Method and system for evaluating and optimizing house building structure

Abstract

The invention discloses a house building structure evaluation optimization method and system, and relates to the technical field of building design, and the method comprises the steps: building a finite element model of a house building, obtaining related parameters, setting the parameters in the model, and carrying out the analysis to obtain a parameter value range. On the basis of the value range, candidate values are selected according to rules, a parameter grid is constructed, and the parameter grid is divided into a preset number of sub-regions; and randomly selecting parameters from each sub-region as a reference combination, setting an optimization objective function to calculate a sub-region target value, and determining a target sub-region. And carrying out repeated grid division and reference parameter selection on the target sub-region, and gradually limiting and shrinking the range until the parameter space is smaller than a preset threshold value. And finally, determining an optimal house building parameter combination in the final target sub-region by using an optimization algorithm and a target function. The problem that in the prior art, high efficiency and accuracy cannot be taken into consideration when house building structure optimization is carried out is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of building design, and in particular to a building structure evaluation and optimization method and system. Background Art

[0002] In today's construction engineering field, structural optimization design has become a key technology to improve building performance and reduce costs. With the increasing complexity of building design and people's increasing requirements for building safety, economy and environmental protection, traditional structural optimization design methods can no longer meet current needs. Especially when faced with a large number of parameter combinations, data processing has become a huge challenge.

[0003] Structural optimization design usually involves multiple variables and complex constraints, such as structural size, material selection, layout, etc. Different combinations of these parameters will directly affect the performance of the building, including load-bearing capacity, stability, earthquake resistance, thermal performance, etc. In actual operation, designers need to repeatedly adjust and optimize these parameters to achieve the best design effect.

[0004] However, as the scale and complexity of buildings increase, the number and combination of parameters grow exponentially, resulting in an extremely large amount of data to be processed. Traditional optimization methods, such as exhaustive search, are computationally intensive and time-consuming when faced with such a large parameter space, while random search algorithms are prone to miss major parameter combinations due to their random nature. Therefore, current house structure optimization methods cannot achieve both high efficiency and accuracy. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a building structure evaluation and optimization method and system, aiming to solve the problem in the prior art that it is impossible to take into account both efficiency and accuracy when optimizing building structures.

[0006] The embodiment of the present invention is implemented as follows: A building structure evaluation and optimization method, the method comprising: Establish a finite element model of the building to be optimized, obtain building parameters related to the optimization of the building structure, set the building parameters in the finite element model and perform finite element analysis to obtain the value range of the building parameters; Selecting a candidate value of each building construction parameter from the value range of the building construction parameter according to a preset rule, and establishing a building construction parameter grid according to the Cartesian product of the candidate value of each building construction parameter; Divide the building construction parameter grid into a preset number of equal sub-areas according to a preset rule, and randomly select the building construction parameter data in one of the grids from the sub-areas as the benchmark building construction parameter combination of the sub-area; Setting a housing building structure optimization objective function, determining a target value of a sub-region according to the benchmark housing building parameter combination and the objective function, and determining a target sub-region from a preset number of sub-regions according to the target value; After the target sub-area is meshed again, the base building construction parameter combinations of the sub-areas are respectively selected to calculate the target values ​​and determine the new target sub-area, so as to narrow the range of the target sub-area until the parameter space of the target sub-area is less than the preset threshold; The final combination of building parameters is determined based on the data of the building parameters in the final target sub-area using a preset optimization algorithm and a building structure optimization objective function.

[0007] Furthermore, in the above-mentioned building structure evaluation optimization method, the step of establishing a building construction parameter grid according to the Cartesian product of the candidate values ​​of each building construction parameter comprises: Obtaining the number of sets in the Cartesian product of the candidate values ​​of each building construction parameter, and determining the number of unit grids of the building construction parameter grid according to the number of sets in the Cartesian product; Determine all possible combinations of the number of rows and the number of columns according to the number of unit grids, and determine a target combination with the smallest difference between the number of rows and the number of columns from among all possible combinations of the number of rows and the number of columns; A house building parameter combination consisting of candidate values ​​of each house building parameter is randomly filled into each unit grid to obtain a house building parameter grid.

