air, to an oxygen concentration sensor. Then, the System Controller 190 may calibrate the oxygen

concentration sensor to 21 %. Similarly, fresh air typically has about 400 ppm of carbon dioxide. The System Controller 190 may direct the monitor 126 to supply a ratio of zero, which includes 0% exhaust flow and 100% fresh air, to a carbon dioxide concentration sensor. Then, the System Controlier 190 may calibrate the carbon dioxide concentration sensor to 400 ppm.

Spiking is best implemented with materials that can be safety contained in liquid form, but are readily vaporized at temperature and pressure conditions found in the underground vault 112 (referred to as Vault

Temperature and Pressure or“VTP”). Carbon dioxide, propane, and butane are examples of materials that are safely and easily stored as liquids. Liquid spiking agents are preferred because a large volume of gas can be generated from a relatively small volume of liquid. For example, the ratio of gas volume (standard temperature and pressure or STP) to liquid volume for carbon dioxide is about 390. Other gases of interest as spiking agents may not be easily liquefied and instead can be stored as high-pressure gases. Because a volume ratio of such gaseous spiking agents at VTP and at storage pressure is much less than the volume ratio of liquid spiking agents (e.g., an ideal gas such as oxygen at 2000 psi has a volume ratio of about 136, or roughly one-third of liquid carbon dioxide), these gaseous spiking agents require larger containers, may be utilized less frequently, or must be periodically refilled or swapped.

It is not possible to calibrate a sensor with zero data points. A single data point can be used for offset calibration. The shortcoming of the single point offset calibration is the slope of the response curve may also drift.

A multi-point calibration is superior to a single point calibration because it allows adjustment of both the intercept and the slope of the calibration curve. More than two data points improve the calibration further, but with diminishing returns. Non-limiting examples of two-point calibration are provided in Table F (below). The System Controller 190 can calibrate one or more sensors using the information of Table F:

Table F

When low concentration gases are encountered, the veracity of the measurement can be tested by varying the dilution and/or immediately zero calibrating the relevant sensor(s). This is particularity useful to prevent false positives from errant sensors.

Figure 16 illustrates a simplified network 900 of underground vaults 908 (e.g., each like the vault 112) and underground connections 910 (e.g., each like the connections 118A-118J). Each of the connections 910 may be characterized as being an underground gas source. The network 900 includes at least one monitor 912 (like the monitor 126 illustrated in Figure 1 ) and the System Controller 190.

In Figure 16, the vaults 908 include nine vaults A-1 to A-3, B-1 to B-3, and C-1 to C-3. One or more of the vaults 908 may house electrical equipment and/or electrical cables (e.g., like the electrical equipment 119 of Figure 1 ). Each of the vaults 908 may be characterized as being a node. Thus, Figure 1 shows a simple nine-node network with two external connections Ext 01 and Ext 02. The external connection Ext 01 is connected to the vault B-3 and the external connection Ext 02 is connected to the vault C-2. Optionally, one or more of the vaults 908 may include the manhole event suppression system 140.

In the embodiment illustrated, the connections 910 include connections AA12, AA23, BB12, BB23a, BB23b, CC12, CC23, AB11 , AB22a, AB22b, AB33, BC11 , BC22a, BC22b, and BC33. Each of the connections 910 connects a pair of the vaults 908 together. For example, the connection AA12 connects the pair of vaults A-1 and D-2 together Each of the connections 910 may be implemented as conduit, duct, or pipe. Some of the connections 910 include at least one cable that extends therethrough. If a connection includes one or more cables, a gap may be defined between the cable(s) and the connection. Such a gap provides fluidic communication between the connected vaults. Thus, a fluidic flow may be present between the connected vaults. In some cases, a technique referred to as duct plugging, which involves installing a plug between the cable(s) and the connection, may be used to limit such fluidic flow. Unfortunately, all such duct plugs are likely to leak after aging and especially if a fire (oxidative decomposition, pyrolysis, and/or plasmatization) occurs and creates a positive pressure in the gap defined between the cable(s) and the connection. Thus, generally speaking, the connections 910 allow at least some communication between the vaults 908.

For ease of illustration, Figure 16 omits connections (e.g., conduits) between buiiding(s) owned by the vault owner’s customers and one or more of the vaults 908 and/or the connections 910. These connections provide electrical and fluidic communication with one or more adjacent buildings that may serve as pathways for dangerous gases to enter customer premises.

Additionally, these connections may provide additional sources of undesirable gases inside the network 900.

The at least one monitor 912 has been illustrated as monitors 912A-912I positioned inside the vaults A-1 to A-3, B-1 to B-3, and C-1 to C-3, respectively. However, this is not a requirement. The network 900 may include any number of monitors each like the monitors 912A-912! installed in any of the vaults 908 and/or the connections 910.

The System Controller 190 communicates over wireless or wired connections with the monitors 912A-912I. The monitors 912A-912I are each configured to send sensor data captured by the sensors 214 and 218 to the System Controller 190. By way of a non-limiting example, the System

Controller 190 may be implemented as a computing device 12 illustrated in Figure 3 and described below.

Figure 16 illustrates a fire 920 (oxidative decomposition, pyrolysis, and/or plasmatization) in the connection BB12 connecting the vaults B-1 and B- 2

In this example, the fire detection sensor(s) 216 will be described as being implemented as chemical or gas concentration sensors. Such gas concentration sensors are not defined and can utilize a variety of physical or chemical technologies, such as infra-red absorbance, florescence quenching, electro-chemical, thermal-conductivity, and/or flame ionization. Gases to be tested for the presence of at least one analyte are conveyed to the sensors (e.g., by tubing or ducting). For these types of sensors, which are each located in a single vault, to determine where the fire 920 is located in the network 900, complicated plumbing is required to draw gas from every possible source of the analyte(s) of interest. For example, to determine which of the connections AB11 , BB12, and BC11 that exit from the vault B-1 harbors the fire 920, the gases emanating from the connections AB11 , BB12, and BC11 must be sampled independently by individual sets of sensors or a conveyance means must be used to convey a sample from each location to a central sensor package. The conveyance means may include at least one tube, appropriate tubing connectors, at least one pump, and valves actuated by the System Controller 190. The conveyance means delivers a sample of gases collected from each of the connections DB11 , BB12, and BC11 to the central sensor package.

