CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is a PCT application claiming priority from UK Patent Application No. GB 1519081.2, filed 28 October 2015, which is hereby incorporated in its entirety by reference.

FIELD OF THE INVENTION

[0002] The present invention relates to building sustainability generally and to a system and method to minimize lifetime energy requirements in single and multi-story structures in particular.

BACKGROUND OF THE INVENTION

[0003] Life Cycle Assessment (LCA) is rapidly becoming a tool for improving sustainability in the building industry. It allows building designers to reduce the environmental impact of the buildings they design by analyzing the environmentally impacting inputs (material and energy resources) and outputs (emissions and wastes to the environment) required for each stage of the building's life. These stages may include (a) materials manufacturing, (b) construction, (c) use and maintenance, and (d) end of life. The "AIA GUIDE TO BUILDING LIFE CYCLE ASSESSMENT IN PRACTICE", published by The American Institute of Architects in 2010, provides "guidelines to help architects understand and use LCA methodology as part of the design process by identifying scenarios for the use of LCA in the design process and providing a set of proposed guidelines for the conductance of whole building LCA". [0004] One important aspect of LCA is energy analysis, which generally takes into consideration most, if not all, energy inputs during the life cycle of a building. These energy inputs may include not only the energy use of the building while in operation (use and maintenance stage), but also the energy required to produce the materials used during the construction and to transport the materials to the building site, as well as the energy consumed during the construction itself. These energy inputs are generally referred to in the art as "operational energy" (OE) and "embodied energy" (EE), respectively. The analysis may also take into consideration the energy used during the end of life stage (e.g. demolition and material removal and disposal).

[0005] Despite the advantages offered by conducting a LCA analysis, designers are frequently faced with given conditions which may influence the efficacy of conducting the analysis. For example, they may design the buildings using materials which are readily available in the vicinity of the construction site, and then determine an energy profile of the building once it is designed. Based on the energy profile of the designed building, the designers then select HVAC (heating, ventilation, air conditioning) equipment based on the energy profile.

[0006] In an attempt to solve the problem of determining the energy profile of a building once it is designed, US Patent Application Publication US 2013/0144546A1 to Brackney et al. discloses " A building energy analysis system includes a building component library configured to store a plurality of building components, a modeling tool configured to access the building component library and create a building model of a building under analysis using building spatial data and using selected building components of the plurality of building components stored in the building component library, a building analysis engine configured to operate the building model and generate a baseline energy model of the building under analysis and further configured to apply one or more energy conservation measures to the baseline energy model in order to generate one or more corresponding optimized energy models, and a recommendation tool configured to assess the one or more optimized energy models against the baseline energy model and generate recommendations for substitute building components or modifications".

SUMMARY OF THE PRESENT INVENTION

[0007] The wall profile generator of the present invention implements an LCA optimization model based on an objective function to determine optimal wall cross sections for structures by identifying the "best" options within a larger number of possible wall cross-sectional configurations, and by concurrently analyzing all influencing design variables. The wall profile generator may use as input structure properties such as orientation, location, openings type, external color and roughness, type of structure, among other structure properties, and may iteratively evaluate the structure's performance and interactively provide the cross-section optimal compositions of the walls as output. These wall cross-section compositions may include parameters such as, for example, thickness, specific heat, and density of insulation, and of other thermal mass components. The wall profile generator, in some embodiments, may be used to determine optimal cross sections for slabs, including floors and ceilings. It may additionally be used to determine optional cross-sections for walls and/or slabs in one or more sections within a structure, for example, for walls, floors and/or ceilings of one or more rooms within the structure.