[0008] Furthermore, in the above-mentioned building structure evaluation optimization method, the step of randomly selecting the data of building construction parameters in one of the grids from the sub-regions as the benchmark building construction parameter combination of the sub-region comprises: Randomly select a preset number of unit grids from the sub-area, and obtain the building construction parameter combination in the unit grid as the benchmark building construction parameter combination; The step of determining the target value of the sub-area according to the combination of the benchmark building construction parameters and the target function comprises: The benchmark housing construction parameter combinations are input into the objective function respectively, and the output values ​​obtained are averaged to obtain the target value of the sub-area.

[0009] Furthermore, in the above-mentioned building structure evaluation optimization method, the step of randomly selecting a preset number of unit grids from the sub-area and obtaining the building construction parameter combination in the unit grid as the benchmark building construction parameter combination includes: Determine any two non-adjacent vertices in the sub-region and obtain the connection line between the two vertices; The two vertices are the starting point and the end point respectively, and the curve formed by the preset frequency and the preset amplitude is used as the grid reference line; Determine the unit grid through which the peak point and the trough point of the grid baseline pass as the selected unit grid.

[0010] Furthermore, in the above-mentioned building structure evaluation optimization method, the step of dividing the building construction parameter grid into a preset number of equal sub-areas according to a preset rule comprises: The central grid point in the building parameter grid is obtained, and corresponding straight lines are extended in the horizontal and vertical directions with the central grid point as the origin to divide the building grid into a preset number of equal sub-areas.

[0011] Furthermore, in the above-mentioned building structure evaluation optimization method, the expression of the objective function is: ; in, α and β are weight coefficients, x is the vector of building parameters, Wk is the weighting coefficient of each group of structural components, Ck(x) It is k The cost function of the group structural components, Ak is the weighting coefficient of each group of structural components, P For the k The ratio of the actual safety factor of a group of structural components to the safety factor required by the code.

[0012] Furthermore, in the above-mentioned building structure assessment and optimization method, the building building parameters include beam and column cross-sectional dimensions, wall thickness, and steel bar anchorage length.

[0013] Another object of the present invention is to provide a building structure evaluation and optimization system, the system comprising: Establishing a module for establishing a finite element model of the house building to be optimized, obtaining house building parameters related to the optimization of the house building structure, setting the house building parameters in the finite element model and performing finite element analysis to obtain the value range of the house building parameters; A selection module, for selecting a candidate value of each building construction parameter from a value range of the building construction parameter according to a preset rule, and establishing a building construction parameter grid according to the Cartesian product of the candidate value of each building construction parameter; A division module is used to divide the housing construction parameter grid into a preset number of equal sub-areas according to a preset rule, and randomly select the data of the housing construction parameter in one of the grids from the sub-areas as the benchmark housing construction parameter combination of the sub-areas; A setting module, used to set a housing building structure optimization objective function, determine a target value of a sub-region according to the benchmark housing building parameter combination and the objective function, and determine a target sub-region from a preset number of sub-regions according to the target value; A limiting module is used to select the benchmark building parameter combination of each sub-region after meshing the target sub-region again, calculate the target value and determine a new target sub-region, so as to limit the range of the target sub-region until the parameter space of the target sub-region is less than a preset threshold; The optimization module is used to determine the final combination of building construction parameters according to the data of the building construction parameters in the final target sub-area using a preset optimization algorithm and a building construction structure optimization objective function.

[0014] Another object of the present invention is to provide a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of any one of the methods described above.

[0015] Another object of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above method when executing the program.

[0016] The present invention establishes a building parameter grid through candidate values ​​of building structure parameters, divides the parameter grid, and in the case of a large amount of parameter data, determines a target sub-region where an optimal solution may appear according to the divided sub-regions, and when the parameter space of the target sub-region is less than a preset threshold, finally searches in the target sub-region to determine the final building parameter combination, thereby ensuring both efficient search efficiency and accuracy in determining building parameters. The problem that the prior art cannot take into account both efficiency and accuracy when optimizing building structures is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a flow chart of a building structure evaluation and optimization method provided by an embodiment of the present invention; Figure 2 It is a structural block diagram of the building structure evaluation and optimization system in the third embodiment of the present invention.

[0018] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0019] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0020] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0022] The following will explain in detail how to achieve both high efficiency and accuracy when optimizing the structure of a building with reference to specific embodiments and drawings.