While Figure 16 illustrates the fire 920 (oxidative decomposition, pyrolysis, and/or plasmatization) occurring in the connection BB12, one of ordinary skill in the art would recognize that the illustrated fire is only one of many possible sources of dangerous gases. Other sources include, but are not limited to, natural gas leaks from nearby pipelines, liquid-phase gasoline or diesel plumes, hydrogen sulfide, and volatile organic compounds (VOCs) from biological decomposition. When the manhole event suppression system 140 is deployed in each of the vaults 908, it is possible to narrow down the location of the offending fire or gas source. The exhaust rates of the relevant manhole event suppression systems 140 may be set such that desired pressure differentials between the external and internal atmospheres 122 and 124 (see Figure 1 ) can be established. Then, a flow of one or more gases created by the fire 920 (or fire by-product(s)) into two or more of the vaults 908 measured and used to determine where the fire 920 is located. For example, if the manhole event suppression systems 140 operating in each of the vault B-1 and B-2 have about the same exhaust rates and employ the same vented manhole cover the vault B-1 and B-2 have about the same negative pressure differential between the external and internal atmospheres 122 and 124 (see Figure 1 ). Thus, if the annular duct space does not include duct restrictions, the flow rate of a first portion of the fire by-product(s) created by the fire 920 flowing into the vault B-1 would be about twice that of the flow rate of a second portion of the fire by products) flowing into the vault B-2 because pneumatic resistance from the fire 920 to the vault B-1 is about half the pneumatic resistance from the fire 920 to the vault B-2. Depending on the size of the fire 920, those of the vaults 908 adjacent to the vaults B-1 and B-2 may also experience small increases in the fire by-product(s), but these increases would be considerably less and considerably delayed by active ventilation generated by the manhole event suppression systems 140 in the vaults B-1 and B-2 and a distance (e.g., several hundred feet) between the vaults. Thus, metrics, including the relative concentrations of the analytes and their times of arrival, can be used to “triangulate” the connection that likely harbors the fire 920 (or gas source) and determine the approximate location of the fire 920 (or gas source). When more than one of the connections 910 joins two of the vaults 908 together, it may not be possible to identify the connection harboring the fire 920 (or gas source), but connections to other vaults can be eliminated from consideration during troubleshooting. COMPUTING DEVICE

Figure 17 is a diagram of hardware and an operating environment in conjunction with which implementations of the System Controller 190 (see Figures 1 and 3) may be practiced. The description of Figure 17 is intended to provide a brief, genera! description of suitable computer hardware and a suitable computing environment in which implementations may be practiced. Although not required, implementations are described in the general context of computer-executable instructions, such as program modules, being executed by a computer, such as a personal computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types.

Moreover, those of ordinary skill in the art will appreciate that implementations may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Implementations may also be practiced in distributed computing environments (e.g., cloud computing platforms) where tasks are performed by remote processing devices that are linked through a

communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

The exemplary hardware and operating environment of Figure 17 includes a general-purpose computing device in the form of the computing device 12. The System Controller 190 (see Figures 1 and 3) may be

substantially identical to the computing device 12 By way of non-limiting examples, the computing device 12 may be implemented as a laptop computer, a tablet computer, a web enabled television, a personal digital assistant, a game console, a smartphone, a mobile computing device, a cellular telephone, a desktop personal computer, and the like.

The computing device 12 includes a system memory 22, the processing unit 21 , and a system bus 23 that operatively couples various system components, including the system memory 22, to the processing unit 21. There may be only one or there may be more than one processing unit 21 , such that the processor of computing device 12 includes a single central- processing unit (“CPU”), or a plurality of processing units, commonly referred to as a parallel processing environment. When multiple processing units are used, the processing units may be heterogeneous. By way of a non-limiting example, such a heterogeneous processing environment may include a conventional CPU, a conventional graphics processing unit (“GPU”), a floating point unit (“FPU”), combinations thereof, and the like.

The computing device 12 may be a conventional computer, a distributed computer, or any other type of computer.

The system bus 23 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The system memory 22 may also be referred to as simply the memory, and includes read only memory (ROM) 24 and random access memory (RAM) 25. A basic input/output system (BIOS) 26, containing the basic routines that help to transfer information between elements within the computing device 12, such as during start-up, is stored in ROM 24. The computing device 12 further includes a hard disk drive 27 for reading from and writing to a hard disk, not shown, a magnetic disk drive 28 for reading from or writing to a removable magnetic disk 29, and an optical disk drive 30 for reading from or writing to a removable optical disk 31 such as a CD ROM, DVD, or other optical media.

The hard disk drive 27, magnetic disk drive 28, and optical disk drive 30 are connected to the system bus 23 by a hard disk drive interface 32, a magnetic disk drive interface 33, and an optical disk drive interface 34, respectively. The drives and their associated computer-readable media provide nonvolatile storage of computer-readable instructions, data structures, program modules, and other data for the computing device 12. It should be appreciated by those of ordinary skill in the art that any type of computer-readable media which can store data that is accessible by a computer, such as magnetic cassettes, flash memory cards, solid state memory devices (“SSD"), USB drives, digital video disks, Bernoulli cartridges, random access memories (RAMs), read only memories (ROMs), and the like, may be used in the exemplary operating environment. As is apparent to those of ordinary skill in the art, the hard disk drive 27 and other forms of computer-readable media (e.g., the removable magnetic disk 29, the removable optical disk 31 , flash memory cards, SSD, USB drives, and the like) accessible by the processing unit 21 may be considered components of the system memory 22.

A number of program modules may be stored on the hard disk drive 27, magnetic disk 29, optical disk 31 , ROM 24, or RAM 25, including the operating system 35, one or more application programs 36, other program modules 37, and program data 38. A user may enter commands and information into the computing device 12 through input devices such as a keyboard 40 and pointing device 42. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, touch sensitive devices (e.g., a stylus or touch pad), video camera, depth camera, or the like. These and other input devices are often connected to the processing unit 21 through a serial port interface 46 that is coupled to the system bus 23, but may be connected by other interfaces, such as a parallel port, game port, a universal serial bus (USB), or a wireless interface (e.g., a Bluetooth interface). A monitor 47 or other type of display device is also connected to the system bus 23 via an interface, such as a video adapter 48. In addition to the monitor, computers typically include other peripheral output devices (not shown), such as speakers, printers, and haptic devices that provide tactile and/or other types of physical feedback (e.g., a force feed back game controller).

The input devices described above are operable to receive user input and selections. Together the input and display devices may be described as providing a user interface.

The computing device 12 may operate in a networked environment using logical connections to one or more remote computers, such as remote computer 49. These logical connections are achieved by a communication device coupled to or a part of the computing device 12 (as the local computer). Implementations are not limited to a particular type of communications device. The remote computer 49 may be another computer, a server, a router, a network PC, a client, a memory storage device, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computing device 12. The remote computer 49 may be connected to a memory storage device 50. The logical connections depicted in Figure 17 include a local-area network (LAN) 51 and a wide-area network (WAN) 52. Such networking environments are

commonplace in offices, enterprise-wide computer networks, intranets and the Internet.