[0008] The wall profile generator may include a multidisciplinary optimization framework which may include several simulation tools for evaluating performance of the alternatives. The simulation tools may include specially designed tools or existing tools, and may use "Process Integration" to combine and interconnect CAE/CAD (Computer Aided Engineering/Computer Aided Design) tools and/or architectural design systems in a computing environment which may manage required data flow and which may iterate the process for sampling a relevant multi-dimensional search space. The optimization process may be carried out in sequential steps, each step adding or changing parameters or components related to the wall cross-section composition. Based on a defined design optimization problem and on the components of the objective function, the wall profile generator may include several analysis tools to carry out Embodied Energy (EE) calculations, Operational Energy (OE) analyses, and Total Life Cycle Energy Assessment (LCEA). The generator may build automatic chains that may control several application programs and scripting. It may be a Graphic User Interface (GUI)-driven tool, and may be Cloud based. The generator may provide a single-objective optimization environment, and may couple computational tools such as finite element analysis, thermal analysis, embodied energy analysis, mathematical optimization analysis, and LCA analysis. It may encompass the different programs, and may perform the optimization by systematically modifying the values assigned to input variables, running the analysis programs for performance evaluation, calculating and aggregating outputs, and then analyzing and reporting the results as objectives of the design problem.

[0009] There is provided, in accordance with an embodiment of the present invention, a wall profile generator for determining thermal properties for one or more walls in a structure, the wall profile generator includes a simulation model generator to convert data associated with the structure into fixed numerical values usable for generating coefficients for an optimization algorithm, a simulation engine to generate the coefficients, and an optimization module to iteratively execute the optimization algorithm for varying thermal properties of one or more walls in the structure and to determine a minimum energy cost function for the structure from the iterative executions.

[0010] There is provided, in accordance with an embodiment of the present invention, a method for reducing lifetime energy requirements in a structure, the method includes converting data associated with the structure into fixed numerical values usable for generating coefficients for an optimization algorithm, generating the coefficients, and iteratively executing the optimization algorithm using the coefficients for varying thermal properties of one or more walls in the structure, and determining a minimum energy cost function for the structure from the iterative executions.

[0011] There is provided, in accordance with an embodiment of the present invention, a method for determining thermal properties for one or more walls in a structure, the method includes the steps of: (a) determining an operational energy and an embodied energy of the structure, wherein thermal properties of the one or more walls are energy inputs used for the determining; (b) computing an energy cost function associated with the operational energy and the embodied energy; (c) iteratively computing the energy cost function for varying thermal properties of the one or more walls in the structure; and (d) determining a minimum energy cost function the iterative computations.

[0012] In accordance with an embodiment of the present invention, the coefficients are associated with an operational energy of the structure.

[0013] In accordance with an embodiment of the present invention, the coefficients are associated with an embodied energy of the structure.

[0014] In accordance with an embodiment of the present invention, the optimization algorithm includes a single-objective constrained algorithm.

[0015] In accordance with an embodiment of the present invention, the thermal properties for the one or more walls are continuous variables in the optimization algorithm.

[0016] In accordance with an embodiment of the present invention, the structure includes a building.

[0017] In accordance with an embodiment of the present invention, the wall profile generator includes an output generator to output the minimum cost function.

[0018] In accordance with an embodiment of the present invention, the simulation engine includes a life cycle assessment simulator to calculate an energy cost function by combining an operational energy component and an embodied energy component associated with the structure.

[0019] In accordance with an embodiment of the present invention, the wall profile generator additionally includes an operational energy simulator to calculate an operational energy associated with the structure, an embodied energy simulator to calculate an embodied energy associated with the structure, and an internal energy simulator to calculate the operational energy component and the embodied energy component based on the calculated operational energy and the embodied energy.

[0020] In accordance with an embodiment of the present invention, the energy cost function includes an objective function.

[0021] In accordance with an embodiment of the present invention, the method includes inputting continuous variables and discrete variables.

[0022] In accordance with an embodiment of the present invention, the method includes varying one or more of the continuous variables during each iteration.

[0023] In accordance with an embodiment of the present invention, the method includes maintaining constant the discrete variables for all iterations.

BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference to the following detailed description when read with the accompanying drawings in which:

[0025] Figure 1 schematically illustrates an exemplary functional block diagram of a wall profile generator for single and multi- story structures, according to an embodiment of the present invention;

[0026] Figure 2 schematically illustrates an exemplary structure designed using the wall profile generator, according to an embodiment of the present invention;

[0027] Figure 3 is a flow graph of a method of generating wall profiles for a structure, according to an embodiment of the present invention; and

[0028] Figure 4 schematically illustrates varying configurations of computerized systems including the wall profile generator, according to an embodiment of the present invention.