[0023] Embodiment 1 See also Figure 1 , which shows a building structure evaluation and optimization method in a first embodiment of the present invention, and the method includes steps S10 to S15.

[0024] Step S10, establishing a finite element model of the building to be optimized, obtaining building parameters related to the optimization of the building structure, setting the building parameters in the finite element model and performing finite element analysis to obtain the value range of the building parameters.

[0025] Among them, the finite element model of the house building to be optimized is established using ANSYS software, and the house building parameters related to the optimization of the house building structure are set in the model, such as the cross-sectional size of beams and columns, the thickness of walls, and the anchorage length of steel bars. Finite element analysis is performed in ANSYS software, such as static calculation, dynamic analysis, or fatigue analysis, to evaluate the impact of the above house building parameters on the overall house. Therefore, according to the results of the analysis and calculation, the appropriate value range of the house building parameters, that is, the feasible domain of the structural design parameters, can be determined. Step S11, selecting a candidate value of each building construction parameter from the value range of the building construction parameter according to a preset rule, and establishing a building construction parameter grid according to the Cartesian product of the candidate value of each building construction parameter.

[0026] Specifically, after determining the value range of the building construction parameters, since specific values ​​need to be determined when performing structural optimization, a preset number of specific values ​​can be selected from the range as candidate values ​​of the building construction parameters. The candidate values ​​are used for subsequent optimization calculations to determine the final values. In specific implementation, the number of candidate values ​​to be selected can be determined based on the size of the value range, and the final number of candidate values ​​can be selected within the value range at preset intervals. At the same time, after selecting the candidate value of each building construction parameter, its corresponding Cartesian product can be obtained to establish a building construction parameter grid.

[0027] The Cartesian product is a basic concept in set theory, which refers to the set of all possible ordered pairs between two or more sets. In the embodiment of the present invention, the Cartesian product of building parameters refers to the set formed by all possible combinations of taking an element from the set of candidate values ​​of each building parameter. The building parameter grid is a grid containing all combinations of building parameters.

[0028] Specifically, in some optional embodiments of the present invention, the step of establishing a building construction parameter grid according to the Cartesian product of the candidate values ​​of each building construction parameter comprises: Obtaining the number of sets in the Cartesian product of the candidate values ​​of each building construction parameter, and determining the number of unit grids of the building construction parameter grid according to the number of sets in the Cartesian product; Determine all possible combinations of the number of rows and the number of columns according to the number of unit grids, and determine a target combination with the smallest difference between the number of rows and the number of columns from among all possible combinations of the number of rows and the number of columns; A house building parameter combination consisting of candidate values ​​of each house building parameter is randomly filled into each unit grid to obtain a house building parameter grid.

[0029] Among them, the number of unit grids of the house building parameter grid is determined according to the number of sets of calculated Cartesian products (i.e., the number of all possible combinations of house building parameters). The "unit grid" here can be understood as an independent space or position used to represent each combination of house building parameters; after determining the total number of unit grids, consider how to arrange these grids in the form of a two-dimensional table. This involves determining the number of rows and columns of the table. Since the total number of grids is fixed, there are multiple combinations of rows and columns to reach this total number; among all possible combinations of rows and columns, a combination that minimizes the difference between the number of rows and columns is selected as the target combination. The purpose of this step is to create a grid layout that is as balanced as possible, avoiding excessive disparity in the number of rows or columns, so as to facilitate subsequent operations and analysis; finally, all possible combinations of house building parameters calculated previously are randomly assigned to each unit grid. In this way, each grid represents a specific parameter combination, forming a complete house building parameter grid. This grid can be used for further analysis, simulation or optimization process.

[0030] Step S12, dividing the building construction parameter grid into a preset number of equal sub-areas according to a preset rule, and randomly selecting the building construction parameter data in one of the grids from the sub-areas as a benchmark building construction parameter combination for the sub-area.

[0031] In order to reduce the parameter space and improve the efficiency of optimization search, the parameter grid is divided into multiple equal sub-areas. In each divided sub-area, a grid unit is randomly selected, and the building parameter combination in the selected grid unit is regarded as the benchmark parameter combination of the sub-area. "Benchmark parameter combination" means that in this sub-area, this set of parameters is regarded as a representative or "typical" parameter set. The random selection process ensures that the benchmark parameter combination of each sub-area has a certain degree of randomness and diversity.