Those of ordinary skill in the art will appreciate that a LAN may be connected to a WAN via a modem using a carrier signal over a telephone network, cable network, cellular network, or power lines. Such a modem may be connected to the computing device 12 by a network interface (e.g., a serial or other type of port). Further, many laptop computers may connect to a network via a cellular data modem.

When used in a LAN-networking environment, the computing device 12 is connected to the local area network 51 through a network interface or adapter 53, which is one type of communications device. When used in a WAN-networking environment, the computing device 12 typically includes a modem 54, a type of communications device, or any other type of

communications device for establishing communications over the wide area network 52, such as the Internet. The modem 54, which may be internal or external, is connected to the system bus 23 via the serial port interface 46 In a networked environment, program modules depicted relative to the personal computing device 12, or portions thereof, may be stored in the remote computer 49 and/or the remote memory storage device 50. It is appreciated that the network connections shown are exemplary and other means of and

communications devices for establishing a communications link between the computers may be used.

The computing device 12 and related components have been presented herein by way of particular example and also by abstraction in order to facilitate a high-level view of the concepts disclosed. The actual technical design and implementation may vary based on particular implementation while maintaining the overall nature of the concepts disclosed.

In some embodiments, the system memory 22 stores computer executable instructions that when executed by one or more processors cause the one or more processors to perform all or portions of one or more of the methods (including the method 200-A illustrated in Figure 7A, the methods 200- C to 2G0-W illustrated in Figures 7C-7W, and the method 300, 350, 400, 500, 800, 700, and 800 illustrated in Figures 9, 10, 11 , 12, 13, 14, and 15, respectively) described above. Such instructions may be stored on one or more non-transitory computer-readable media.

In some embodiments, the system memory 22 stores computer executable instructions that when executed by one or more processors cause the one or more processors to generate the notifications identified in

Figures 7F-7H and described above. Such instructions may be stored on one or more non-transitory computer-readable media.

Embodiments of the present disclosure can be described in view of the following clauses:

1. A method for use with a system of interconnected underground vaults, the method comprising:

obtaining, by a system controller, a first metric from a first sensor installed in a first underground vault of the system;

obtaining, by the system controller, a second metric from a second sensor installed in a second underground vault of the system, the first and second underground vaults being in fluid communication with one another via one or more connections;

locating, by the system controller, a gas source based at least in part on one or both of the first and second metrics; and

performing, by the system controller, an action comprising at least one of identifying the gas source to one or more users or altering a rate of atmospheric turnover in at least a portion of the system.

2. The method of clause 1 , wherein the first and second underground vaults each include a manhole event suppression system, and the manhole event suppression system of the first underground vault is configured to provide active ventilation to the first underground vault, and

the manhole event suppression system of the second underground vault is configured to provide active ventilation to the second underground vault. 3. The method of clause 2, wherein the active ventilation exhausts gases from each of the first and second underground vaults thereby creating negative pressure inside the first and second underground vaults compared to an atmospheric pressure outside the system

4. The method of any of clauses 1 -3, wherein the gas source is at least one of the one or more connections,

the first and second metrics are first and second concentrations, respectively, of at least one analyte, and

a portion of the at least one analyte originated from the gas source.

5. The method of clause 4, further comprising: identifying, by the system controller, from where in the gas source the portion of the at least one analyte originated based at least in part on the first and second concentrations

6. The method of clause 4 or 5, further comprising:

determining, by the system controller, a first time of arrival at which a first portion of the at least one analyte arrived in the first underground vault;

determining, by the system controller, a second time of arrival at which a second portion of the at least one analyte arrived in the second underground vault; and

identifying, by the system controller, from where in the gas source the portion of the at least one analyte originated based at least in part on a difference between the first time of arrival and the second time of arrival.

7. The method of any of clauses 1 -6, wherein the gas source is a location of a fire, and

the first and second metrics are first and second flow rates, respectively, of a by-product of the fire. A system comprising: a first sensor configured to be installed in a first underground vault of an underground vault system of interconnected underground vaults;

a second sensor configured to be installed in a second underground vault of the underground vault system, the first and second underground vaults being in fluid communication with one another via one or more connections; and

a system controller comprising at least one processor connected to memory storing instructions executable by the at least one processor, the instructions, when executed by the at least one processor, causing the at least one processor to:

obtain a first metric from the first sensor,

obtain a second metric from the second sensor,

locate a gas source based at least in part on one or both of the first and second metrics, and

perform an action comprising at least one of identifying the gas source to one or more users or altering a rate of atmospheric turnover in at least a portion of the underground vault system.

9. The system of clause 8, further comprising:

a first manhole event suppression system configured to be installed in the first underground vault and to provide active ventilation to the first underground vault; and

a second manhole event suppression system configured to be installed in the second underground vault and to provide active ventilation to the second underground vault.

10. The system of clause 9, wherein the active ventilation exhausts gases from each of the first and second underground vaults thereby creating negative pressure inside the first and second underground vaults compared to an atmospheric pressure outside the underground vault system.

11. The system of any of clauses 8-10, wherein the gas source is at least one of the one or more connections, the first and second metrics are first and second concentrations, respectively, of at least one analyte, and

a portion of the at least one analyte originated from the gas source. 12. The system of clause 11 , wherein the instructions, when executed by the at least one processor, cause the at least one processor to identify from where in the gas source the portion of the at least one analyte originated based at least in part on the first and second concentrations

13. The system of clause 11 or 12, wherein the instructions, when executed by the at least one processor, cause the at least one processor to:

determine a first time of arrival at which a first portion of the at least one analyte arrived in the first underground vault;

determine a second time of arrival at which a second portion of the at least one analyte arrived in the second underground vault; and

identify from where in the gas source the portion of the at least one analyte originated based at least in part on a difference between the first time of arrival and the second time of arrival.

14. The system of any of clauses 8-13, wherein the gas source is a location of a fire, and

the first and second metrics are first and second flow rates, respectively, of a by-product of the fire.

15. A system comprising:

a gas sensor;

a fresh air flow controller configured to deliver fresh air to the gas sensor;

a sample flow controller configured to deliver a sample to the gas sensor; and

a system controller comprising at least one processor connected to memory storing instructions executable by the at least one processor, the instructions, when executed by the at least one processor, causing the at least one processor to:

determine an intermix ratio of the sample to the fresh air, instruct the fresh air flow controller and the sample flow controller to deliver the fresh air and the sample, respectively, to the gas sensor in accordance with the intermix ratio, the fresh air flow controller and the sample flow controller being configured to adjust the fresh air and the sample, respectively, delivered to the gas sensor in response to the instruction, and receive a sensor reading from the gas sensor after the fresh air flow controller and the sample flow controller have adjusted the fresh air and the sample, respectively.