[0029] It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements. DETAILED DESCRIPTION OF THE PRESENT INVENTION

[0030] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present invention.

[0031] Applicant has realized that the lifetime energy requirements of a single-story and multi-story structure may be optimized by tailoring the profile of the walls, including wall insulation and mass materials thickness, based on a number of parameters such as their location in the envelope structure, their expected use, and surrounding environmental conditions, with each wall potentially having a different profile. The walls may include the exterior walls, but may also include the interior walls. For example, the lifetime energy requirements of a house in a northern country having an exterior north wall facing a lake and an exterior west wall facing an adjacent building may be optimized by tailoring the profile of each wall taking into consideration that the north wall may be colder than the west wall during the winter.

[0032] Applicant has further realized that the optimization may be performed during the design phase of a structure by using a wall profile generator which may compute an energy cost function associated with the lifetime energy requirement of the structure for different wall profiles. Determination of the energy cost function may take into consideration both the embodied energy and the operational energy of the structure. During an optimization process, the wall profile generator, which may include a Graphic-User Interface (GUI), may systematically modify values assigned design variables, including to the different wall profiles, and may run performance evaluations and make calculations based on the design variables to compute a number of energy cost functions. The wall profile generator may additionally analyze the calculated energy cost functions to determine which of the different wall profiles yields the minimum lifetime energy needs while satisfying thermal design requirements.

[0033] It may be appreciated by the skilled person in the art that, although the profile generator is described herein with reference to a wall profile generator, in some embodiments, it may be used to determine optimal cross sections for slabs, including floors and ceilings. It may also be appreciated that the profile generator may also be used to determine optional cross- sections for walls and/or slabs in one or more sections within a structure, for example, for walls, floors and/or ceilings of one or more rooms within the structure, and which may additionally include one or more apartments or one or more rooms within an apartment, or common areas within a structure.

[0034] Reference is now made to Figure 1 which schematically illustrates a wall profile generator 100, according to an embodiment of the present invention. Wall profile generator 100 may include an optimizer module 102, a simulation engine 105, a pre-processor module 104, and a converter module 114.

[0035] Optimizer module 102 may compute an energy cost function for the structure using an optimization algorithm which may be directed to reducing the lifetime energy requirement of the structure. The optimization algorithm may additionally be directed to minimizing operational energy in the structure and its users. The optimization algorithm may be a single- objective constrained optimization algorithm which may be described by the following equation:

where CLCE is the cost energy function and represents cumulative life-cycle energy consumption, X is a vector of possible design variables, and EE and OE are respectively the embodied energy and operational energy of the entire building for variable X. Qm is the quantity (or mass) of material m in m ³ , EECm is the embodied energy coefficient for material m in primary energy (MJ/m ³ ), le is the life expectancy of the building in years, af is the efficiency of production and delivery of fuel f (the fugitive energy coefficient associated with MJconsumer/MJprimary) which converts energy consumed from the specific source (e.g. electricity) into primary energy. OECf is the annual energy consumption of fuel f in MJ for the operation of the building due to heating and cooling, any may be obtained from thermal simulation. COPf is the coefficient of performance, the energy-efficiency measurement of heating, cooling, and refrigeration appliances, which is the ratio of useful energy output (heating or cooling) to the amount of energy that is input. A higher COP indicates a more efficient device, and it depends on the fuel utilized.

[0036] Optimizer module 102 may calculate the energy cost function by evaluating the performance of alternative wall profiles for one or more walls in the structure based on a number of design variables. These design variables may include continuous variables, discrete variables, and constant parameters.