[0032] Specifically, in some optional embodiments of the present invention, the step of dividing the building construction parameter grid into a preset number of equally divided sub-areas according to a preset rule comprises: The central grid point in the building parameter grid is obtained, and corresponding straight lines are extended in the horizontal and vertical directions with the central grid point as the origin to divide the building grid into a preset number of equal sub-areas.

[0033] First, it is necessary to determine the center grid point of the entire house construction parameter grid. This center grid point can be the average of the center positions of all grid cells in the grid, or a fixed point pre-calculated according to the geometry and size of the grid. Once the center point is determined, straight lines can be extended from this point in the horizontal direction (i.e., the row direction of the grid) and the vertical direction (i.e., the column direction of the grid). These straight lines cut the grid into multiple parts, each of which represents a sub-area. Generally, the house construction parameter grid is divided into four equal sub-areas.

[0034] Step S13, setting a building structure optimization objective function, determining a target value of a sub-region according to the benchmark building parameter combination and the objective function, and determining a target sub-region from a preset number of sub-regions according to the target value.

[0035] Before optimizing the building structure, we first need to clarify the optimization goal. This goal is usually one or more indicators related to the building structure performance, such as cost, strength, stability, energy consumption, etc. Specifically, the expression of the objective function is: ; in, α and β are weight coefficients, x is the vector of building parameters, Wk is the weighting coefficient of each group of structural components, Ck(x) It is k The cost function of the group structural components, Ak is the weighting coefficient of each group of structural components, P For the k The ratio of the actual safety factor of a group of structural components to the safety factor required by the code.

[0036] Furthermore, these benchmark parameter combinations are substituted into the objective function to calculate the corresponding target value. This target value reflects the performance or performance of the sub-region on the optimization target. After obtaining the target values ​​of all sub-regions, these values ​​need to be compared to determine which sub-region performs best on the optimization target, and select a sub-region that performs best on the optimization target as the target sub-region. These sub-regions contain possible optimal or suboptimal parameter combinations and are the focus of subsequent detailed analysis and optimization.

[0037] Step S14, after meshing the target sub-region again, select the benchmark building parameter combination of the sub-region respectively to calculate the target value to determine a new target sub-region, so as to limit the scope of the target sub-region until the parameter space of the target sub-region is less than a preset threshold.

[0038] Among them, after the target sub-region is determined for the first time, in order to explore the parameter space in the region more finely, it is necessary to mesh it again. The division method is the same as before. The divided grid further subdivides the target sub-region into smaller sub-regions. Each sub-region contains fewer parameter combinations, so that the subsequent parameter analysis and optimization process are more accurate and efficient. In each newly divided sub-region, one or more benchmark house building parameter combinations are selected. These combinations represent one or more representative samples of the parameter space in the sub-region. Substitute these benchmark parameter combinations into the previously set objective function to calculate the corresponding target values. These target values ​​reflect the performance or performance of each sub-region on the optimization target. In this way, one or more target values ​​can be determined for each newly divided sub-region to determine the new target sub-region. Repeat the above steps (i.e., mesh division, target value calculation, and new target sub-region determination) to continuously narrow the scope of the target sub-region until it is less than a preset threshold. This threshold is a parameter space size limit pre-set according to the optimization requirements and the complexity of the problem, and is not limited here.

[0039] Step S15, determining the final combination of building construction parameters according to the data of the building construction parameters in the final target sub-area using a preset optimization algorithm and a building construction structure optimization objective function.

[0040] After a series of iterations and optimization steps, a target sub-region with a smaller range and better parameter combination is obtained. The parameter data in this sub-region represents one or more sets of building parameters that may meet the optimization target. The preset optimization algorithm is a mathematical method for finding the optimal or approximately optimal solution in a given parameter space. In specific implementation, it can be used, including but not limited to gradient descent method, genetic algorithm, particle swarm optimization algorithm and global search algorithm.

[0041] In summary, the building structure evaluation and optimization method in the above embodiment of the present invention establishes a building parameter grid through candidate values ​​of building structure parameters, divides the parameter grid, and in the case of a large amount of parameter data, determines the target sub-region where the optimal solution may appear according to the divided sub-regions, and when the parameter space of the target sub-region is less than a preset threshold, finally searches in the target sub-region to determine the final building parameter combination, thus ensuring both efficient search efficiency and accuracy of building parameter determination. The problem of not being able to take into account both efficiency and accuracy when optimizing building structure in the prior art is solved.

