Method for determining parameters of a modular building seismic isolation structure and related equipment

Abstract

The application discloses a method for determining parameters of a modular building isolation structure and related equipment, wherein a plurality of different fine building finite element models are constructed, each fine building finite element model is simplified to obtain an initial simplified finite element model corresponding to the fine building finite element model, a first response parameter of the fine building finite element model and a second response parameter of the corresponding initial simplified finite element model are determined, a component parameter of the initial simplified finite element model is iteratively updated based on a response difference degree of the first response parameter and the second response parameter until a preset stop condition is met, and a candidate simplified finite element model is obtained, an isolation parameter of the candidate simplified finite element model is determined based on a plurality of third response parameters of the candidate simplified finite element model, a target simplified finite element model is screened out, and the corresponding fine building finite element model is output. The application can improve the calculation efficiency of the parameters of the modular building isolation structure.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, specifically to a method for determining the parameters of a modular building seismic isolation structure and related equipment. Background Technology

[0002] Prefabricated modular buildings are a rapidly developing form of assembled construction in recent years, characterized by factory prefabrication and rapid on-site assembly. They are widely used in temporary buildings, projects in remote areas, barracks in scenic areas, and pressurized buildings in high-altitude regions. Current technology typically involves designing multiple detailed finite element models (FEMs) of the building, analyzing these models, and selecting the optimal FEM for seismic isolation. This optimal FEM then guides the building construction. However, due to the large number of component elements in the detailed FEM, each update and recalculation takes considerable time, resulting in low computational efficiency for the seismic isolation structural parameters of modular buildings. Summary of the Invention

[0003] This application provides a method and related equipment for determining the parameters of a modular building seismic isolation structure, which can improve the calculation efficiency of the parameters of the modular building seismic isolation structure.

[0004] This application provides a method for determining the parameters of a modular building seismic isolation structure, the method comprising: Multiple detailed building finite element models were constructed, each with a different seismic isolation design strategy. Each of the refined building finite element models is simplified to obtain an initial simplified finite element model corresponding to each of the refined building finite element models, wherein the number of component elements in the refined building finite element model is greater than the number of component elements in the initial simplified finite element model; Determine the first response parameters of the refined building finite element model under the preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load; Based on the response difference between the first response parameter and the second response parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, thus obtaining a candidate simplified finite element model. Determine multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads; The seismic isolation parameters of the candidate simplified finite element model are determined based on multiple third response parameters of the candidate simplified finite element model. Based on the isolation parameters, a target simplified finite element model is selected from multiple candidate simplified finite element models. Output the refined architectural finite element model corresponding to the simplified finite element model of the target.

[0005] In an optional embodiment, the construction of multiple different detailed building finite element models includes: A finite element model of a box unit is constructed, comprising a box frame and six plate elements on the box frame, wherein the plate elements include at least three shell elements. A seismic isolation bearing finite element model is generated between adjacent box element finite element models to connect the two adjacent box element finite element models, thus obtaining a refined building finite element model. The number and position of the support finite element model were updated multiple times to obtain several different detailed building finite element models.

[0006] In an optional embodiment, the simplification of each of the detailed architectural finite element models to obtain the initial simplified finite element model corresponding to each of the detailed architectural finite element models includes: Each plate element is equivalently replaced by two cross-arranged equivalent support beam elements to obtain the initial simplified finite element model corresponding to the refined building finite element model.

[0007] In an optional embodiment, determining the first response parameters of the refined building finite element model under a preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load includes: Initialize the component element parameter set, wherein the component element parameter set includes the component parameters of each component element in the initial simplified finite element model, and the component parameters include the component cross-sectional area and yield strength; The component element parameter set and the preset vibration load are input into the initial simplified finite element model to obtain the second response parameter corresponding to the initial simplified finite element model.

[0008] In an optional embodiment, based on the response difference between the first response parameter and the second response parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, resulting in a candidate simplified finite element model, including: Obtain multiple second response parameters corresponding to multiple initialized component unit parameter sets; Based on the first response parameter and multiple second response parameters, multiple response difference degrees are determined, and the minimum value of the multiple response difference degrees is determined as the global fitness parameter; Based on the global fitness parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, thereby obtaining a candidate simplified finite element model. The preset stopping condition includes the convergence of the global fitness parameter.