[0037] Continuous variables may include one or more parameters which may be varied by optimizer module 102 during iterative optimization runs to compute the cost energy function associated with the minimum lifetime energy requirement. An example of a continuous variable may be wall insulation material thicknesses, which during each optimization run (e.g. iteration), optimizer module 102 may select a different thickness to determine the energy cost function for each particular thickness. Other examples of continuous variables may be wall insulation material properties (type of material) and wall insulation material composition, so that optimizer module may select different types of insulation materials or use different compositions during one or more optimization runs. The continuous variables may be automatically selected by optimizer module 102 from a database wherein may be stored all the continuous variables. Selection of the continuous variables by optimization module may not be limited to only one variable or only one parameter being varied during each optimization run, rather, the optimization module may select multiple variables and vary multiple parameters during one or more optimization runs.

[0038] Discrete variables may include parameters which may be input by a user or selected from a database and remain constant during the iterative optimization runs performed by optimizer module 102. The discrete variables may include parameters associated with the structure and which are not modifiable, for example, the geographical location of the structure, type of structure (high rise building, single story house, residential, commercial, industrial, etc.), layout of the structure, the design of the structure, and structure orientation.

[0039] Constant parameters may include those parameters which are neither continuous variables nor discrete variables and which may be considered default data. Examples of this type of parameter may be layout of the building, heating and cooling devices, primary and consumer energy devices, and set point temperatures.

[0040] The optimization algorithm may be bound by constraints which may limit the maximum and minimum values of the continuous variables which may be selected by optimizer module 102. For example, the allowable domain for each parameter may be represented by maximum and minimum thicknesses for each layer of wall material, such as insulation. A linear equality constraint may then be set as the total thickness of variable layers of wall insulation material, described by the equation∑ (X) = Wth, where Wth is the wall material thickness. Indirect functional constraints may also be taken into consideration in the optimization algorithm, such as building regulations which may include code requirements for minimum wall insulation properties for providing minimal thermal comfort. [0041] Optimization module 102 may include dedicated software specifically developed to apply the optimization algorithm and solve the optimization problem. Additionally or alternatively, optimization module 102 may include use of commercially known software suitable for determining a minimum in non-linear multivariate constrained problems. An example of such commercially available software may include, for example, "fmincon", which is associated with the Optimization Toolbox of MATLAB. "fmincon" may use a sequential quadratic programming method and may require the selection of a starting point, which may be defined as the maximum bounds values of the continuous variables.

[0042] Simulation engine 105 may be used to compute values for the objective function components in the optimization algorithm according to specific values of the design variables provided by optimizer module 102. These objective function component values may then be used by optimization module 102 to compute the value of the energy cost function CLCE and to determine if a minimum CLCE value has been achieved.

[0043] Simulation engine 105 may include dedicated software specifically developed to determine the value of the objective function and/or commercially known software suitable for determining the values. Simulation engine 105 may include one or more simulators for performing this task, for example, a life cycle assessment (LCA) simulator 106, an operational energy (OE) simulator 108, an embodied energy (EE) simulator 110, and internal energy (IE) simulator 112. LCA simulator 106 may determine the value of CLCE for each iteration; OE simulator 108 may determine the value of OECf, EE simulator 110 may determine the value of EECm, and IE simulator 112 may perform the summation actions (∑) for each component and may determine the values of the variables Qm, le, af, and COPf.

[0044] Preprocessor module 104 may include a simulation model generator and may translate discrete variable data and constant parameter data input to wall profile generator 100 into specific values required by the optimization algorithm for determining a minimum CLCE. Preprocessor module 104 may additionally take into consideration in generating the specific values the continuous variables from optimizer module 102 and/or the functional constraints.

[0045] Converter module 114 may output the results of the optimization process and may include the wall material parameters WP which yield a minimum CLCE value (minimum lifetime energy requirement of the structure) as determined by optimizer module 102. WP may be associated with the continuous variables selected by optimizer module 102. For example, shown in Figure 2 is an exemplary structure 200 including a wall Wl having a wall profile including a first set of wall material parameters PI, and a second wall W2 having a wall profile including a second set of wall material parameters P2 different from PI, the profiles of each wall Wl and W2 generated using wall profile generator 100.

[0046] Reference is now made to Figure 3 which is a flow graph of a method of generating wall profiles for a structure using wall profile generator 100, according to an embodiment of the present invention. The skilled person in the art may appreciate that the sequence and/or number of steps shown in the flow graph are for exemplary purposes, and that the method may be implemented with a different sequence of steps or with more or less steps.