[0042] Embodiment 2 This embodiment also proposes a building structure evaluation optimization method. The building structure evaluation optimization method in this embodiment is different from the building structure evaluation optimization method in the first embodiment in that: The step of randomly selecting the data of the building construction parameters in one of the grids from the sub-areas as the reference building construction parameter combination of the sub-areas comprises: Randomly select a preset number of unit grids from the sub-area, and obtain the building construction parameter combination in the unit grid as the benchmark building construction parameter combination; The step of determining the target value of the sub-area according to the combination of the benchmark building construction parameters and the target function comprises: The benchmark housing construction parameter combinations are input into the objective function respectively, and the output values ​​obtained are averaged to obtain the target value of the sub-area.

[0043] Among them, after the entire house construction parameter grid is divided into a preset number of sub-areas, a certain number of unit grids are randomly selected from each sub-area. This number is preset and can be determined based on factors such as the complexity of the optimization problem and the desired accuracy. For each sub-area, the average value of the target values ​​corresponding to all benchmark house construction parameter combinations is calculated. This average value represents the overall performance or performance of the sub-area on the optimization target. By calculating the average value, a more robust and reliable sub-area target value can be obtained.

[0044] In addition, in order to further improve the accuracy of optimization, when selecting the benchmark house building parameters, determine any two non-adjacent vertices in the sub-area and obtain the connecting line between the two vertices; take the two vertices as the starting point and the end point, and the curve formed by the preset frequency and preset amplitude as the grid baseline; determine the unit grids through which the peak points and the trough points of the grid baseline pass as the unit grids for selecting the benchmark house building parameters. Among them, the unit grids where the peak points and the trough points are located are selected as the source of the benchmark house building parameters. This is because these grid points are more likely to contain optimal or suboptimal parameter combinations because they are located at the extreme points of the curve. In this way, we can ensure that the selected benchmark parameters are not only representative, but also more likely to contain parameter combinations that have an important impact on the optimization objectives.

[0045] In summary, the building structure evaluation and optimization method in the above embodiment of the present invention establishes a building parameter grid through candidate values ​​of building structure parameters, divides the parameter grid, and in the case of a large amount of parameter data, determines the target sub-region where the optimal solution may appear according to the divided sub-regions, and when the parameter space of the target sub-region is less than a preset threshold, finally searches in the target sub-region to determine the final building parameter combination, thus ensuring both efficient search efficiency and accuracy of building parameter determination. The problem of not being able to take into account both efficiency and accuracy when optimizing building structure in the prior art is solved.

[0046] Embodiment 3 See also Figure 2 , which shows a building structure evaluation and optimization system proposed in Embodiment 3 of the present invention, and the system comprises: Establishing module 100, for establishing a finite element model of the building to be optimized, obtaining building parameters related to the optimization of the building structure, setting the building parameters in the finite element model and performing finite element analysis to obtain the value range of the building parameters; A selection module 200 is used to select a candidate value of each building construction parameter from the value range of the building construction parameter according to a preset rule, and establish a building construction parameter grid according to the Cartesian product of the candidate value of each building construction parameter; The division module 300 is used to divide the building construction parameter grid into a preset number of equal sub-regions according to a preset rule, and randomly select the data of the building construction parameter in one of the grids from the sub-regions as the benchmark building construction parameter combination of the sub-region; A setting module 400 is used to set a housing building structure optimization objective function, determine a target value of a sub-region according to the benchmark housing building parameter combination and the objective function, and determine a target sub-region from a preset number of sub-regions according to the target value; The limiting module 500 is used to select the benchmark building parameter combination of each sub-region to calculate the target value and determine a new target sub-region after meshing the target sub-region again, so as to limit the range of the target sub-region until the parameter space of the target sub-region is less than a preset threshold; The optimization module 600 is used to determine the final combination of building construction parameters according to the data of the building construction parameters in the final target sub-area by using a preset optimization algorithm and a building construction structure optimization objective function.