18. The system of clause 15, wherein the intermix ratio changes the fresh air with respect to the sample to thereby change a dilution level of the sample, and

the instructions, when executed by the at least one processor, cause the at least one processor to vary the dilution level by a predetermined amount to thereby implement multi-point calibration.

17 The system of clause 16, wherein varying the dilution level comprises instructing the sample flow controller not to deliver the sample to the gas sensor thereby causing the gas sensor to receive only the fresh air delivered by the fresh air flow controller and infinitely diluting the sample with the fresh air.

18. The system of clause 17 for use with an atmospheric level of at least one analyte, wherein the gas sensor is configured to sense the at least one analyte, and

the instructions, when executed by the at least one processor, cause the at least one processor to calibrate the gas sensor using the atmospheric level of the at least one analyte.

19. The system of clause 18 wherein the Instructions, when executed by the at least one processor, cause the at least one processor to obtain a typical atmospheric level of the at least one analyte and use the typical atmospheric level as the atmospheric level.

20. The system of clause 18 or 19, wherein the at least one analyte comprises an atmospheric analyte, and the system further comprises:

a nearby calibrated sensor configured to detect the atmospheric analyte, the instructions, when executed by the at least one processor, causing the at least one processor to receive a calibrated sensor reading of the atmospheric analyte from the nearby calibrated sensor and use the calibrated sensor reading as the atmospheric level. 21. The system of any of clauses 18-20, wherein the

instructions, when executed by the at least one processor, cause the at least one processor to receive an estimated value based upon atmospheric modeling, and use the estimated value as the atmospheric level.

22. The system of any of clauses 15-21 , wherein the

instructions, when executed by the at least one processor, cause the at least one processor to calibrate the gas sensor based at least in part on the sensor reading.

23. The system of clause 22, wherein the intermix ratio includes 100% fresh air, and

calibrating the gas sensor comprises setting a sensor baseline value for the gas sensor equal to the sensor reading received from the gas sensor after the fresh air flow controller and the sample flow controller adjust the fresh air and the sample, respectively.

24. The system of any of clauses 15-23, wherein the

instructions when executed by the at least one processor, cause the at least one processor to adjust the intermix ratio such that the gas sensor operates within its sensitivity range.

25. The system of clause 24, wherein the instructions, when executed by the at least one processor, cause the at least one processor to determine the gas sensor is operating near or above its upper sensitivity limit, and increase the fresh air of the intermix ratio to allow the gas sensor to operate within its sensitivity range.

26 The system of clause 24 or 25, wherein the instructions, when executed by the at least one processor, cause the at least one processor to determine the gas sensor is operating near or below its lower sensitivity limit, and decrease the fresh air of the intermix ratio to allow the gas sensor to operate within its sensitivity range

27 The system of any of clauses 15-26, wherein the gas sensor is a first one of a plurality of gas sensors, and

the instructions, when executed by the at least one processor, cause the at least one processor to increase or decrease the intermix ratio for a second one of the plurality of gas sensors after the sensor reading has been received. 28 The system of any of clauses 15-27, wherein the intermix ratio changes the fresh air with respect to the sample to thereby change a dilution level of the sample, and

the instructions, when executed by the at least one processor, cause the at least one processor to vary the dilution level by a predetermined amount and perform a drift validation test.

29 The system of any of clauses 15-28, further comprising: a plurality of sensor groups, a first one of the plurality of sensor groups comprising the gas sensor, the instruction causing the fresh air flow controller and the sample flow controller to deliver the fresh air and the sample, respectively, to the first sensor group in accordance with the intermix ratio

30 The system of clause 29, wherein the inter ix ratio is a first intermix ratio, and the instructions, when executed by the at least one

processor, cause the at least one processor to:

determine a second intermix ratio of the sample to the fresh air, and instruct the fresh air flow controller and the sample flow controller to deliver the fresh air and the sample, respectively, to a second one of the plurality of sensor groups in accordance with the second intermix ratio.

31. The system of any of clauses 15-30, further comprising: a plurality of sensor groups, a particular one of the plurality of sensor groups comprising the gas sensor,

the instructions, when executed by the at least one processor, causing the at least one processor to operate at least two of the plurality of sensor groups in different modes.

32. The system of any of clauses 15-31 , wherein the gas sensor is a first one of a plurality of gas sensors, and

the instructions, when executed by the at least one processor, cause the at least one processor to operate the first gas sensor at a first sample rate and a second one of the plurality of gas sensors at a second sample rate, the first and second sample rates being different from one another.

33. The system of clause 32, wherein the first gas sensor is a member of a sensor group,

the instructions, when executed by the at least one processor, cause the at least one processor to choose the first sample rate, and

the first sample rate limits a cumulative exposure of the sensor group to exhaust.

34. A computer-implemented method comprising: determining, by a computing system, an intermix ratio of an exhaust sample stream to a fresh air sample stream;

instructing, by the computing system, a fresh air flow controller and a sample flow controller to deliver the exhaust sample stream and the fresh air sample stream, respectively, to a gas sensor in accordance with the intermix ratio; and

receiving, by the computing system, a sensor reading from the gas sensor after the fresh air flow controller and the sample flow controller have adjusted the exhaust sample stream and the fresh air sample stream, respectively.

35 The method of clause 34, further comprising: obtaining, by the computing system, an atmospheric level of at least one analyte, the gas sensor being configured to sense the at least one analyte; and

calibrating, by the computing system, the gas sensor using the atmospheric level of the at least one analyte.

36 The method of clause 35, wherein obtaining the atmospheric level of the at least one analyte comprises:

receiving a calibrated sensor reading from a nearby calibrated sensor configured to detect the at least one analyte; and

using the calibrated sensor reading as the atmospheric level.

37 The method of any of clauses 34-36, wherein the intermix ratio includes 100% fresh air, and the method further comprises:

calibrating, by the computing system, the gas sensor by setting a sensor baseline value for the gas sensor equal to the sensor reading received from the gas sensor after the fresh air flow controller and the sample flow controller have adjusted the fresh air and the sample, respectively. 38 The method of any of clauses 34-37, further comprising: adjusting, by the computing system, the intermix ratio such that the gas sensor operates within its sensitivity range.