[0047] At 300, a user may input discrete variables data and constant parameters data through a GUI and/or may download a portion or all of the data from a storage medium onto a computing device on which the wall profile generator 100 is run. The storage medium may be connected locally to the computing device or may be connected over a server. Data associated with the continuous variables may have been previously downloaded to a database in the computing device or connected storage medium, or may be server downloaded and stored in the device and/or a separate storage medium. [0048] At 302, pre-processor module 104 may convert the discrete variable data and the constant parameters into specific values which are to be used during the optimization process and remain constant (values do not vary during the optimization process).

[0049] At 304, optimization module 102 selects a set of values associated with a set of continuous variables and transfers the values to simulation engine 105. Selection of the values may be dependent on functional constraints.

[0050] At 306, simulation engine 105 computes the values of the energy components based on the values determined during steps 302 and 304.

[0051] At 308, simulation engine 105 computes the energy cost function CLCE.

[0052] At 310, optimizer module 102 determines whether or not the value is of CLCE is a minimum value. If yes, the wall material parameters used in the optimization process are output through the GUI. If no, optimizer 102 selects a new set of values for the continuous variables (stored in the database), as per step 304, and steps 306 - 310 are repeated. The optimization process may iterate steps 304 - 310 as many times as necessary until a minimum is achieved within the bounds of the constraints.

[0053] Reference is now made to Figure 4 which schematically illustrates varying configurations of computerized systems 400 including the wall profile generator of Figure 1, according to an embodiment of the present invention.

[0054] In one possible configuration, wall profile generator 100 may be implemented in a server based system over the internet or over an otherwise wide area network (WAN) and may be accessed by numerous computing devices. The computing devices may include desk-top devices such as personal computers and workstations, and may also include portable devices such laptop computers, tablets, smartphones, and the like. For example, wall profile generator 100 may be implemented in a server 402 which may be accessed through WAN 404 by the one or more computing devices, for example as shown by computing devices 406A and 406B.

[0055] In a second possible configuration, wall profile generator may be implemented in a server based system over a local area network (LAN) to which the one or more computing devices may be connected. For example, wall profile generator 100 may be implemented in a server 408 which may be accessed through a LAN 407 by the one or more computing devices, for example as shown by computing devices 410A, 410B, and 410C. In an alternative configuration, server 408 may connect to WAN 404 so that wall profile generator 100 in server 402 may also be accessed by computing devices 410A, 410B, and 410C connected to server 408 through LAN 407. Additionally or alternatively, wall profile generator 100 may be implemented in server 408 and may be accessed through WAN 404 by computing devices 406A and 406B in addition to those computing devices connected through LAN 407.

[0056] In a third possible configuration, wall profile generator 100 may be implemented in a stand-alone computing device, as shown for example by computing device 412.

[0057] Unless specifically stated otherwise, as apparent from the preceding discussions, it is appreciated that, throughout the specification, discussions utilizing terms such as "processing," "computing," "calculating," "determining," or the like, refer to the action and/or processes of a computer, computing system, or similar electronic computing device that manipulates and/or transforms data represented as physical, such as electronic, quantities within the computing system's registers and/or memories into other data similarly represented as physical quantities within the computing system's memories, registers or other such information storage, transmission or display devices.

[0058] Embodiments of the present invention may include apparatus for performing the operations herein. This apparatus may be specially constructed for the desired purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but not limited to, any type of disk, including floppy disks, optical disks, magnetic-optical disks, read-only memories (ROMs), compact disc read-only memories (CD-ROMs), random access memories (RAMs), electrically programmable read-only memories (EPROMs), electrically erasable and programmable read only memories (EEPROMs), magnetic or optical cards, Flash memory, or any other type of media suitable for storing electronic instructions and capable of being coupled to a computer system bus.

[0059] The processes and displays presented herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct a more specialized apparatus to perform the desired method. The desired structure for a variety of these systems will appear from the description below. In addition, embodiments of the present invention are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the invention as described herein.

[0060] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those of ordinary skill in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.