[0047] Furthermore, in the above-mentioned building structure evaluation and optimization system, the step of establishing a building construction parameter grid according to the Cartesian product of the candidate values ​​of each building construction parameter comprises: Obtaining the number of sets in the Cartesian product of the candidate values ​​of each building construction parameter, and determining the number of unit grids of the building construction parameter grid according to the number of sets in the Cartesian product; Determine all possible combinations of the number of rows and the number of columns according to the number of unit grids, and determine a target combination with the smallest difference between the number of rows and the number of columns from among all possible combinations of the number of rows and the number of columns; A house building parameter combination consisting of candidate values ​​of each house building parameter is randomly filled into each unit grid to obtain a house building parameter grid.

[0048] Furthermore, in the above-mentioned house building structure evaluation and optimization system, the step of randomly selecting the data of the house building parameters in one of the grids from the sub-areas as the reference house building parameter combination of the sub-area comprises: Randomly select a preset number of unit grids from the sub-area, and obtain the building construction parameter combination in the unit grid as the benchmark building construction parameter combination; The step of determining the target value of the sub-area according to the combination of the benchmark building construction parameters and the target function comprises: The benchmark housing construction parameter combinations are input into the objective function respectively, and the output values ​​obtained are averaged to obtain the target value of the sub-area.

[0049] Furthermore, in the above-mentioned house building structure evaluation and optimization system, the step of randomly selecting a preset number of unit grids from the sub-area and obtaining the house building parameter combination in the unit grid as the benchmark house building parameter combination comprises: Determine any two non-adjacent vertices in the sub-region and obtain the connection line between the two vertices; The two vertices are the starting point and the end point respectively, and the curve formed by the preset frequency and the preset amplitude is used as the grid reference line; Determine the unit grid through which the peak point and the trough point of the grid baseline pass as the selected unit grid.

[0050] Furthermore, in the above-mentioned building structure evaluation and optimization system, the step of dividing the building construction parameter grid into a preset number of equally divided sub-areas according to a preset rule comprises: The central grid point in the building parameter grid is obtained, and corresponding straight lines are extended in the horizontal and vertical directions with the central grid point as the origin to divide the building grid into a preset number of equal sub-areas.

[0051] Furthermore, in the above-mentioned building structure evaluation and optimization system, the expression of the objective function is: ; in, α andβ are weight coefficients, x is the vector of building parameters, Wk is the weighting coefficient of each group of structural components, Ck(x) It is k The cost function of the group structural components, Ak is the weighting coefficient of each group of structural components, P For the k The ratio of the actual safety factor of a group of structural components to the safety factor required by the code.

[0052] Furthermore, in the above-mentioned building structure evaluation and optimization system, the building building parameters include beam and column cross-sectional dimensions, wall thickness, and steel bar anchorage length.

[0053] The functions or operation steps implemented when the above modules are executed are substantially the same as those in the above method embodiments, and will not be repeated here.

[0054] Embodiment 4 Another aspect of the present invention further provides a readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the steps of the method described in any one of the above-mentioned embodiments 1 to 2 are implemented.

[0055] Embodiment 5 Another aspect of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the program, the steps of the method described in any one of the above-mentioned embodiments 1 to 2 are implemented.

[0056] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable storage medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable storage medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0058] More specific examples (a non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable storage medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0059] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0060] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0061] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A building structure evaluation and optimization method, characterized in that: The method comprises: Establish a finite element model of the building to be optimized, obtain building parameters related to the optimization of the building structure, set the building parameters in the finite element model and perform finite element analysis to obtain the value range of the building parameters; Selecting a candidate value of each building construction parameter from the value range of the building construction parameter according to a preset rule, and establishing a building construction parameter grid according to the Cartesian product of the candidate value of each building construction parameter; Divide the building construction parameter grid into a preset number of equal sub-areas according to a preset rule, and randomly select the building construction parameter data in one of the grids from the sub-areas as the benchmark building construction parameter combination of the sub-area; Setting a housing building structure optimization objective function, determining a target value of a sub-region according to the benchmark housing building parameter combination and the objective function, and determining a target sub-region from a preset number of sub-regions according to the target value; After the target sub-area is meshed again, the base building construction parameter combinations of the sub-areas are respectively selected to calculate the target values ​​and determine the new target sub-area, so as to narrow the range of the target sub-area until the parameter space of the target sub-area is less than the preset threshold; The final combination of building parameters is determined based on the data of the building parameters in the final target sub-area using a preset optimization algorithm and a building structure optimization objective function.