39. The method of any of clauses 34-38, wherein the intermix ratio is a first intermix ratio, and further comprises:

determining, by the computing system, a second intermix ratio of the exhaust sample stream to the fresh air sample stream, the gas sensor belonging to a first one of a plurality of sensor groups; and

instructing, by the computing system, the fresh air flow controller and the sample flow controller to deliver the exhaust sample stream and the fresh air sample stream, respectively, to a second one of the plurality of sensor groups in accordance with the second intermix ratio.

40. A system comprising:

an active ventilation device configured to be installed in an underground vault and to generate a flow of exhaust therefrom, the flow of exhaust having an exhaust rate;

at least one gas sensor in physical communication with the flow of exhaust; and

a system controller operable to communicate with the active ventilation device and operable to receive first sensor readings from each of the at least one gas sensor, the system controller being configured to determine a selected reading of the first sensor readings indicates that a manhole event is occurring, and instruct the active ventilation device to change the exhaust rate to achieve a desired dilution level when the selected reading indicates that the manhole event is occurring, the selected reading having been received from a selected one of the at least one gas sensor, the active ventilation device being configured to change the exhaust rate in response to being instructed to do so by the system controller, the system controller being configured to receive second sensor readings from each of the at least one gas sensor after the exhaust rate has been changed, determine whether the selected gas sensor is exhibiting sensor drift based at least in part on the second sensor readings, and perform an action when the system controller determines the selected gas sensor is not exhibiting sensor drift, the action including at least one of notifying one or more users or instructing the active ventilation device to alter the exhaust rate, the active ventilation device being configured to alter the exhaust rate in accordance with the instruction to do so.

41. The system of clause 40, wherein the system controller is operable to calibrate the selected gas sensor when the system controller determines the selected gas sensor is exhibiting sensor drift.

42. The system of clause 41 , wherein calibrating the selected gas sensor comprises: supplying fresh air to the selected gas sensor, and

setting a sensor baseline to a new sensor reading obtained after the fresh air has been supplied to the selected gas sensor.

43. The system of clause 41 or 42, wherein calibrating the selected gas sensor comprises:

instructing the active ventilation device to increase the exhaust rate, the active ventilation device being configured to increase the exhaust rate in accordance with the instruction to do so, and

setting a sensor baseline to a new sensor reading obtained after the fresh air has been supplied to the selected gas sensor.

44. The system of any of clauses 40-43, wherein the selected reading is a first reading, the system controller has an atmospheric value for a gas measured by the selected gas sensor,

a second reading is one of the second sensor readings received from the selected gas sensor,

the system controller is operable to determine a first rate at which the first reading changed with respect to the atmospheric value,

the system controller is operable to determine a second rate at which the second reading changed with respect to the first reading, and

the system controller determines the selected gas sensor is not exhibiting sensor drift when the second rate is greater than the first rate.

45. The system of any of clauses 40-44, wherein the second sensor readings are received after an amount of time has elapsed after the exhaust rate has been changed, and

the system controller is operable to determine the amount of time based in part on a time constant associated with the underground vault

46. The system of clause 45, wherein the system controller is operable to calculate the time constant based on a volume of the underground vault. 47. The system of any of clauses 40-46, wherein the selected reading is a first reading, the system controller has an atmospheric value for a gas measured by the selected gas sensor,

a second reading is one of the second sensor readings received from the selected gas sensor,

the system controller is operable to determine a first rate at which the first reading changed with respect to the atmospheric value,

the system controller is operable to determine a second rate at which the second reading changed with respect to the first reading, and

the system controller determines the selected gas sensor is exhibiting sensor drift when the second rate is equal to the first rate.

48. A system for use with an underground vault, the system comprising:

an active ventilation device configured to be installed in the underground vault, the active ventilation device being configured to generate an exhaust mass flow from the underground vault, a fresh air mass flow flowing into the underground vault from an external atmosphere, an event mass flow originating from a manhole event; and

a mass flow estimator configured to estimate a total exhaust mass flow value based on the exhaust mass flow, a total fresh air mass flow value based on the fresh air mass flow, and a total event mass flow value based on the event mass flow, the mass flow estimator being configured to estimate individual component masses of components of each of the exhaust mass flow, the fresh air mass flow, and the event mass flow, the mass flow estimator being configured to determine a size of a fire in at least one of the underground vault and one or more connections connected to the underground vault, the mass flow estimator being configured to calculate a rate of accumulation of flammable vapors inside the underground vault.

49. The system of clause 48, wherein a vapor mass flow is evaporating from a fluid inside the underground vault,

the mass flow estimator is configured to estimate a total vaporized liquids mass flow value based on the vapor mass flow, and the mass flow estimator is configured to estimate the individual component masses of components of the vapor mass flow.

50. The system of clause 48 or 49, wherein the exhaust mass flow has an exhaust rate,

the mass flow estimator is configured to extrapolate the rate of accumulation of the flammable vapors to estimate when an amount of the flammable vapors in the underground vault reaches a dangerous level, and the mass flow estimator is configured to adjust the exhaust rate to avoid or forestall a dangerous condition.

51. The system of any of clauses 48-50, wherein the mass flow estimator is configured to determine an exhaust enthalpy for the exhaust mass flow, a fresh air enthalpy for the fresh air mass flow, and an event enthalpy for the event mass flow,

the mass flow estimator is configured to determine a quantity of energy dissipated by the exhaust mass flow based on the exhaust enthalpy, the fresh air enthalpy, and the event enthalpy, and

the mass flow estimator is configured to report at least one of the quantity of energy dissipated by the exhaust mass flow and a quantity of energy from the fire to a user.

52. The system of any of clauses 48-51 , further comprising: at least one gas sensor configured to measure a concentration of wafer in the exhaust mass flow, the mass flow estimator being configured to estimate a net water flux based on the concentration of wafer, the mass flow estimator being configured to report the net water flux to a user.

53. The system of any of clauses 48-52 for use with a source of weather information, wherein the mass flow estimator is configured to receive a relative humidity from the source of weather information and estimate a net water flux based on the relative humidity, and

the mass flow estimator is configured to report the net water flux to a user. 54. A system comprising:

an active ventilation device installed in an underground vault, the active ventilation device being configured to generate an exhaust flow from the underground vault; and

a mass flow estimator configured to determine a percentage corrected lower explosive limit for at least one gas inside the underground vault and instruct the active ventilation device to increase an exhaust flow rate of the exhaust flow when the percentage corrected lower explosive limit is equal to or greater than a threshold value, the active ventilation device being configured to increase the exhaust flow rate in response to the instruction.

55. The system of clause 54, wherein the threshold value is 100% times a safety factor between 33% and 100%.

56. The system of clause 54 or 55, wherein the safety factor is 75%.

57. A method comprising:

estimating, by a system controller, relative contributions of at least two of oxidative decomposition, pyrolysis, piasmatization, and flammable gas accumulation to a fire occurring in a duct-manhole system; and

performing, by the system controller, an action based at least in part on the estimated relative contributions, the action including at least one of notifying one or more users or altering a rate of atmospheric turnover in the duct-manhole system.

58. The method of clause 57, further comprising: determining, by a system controller, a phase of the fire based at least in part on the relative contributions; and

informing, by the system controller, the one or more user of the phase of the fire

59. The method of clause 58, further comprising: determining, by the system controller, a rate of change of the fire; and informing, by the system controller, the one or more user of the rate of change allowing the one or more user to address the fire in the duct- manhole system.

60. A method of estimating a size of a manhole event occurring in a selected manhole vault within a network of manhole vaults that are interconnected by connections, the method comprising:

obtaining, by a system controller, an exhaust temperature, an exhaust mass, and an exhaust heat capacity for an exhaust flow, the exhaust flow exiting the selected manhole vault;

obtaining, by the system controller, a fresh air temperature, a fresh air mass, and a fresh air heat capacity for a fresh air flow, the fresh air flow entering the selected manhole vault from an external atmosphere;

determining, by the system controller, an event start time;

obtaining, by the system controller, an anticipated base energy based on past base energy values, the event start time, and a current time;

determining, by the system controller, an actual base energy at the current time based on the exhaust temperature, the exhaust mass, the exhaust heat capacity, the fresh air temperature, the fresh air mass, and the fresh air heat capacity;

calculating, by the system controller, a difference between the actual base energy and the anticipated base energy at the current time;

estimating, by the system controller, the size of the manhole event based on said difference; and

performing, by the system controller, an action based at least in part on the size of the manhole event, the action including at least one of notifying one or more users or altering a turnover rate of atmospheric turnover in the selected manhole vault.

61. The method of clause 60, wherein the exhaust temperature, the exhaust mass, and the exhaust heat capacity are first values that are determined by the system controller deterministically, the fresh air temperature, the fresh air mass, and the fresh air heat capacity are second values that are determined by the system controller deterministically,

the first and second values are deterministic inputs; and determining the actual base energy at the current time comprises creating, by the system controller, probabilistic inputs based on the

deterministic inputs, and performing, by the system controller, a probabilistic analysis on the probabilistic inputs to obtain a probabilistic output, the probabilistic output being the actual base energy at the current time

62. The method of clause 61 , wherein the probabilistic analysis is a Monte Carlo analysis.

63. The method of any of clauses 60-62, wherein determining the actual base energy at the current time comprises:

multiplying the exhaust temperature, the exhaust mass, and the exhaust heat capacity to obtain an exhaust product;

multiplying the fresh air temperature, the fresh air mass, and the fresh air heat capacity to obtain a fresh air product; and

subtracting the fresh air product from the exhaust product.

64. The method of any of clauses 60-63, wherein estimating the size of the manhole event produces an energy balance size estimate, and the method further comprises:

obtaining, by the system controller, a first mass flow rate for each of a plurality of gaseous components present in the exhaust flow;

obtaining, by the system controller, a second mass flow rate for each of the plurality of gaseous components present in the fresh air flow;

obtaining, by the system controller, a third mass flow rate for each of the plurality of gaseous components present in a event flow, the event flow originating from the manhole event, the third mass flow rate for each of a portion of the plurality of gaseous components being determined by subtracting the second mass flow rate obtained for the gaseous component from the first mass flow rate obtained for the gaseous component; obtaining a component mass balance size estimate by estimating, with the system controller, the size of the manhole event based on the third mass flow rate obtained for at least one of the plurality of gaseous components; and

generating, by the system controller, a combined size estimate based on the energy balance size estimate and the component mass balance size estimate.

65 The method of any of clauses 60-64, wherein estimating the size of the manhole event produces an energy balance size estimate, and the method further comprises:

obtaining, by the system controller, first values comprising a first mass flow rate for each of a plurality of gaseous components present in the exhaust flow, each of the first values being determined by the system controller deterministically;

obtaining, by the system controller, second values comprising a second mass flow rate for each of the plurality of gaseous components present in the fresh air flow, each of the second values being determined by the system controller deterministically;

obtaining, by the system controller, third values comprising a third mass flow rate for each of the plurality of gaseous components present in an event flow, the event flow originating from the manhole event, each of the third values being determined by the system controller deterministically, the first, second, and third values being first deterministic inputs;

creating, by the system controller, at least one probabilistic input based on at least one of the first deterministic inputs;

performing, by the system controller, a first probabilistic analysis on the at least one probabilistic input to obtain thereby a probabilistic estimate of fire size, the probabilistic estimate of fire size being a component mass balance size estimate; and

generating, by the system controller, a combined size estimate based on the energy balance size estimate and the component mass balance size estimate, wherein the exhaust temperature, the exhaust mass, and the exhaust heat capacity are fourth values that are determined by the system controller deterministically,

the fresh air temperature, the fresh air mass, and the fresh air heat capacity are fifth values that are determined by the system controller deterministically,

the fourth and fifth values are second deterministic inputs, and determining the actual base energy at the current time comprises creating, by the system controller, second probabilistic inputs based on the second deterministic inputs, and performing, by the system controller, a second probabilistic analysis on the second probabilistic inputs to obtain a second probabilistic output, the second probabilistic output being the actual base energy at the current time.

66. A method comprising:

estimating, by a system controller, relative contributions of at least two of oxidative decomposition, pyrolysis, and plasmatization to a fire occurring in a duct-manhole system; and

performing, by the system controller, an action based at least in part on the estimated relative contributions, the action including at least one of notifying one or more users, or altering a rate of atmospheric turnover in the duct-manhole system.

67. The method of clause 66, further comprising: determining, by a system controller, a phase of the fire based at least in part on the relative contributions; and

informing, by the system controller, the one or more user of the phase of the fire.

68. The method of clause 67, further comprising: determining, by the system controller, a rate of change of the fire; informing, by the system controller, the one or more user of the rate of change allowing the one or more user to address the fire in the duct- manhole system.

69. A method to estimate a size of a manhole event occurring in a network of manhole vaults interconnected by connections, the method comprising:

obtaining, by a system controller, a first mass flow rate for each of a plurality of gaseous components present in an exhaust flow, the exhaust flow exiting a selected one of the manhole vaults;

obtaining, by the system controller, a second mass flow rate for each of the plurality of gaseous components present in a fresh air flow, the fresh air flow entering the selected manhole vault from an external atmosphere;

obtaining, by the system controller, a third mass flow rate for each of the plurality of gaseous components present in an event flow, the event flow originating from the manhole event, the third mass flow rate for each of a portion of the plurality of gaseous components being determined by subtracting the second mass flow rate obtained for the gaseous component from the first mass flow rate obtained for the gaseous component;

estimating, by the system controller, the size of the manhole event based on the third mass flow rate obtained for at least one of the plurality of gaseous components; and

performing, by the system controller, an action based at least in part on the size of the manhole event, the action including at least one of notifying a user or altering a turnover rate of atmospheric turnover in the selected manhole vault.