2. The building structure evaluation and optimization method according to claim 1, characterized in that: The step of establishing a building construction parameter grid according to the Cartesian product of the candidate values ​​of each building construction parameter comprises: Obtaining the number of sets in the Cartesian product of the candidate values ​​of each building construction parameter, and determining the number of unit grids of the building construction parameter grid according to the number of sets in the Cartesian product; Determine all possible combinations of the number of rows and the number of columns according to the number of unit grids, and determine a target combination with the smallest difference between the number of rows and the number of columns from among all possible combinations of the number of rows and the number of columns; A house building parameter combination consisting of candidate values ​​of each house building parameter is randomly filled into each unit grid to obtain a house building parameter grid.

3. The building structure evaluation and optimization method according to claim 2, characterized in that: The step of randomly selecting the data of the building construction parameters in one of the grids from the sub-areas as the reference building construction parameter combination of the sub-areas comprises: Randomly select a preset number of unit grids from the sub-area, and obtain the building construction parameter combination in the unit grid as the benchmark building construction parameter combination; The step of determining the target value of the sub-area according to the combination of the benchmark building construction parameters and the target function comprises: The benchmark housing construction parameter combinations are input into the objective function respectively, and the output values ​​obtained are averaged to obtain the target value of the sub-area.

4. The building structure evaluation and optimization method according to claim 3 is characterized in that: The step of randomly selecting a preset number of unit grids from the sub-areas and obtaining the building construction parameter combination in the unit grids as the benchmark building construction parameter combination comprises: Determine any two non-adjacent vertices in the sub-region and obtain the connection line between the two vertices; The two vertices are the starting point and the end point respectively, and the curve formed by the preset frequency and the preset amplitude is used as the grid reference line; Determine the unit grid through which the peak point and the trough point of the grid baseline pass as the selected unit grid.

5. The building structure evaluation and optimization method according to claim 1, characterized in that: The step of dividing the building construction parameter grid into a preset number of equally divided sub-areas according to a preset rule comprises: The central grid point in the building parameter grid is obtained, and corresponding straight lines are extended in the horizontal and vertical directions with the central grid point as the origin to divide the building grid into a preset number of equal sub-areas.

6. The building structure evaluation and optimization method according to claim 1, characterized in that: The expression of the objective function is: ； in, α and β are weight coefficients, x is the vector of building parameters, Wk is the weighting coefficient of each group of structural components, Ck(x) It is k The cost function of the group structural components, Ak is the weighting coefficient of each group of structural components, P For the k The ratio of the actual safety factor of a group of structural components to the safety factor required by the code.

7. The building structure evaluation and optimization method according to any one of claims 1 to 6, characterized in that: The building construction parameters include beam and column cross-sectional dimensions, wall thickness, and steel bar anchorage length.

8. A building structure evaluation and optimization system, characterized in that: The system comprises: Establishing a module for establishing a finite element model of the house building to be optimized, obtaining house building parameters related to the optimization of the house building structure, setting the house building parameters in the finite element model and performing finite element analysis to obtain the value range of the house building parameters; A selection module, for selecting a candidate value of each building construction parameter from a value range of the building construction parameter according to a preset rule, and establishing a building construction parameter grid according to the Cartesian product of the candidate value of each building construction parameter; A division module is used to divide the housing construction parameter grid into a preset number of equal sub-areas according to a preset rule, and randomly select the data of the housing construction parameter in one of the grids from the sub-areas as the benchmark housing construction parameter combination of the sub-areas; A setting module, used to set a housing building structure optimization objective function, determine a target value of a sub-region according to the benchmark housing building parameter combination and the objective function, and determine a target sub-region from a preset number of sub-regions according to the target value; A limiting module is used to select the benchmark building parameter combination of each sub-region after meshing the target sub-region again, calculate the target value and determine a new target sub-region, so as to limit the range of the target sub-region until the parameter space of the target sub-region is less than a preset threshold; The optimization module is used to determine the final combination of building construction parameters according to the data of the building construction parameters in the final target sub-area using a preset optimization algorithm and a building construction structure optimization objective function.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.

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