70. The method of clause 69, wherein estimating the size of the manhole event comprises the system controller using chemical reaction stoichiometry to calculate a burn rate of a flammable gas accumulation.

71. The method of clause 69 or 70, wherein the system controller notifies the user when the size of the manhole event exceeds a threshold value. 72. The method of any of clauses 69-71 , wherein the plurality of gaseous components comprises carbon dioxide, and the method further comprises:

receiving, by the system controller, a concentration measurement for the carbon dioxide from a sensor, and

extrapolating, by the system controller, the concentration measurement to obtain a plateau value, the size of the manhole event being estimated by the system controller based on the plateau value.

73. The method of any of clauses 69-72, wherein the manhole event comprises at least one of oxidative decomposition, pyrolysis,

plasmatization, and flammable gas accumulation.

74. The method of any of clauses 69-73, wherein obtaining the first mass flow rate for each of a portion of the plurality of gaseous components comprises receiving, by the system controller, a concentration measurement for the gaseous component from at least one analyte sensor.

75. The method of any of clauses 69-74, wherein the plurality of gaseous components comprise a product of at least one of oxidative decomposition, pyrolysis, plasmatization, and flammable gas accumulation.

76. The method of any of clauses 69-75, wherein the plurality of gaseous components comprise a product of a flammable gas accumulation, and

the flammable gas accumulation has a source comprising at least one of oxidative decomposition, pyrolysis, plasmatization, a natural gas leak, a hydrocarbon plume, a hydrogen sulfide plume, VOCs of a man-made origin, and VOCs resulting from biological decomposition of organic matter.

77. The method of any of clauses 69-76, wherein the plurality of gaseous components comprises at least one of CO, CO2, H2, NO, NO2, VOCs, H2S, C, particulates, and O3. 78. The method of any of clauses 69-77, further comprising: estimating, by the system controller, a burn rate or a flammable gas accumulation rate based on the third mass flow rate obtained for each of a portion of the plurality of gaseous components and a molecular weight of a fuel 79. The method of clause 78, further comprising: determining, by the system controller, whether the manhole event is a nuisance or a serious event based on the burn rate.

80. The method of clause 79, wherein the serious event includes at least one of oxidative decomposition, pyrolysis, plasmatization, and flammable gas accumulation.

81. The method of any of clauses 69-80, further comprising: calculating, by the system controller, a percentage lower explosive limit of flammable gases present; and

increasing, by the system controller, the turnover rate of the atmospheric turnover in the selected manhole vault based at least In part on the percentage lower explosive limit of the flammable gases present.

82. The method of clause 81 , wherein the percentage lower explosive limit of the flammable gases present is a percentage corrected lower explosive limit of the flammable gases present. 83. The method of any of clauses 69-82, further comprising: calculating, by the system controller, a percentage lower explosive limit of flammable gases present; and

displaying, by the system controller, the percentage lower explosive limit. 84. The method of clause 83, wherein the percentage lower explosive limit of the flammable gases present is a percentage corrected lower explosive limit of the flammable gases present. 85. The method of any of clauses 69-84, wherein the first mass flow rate obtained for each of the plurality of gaseous components of the exhaust flow are first values that are determined by the system controller deterministically,

the second mass flow rate obtained for each of the plurality of gaseous components of the fresh air flow are second values that are

determined by the system controller deterministically,

the third mass flow rate obtained for each of the plurality of gaseous components of the event flow are third values that are determined by the system controller deterministically,

the first, second, and third values are deterministic inputs; and the method further comprises creating, by the system controller, at least one probabilistic input based on at least one of the deterministic inputs, and performing, by the system controller, a Monte Carlo analysis on the at least one probabilistic input to obtain thereby a probabilistic estimate of fire size and a probabilistic estimate of a percentage lower explosive limit.

86. The method of clause 85, wherein the percentage lower explosive limit is a percentage corrected lower explosive limit.

87. The method of clause 85 or 86, wherein the system controller obtains a portion of the deterministic inputs from a plurality of analyte sensors.

88. The method of clause 87, wherein the plurality of analyte sensors each detect at least one of CO, CO2, H2, NO, NO2, VOCs, H2S, C, particulates, and O3. 89. The method of clause 87 or 88, wherein the plurality of analyte sensors each detect a product of at least one of oxidative

decomposition, pyrolysis, plasmatization, and flammable gas accumulation.

90. The method of any of clauses 87-89, wherein the plurality of analyte sensors each detect a product of flammable gas accumulation having a source comprising at least one of oxidative decomposition, pyrolysis, piasmatization, natural gas leaks, hydrocarbon plumes, hydrogen sulfide plumes, other VOCs of man-made origin, and other VOCs resulting from biological decomposition of organic matter.

91. The method of any of clauses 69-90, further comprising: estimating, by the system controller, quotients of unit masses of gases introduced and unit time of at least two of oxidative decomposition, pyrolysis, piasmatization, and flammable gas accumulation based on the third mass flow rate obtained for each of the plurality of gaseous components of the event flow. 92. The method of clause 91 , further comprising: distinguishing, by the system controller, between at least two of oxidative decomposition, pyrolysis, piasmatization, and flammable gas accumulation based on the quotients of the unit masses of gases introduced and time.

93 The method of clause 92, wherein the first mass flow rate obtained for each of the plurality of gaseous components of the exhaust flow are first values that are determined by the system controller deterministically, the second mass flow rate obtained for each of the plurality of gaseous components of the fresh air flow are second values that are determined by the system controller deterministically,

the third mass flow rate obtained for each of the plurality of gaseous components of the event flow are third values that are determined by the system controller deterministically, and

the method further comprises:

determining, by the system controller, a temperature change for the event flow, the temperature change, the first values, the second values, and the third values being deterministic inputs;

creating, by the system controller, first probabilistic estimates for the deterministic inputs; performing, by the system controller, a Monte Carlo analysis on the first probabilistic estimates to obtain second probabilistic estimates of the quotients of the unit masses of gases introduced; and

displaying, by the system controller, the second

probabilistic estimates.

94. A method comprising:

obtaining a sensor reading from a sensor installed inside an underground vault;

determining whether the sensor reading is indicative of an alarm state;

when the sensor reading is indicative of the alarm state, obtaining multiple confirmatory measurements and determining whether the sensor reading includes sensor drift based at least in part on the multiple confirmatory measurements;

establishing the alarm state when the sensor reading is determined not to include sensor drift; and

removing the sensor drift when the sensor reading is determined to include sensor drift.

95. The method of clause 94, wherein the confirmation measurements are obtained from the sensor

96. The method of clause 94 or 95, wherein the confirmation measurements are obtained from at least one corroborating sensor installed inside the underground vault or in at least one adjacent underground vault, the at least one corroborating sensor being different from the sensor.

97. The method of any of clauses 94-96, further comprising: notifying a user that the alarm state has been established.

98. A method comprising:

obtaining a sensor reading from a sensor installed inside an underground vault; determining whether the sensor reading is indicative of an alarm state;

when the sensor reading is indicative of the alarm state, obtaining at least one new reading from at least one corroborating sensor and

determining whether the sensor reading includes sensor drift based at least in part on the at least one new reading;

establishing the alarm state when the sensor reading is

determined not to include sensor drift; and

removing the sensor drift when the sensor reading is determined to include sensor drift.

99. The method of clause 98, further comprising: notifying a user that the alarm state has been established.

100. A method comprising:

obtaining a sensor reading from a sensor installed inside an underground vault;

determining whether the sensor reading is indicative of an alarm state;

if the sensor reading is indicative of the alarm state, triggering variable active dilution inside the underground vault, obtaining at least one new sensor reading after triggering the variable active dilution, and determining whether the sensor reading includes sensor drift based at least in pari on the at least one new sensor reading;

establishing the alarm state when the sensor reading is

determined not to include sensor drift; and

removing the sensor drift when the sensor reading is determined to include sensor drift.

101. The method of clause 100, wherein the variable active dilution is dilution of a first type.

102. The method of clause 100 or 101 , wherein the variable active dilution is dilution of a second type. 103. The method of any of clauses 100-102, further comprising: notifying a user that the alarm state has been established.

104. A system comprising:

a sensor installed inside an underground vault; and a system controller comprising at least one processor connected to memory storing instructions executable by the at least one processor, the instructions, when executed by the at least one processor, causing the at least one processor to:

obtain a sensor reading from the sensor;

determine whether the sensor reading is indicative of an alarm state;

when the sensor reading Is indicative of the alarm state, obtain at least one new sensor reading and determine whether the sensor reading includes sensor drift based at least in part on the at least one new sensor reading;

establish the alarm state when the sensor reading is determined not to include sensor drift; and

remove the sensor drift when the sensor reading is determined to include sensor drift.

105. The system of clause 104, wherein the at least one new sensor reading comprises one or more confirmation measurements obtained from the sensor.

106. The system of clause 104 or 105, further comprising:

at least one corroborating sensor installed inside the underground vault or in at least one adjacent underground vault, the at least one

corroborating sensor being different from the sensor, the at least one new sensor reading comprising one or more confirmation measurements obtained from the at least one corroborating sensor.

107. The system of any of clauses 104-106, wherein when the sensor reading is indicative of the alarm state, the instructions, when executed by the at least one processor, cause the at least one processor to trigger variable active dilution inside the underground vault before obtaining the at least one new sensor reading.

108. The system of clause 107, wherein the variable active dilution is dilution of a first type.

109. The system of clause 107 or 108, wherein the variable active dilution is dilution of a second type.

110. The system of any of clauses 104-109, wherein the instructions, when executed by the at least one processor, cause the at least one processor to notify a user that the alarm state has been established

111. The system of any of clauses 104-110, wherein the instructions, when executed by the at least one processor, cause the at least one processor to display a notification, on a display device, indicating the alarm state has been established.

112. The system of any of clauses 104-111 , wherein the instructions, when executed by the at least one processor, cause the at least one processor to instruct an air moving device installed inside the underground vault to change an airflow rate after the alarm state has been established.

113. The system of clause 112, wherein the airflow rate is increased after the alarm state has been established to increase thereby a turnover rate of an atmosphere inside the underground vault.

The foregoing described embodiments depict different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are merely exemplary, and that in fact many other architectures can be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively“associated” such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as“associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being“operably connected,” or“operably coupled,” to each other to achieve the desired functionality.

While particular embodiments of the present invention have been shown and described, it will be obvious to those skilled in the art that, based upon the teachings herein, changes and modifications may be made without departing from this invention and its broader aspects and, therefore, the appended claims are to encompass within their scope ail such changes and modifications as are within the true spirit and scope of this invention.

Furthermore, it is to be understood that the invention is solely defined by the appended claims. It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as“open” terms (e.g., the term “including” should be interpreted as“including but not limited to,” the term “having” should be interpreted as“having at least,” the term“includes" should be interpreted as“includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases“at least one” and“one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles“a” or“an” limits any particular claim containing such introduced claim recitation to inventions containing only one such recitation, even when the same claim includes the introductory phrases“one or more" or“at least one” and indefinite articles such as“a” or“an” (e.g.,“a” and/or“an” should typically be interpreted to mean“at least one” or“one or more”); the same holds true for the use of definite articles used to introduce claim recitations !n addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be

interpreted to mean at least the recited number (e.g., the bare recitation of“two recitations,” without other modifiers, typically means at least t wo recitations, or two or more recitations).

Conjunctive language, such as phrases of the form“at least one of A, B, and C,” or“at least one of A, B and C,” (i.e., the same phrase with or without the Oxford comma) unless specifically stated otherwise or otherwise clearly contradicted by context, is otherwise understood with the context as used in general to present that an item, term, etc , may be either A or B or C, any nonempty subset of the set of A and B and C, or any set not contradicted by context or otherwise excluded that contains at least one A, at least one B, or at least one C. For instance, in the illustrative example of a set having three members, the conjunctive phrases“at least one of A, B, and C” and“at least one of A, B and C” refer to any of the following sets: {A}, {B}, {C}, {A, B}, {A, C}, {B, C}, {A, B, C}, and, if not contradicted explicitly or by context, any set having {A}, {B}, and/or {C} as a subset (e.g., sets with multiple“A”). Thus, such conjunctive language is not generally intended to imply that certain

embodiments require at least one of A, at least one of B, and at least one of C each to be present. Similarly, phrases such as“at least one of A, B, or C” and “at least one of A, B or C" refer to the same as“at least one of A, B, and C” and “at least one of A, B and C” refer to any of the following sets: {A}, {B}, {C}, {A, B}, {A, C}, {B, C}, {A, B, C}, unless differing meaning is explicitly stated or clear from context.

Accordingly, the invention is not limited except as by the appended claims.