[0009] In an optional embodiment, the step of iteratively updating the component parameters of the initial simplified finite element model based on the global fitness parameter until a preset stopping condition is met to obtain a candidate simplified finite element model includes: If the global fitness parameter does not meet the preset stopping condition, then update each of the component unit parameter sets to obtain updated multiple component unit parameter sets; The updated global fitness parameters are determined based on the updated set of multiple component element parameters. If the global fitness parameter satisfies the preset stopping condition, the set of component element parameters corresponding to the updated global fitness parameter is determined as the component parameters of the initial simplified finite element model, thus obtaining a candidate simplified finite element model.

[0010] In an optional embodiment, both the first response parameter and the second response parameter include response quantities across multiple dimensions, and determining multiple response differences based on the first response parameter and the multiple second response parameters includes: Determine the absolute value of the difference in response quantity between the first response parameter and the second response parameter in each dimension; The response difference is obtained by weighting and summing the absolute values ​​of the response differences across each dimension based on preset weighting coefficients.

[0011] Accordingly, this application provides a device for determining the parameters of a modular building seismic isolation structure, the device comprising: Modules are used to build multiple different detailed finite element models of buildings; A simplification module is used to simplify each of the detailed building finite element models to obtain an initial simplified finite element model corresponding to each of the detailed building finite element models, wherein the number of component elements in the detailed building finite element model is greater than the number of component elements in the initial simplified finite element model. The first determining module is used to determine the first response parameters of the refined building finite element model under the preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load; The update module is used to iteratively update the component parameters of the initial simplified finite element model based on the response difference between the first response parameter and the second response parameter until a preset stopping condition is met, thereby obtaining a candidate simplified finite element model. The second determining module is used to determine multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads; The third determining module is used to determine the seismic isolation parameters of the candidate simplified finite element model based on multiple third response parameters of the candidate simplified finite element model. The filtering module is used to select a target simplified finite element model from multiple candidate simplified finite element models based on the seismic isolation parameters. The output module is used to output the detailed architectural finite element model corresponding to the target simplified finite element model.

[0012] Furthermore, the electronic device provided in this application includes a memory and a processor. The memory stores a computer program, and the processor runs the computer program in the memory to implement the steps in the method for determining the parameters of the modular building seismic isolation structure provided in this application.

[0013] Furthermore, the computer-readable storage medium provided in this application stores a computer program that is adapted to be loaded by a processor to implement the steps in the method for determining the parameters of the modular building seismic isolation structure provided in this application.

[0014] Furthermore, the computer program product provided in this application includes a computer program that, when executed by a processor, implements the steps in the method for determining the parameters of a modular building seismic isolation structure provided in this application.

[0015] In this application, compared to related technologies, multiple different refined building finite element models are constructed, each with a different seismic isolation design strategy. Each refined building finite element model is simplified to obtain an initial simplified finite element model, wherein the number of component elements in the refined building finite element model is greater than that in the initial simplified finite element model. First response parameters of the refined building finite element model under a preset vibration load and second response parameters of the corresponding initial simplified finite element model under the same preset vibration load are determined. Based on the response difference between the first and second response parameters, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, resulting in a candidate simplified finite element model. Multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads are determined. Seismic isolation parameters of the candidate simplified finite element model are determined based on these third response parameters. Based on the seismic isolation parameters, a target simplified finite element model is selected from the multiple candidate simplified finite element models, and the refined building finite element model corresponding to the target simplified finite element model is output. This application simplifies the refined finite element models corresponding to different seismic isolation design strategies, significantly reducing the number of model component elements. The simplified initial finite element model is iteratively updated to approximate the refined building finite element model, resulting in candidate simplified finite element models. Then, the corresponding refined building finite element model is selected based on the seismic isolation parameters of the candidate simplified finite element models. This reduces the computational dimension, fundamentally reduces the amount of finite element iteration calculation, and improves the computational efficiency of modular building seismic isolation structure parameters. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a system for determining the parameters of a modular building seismic isolation structure provided in an embodiment of this application. Figure 2 This is a schematic flowchart of an embodiment of the method for determining the parameters of a modular building seismic isolation structure provided in this application. Figure 3 This is a schematic diagram of a fine building finite element model in one embodiment of the method for determining the parameters of a modular building seismic isolation structure provided in this application. Figure 4 This is a schematic diagram of the initial simplified finite element model in one embodiment of the method for determining the parameters of a modular building seismic isolation structure provided in this application. Figure 5 This is a schematic diagram of the structure of the seismic isolation bearing in one embodiment of the method for determining the parameters of the modular building seismic isolation structure provided in this application. Figure 6 This is a cross-sectional schematic diagram of the seismic isolation bearing in one embodiment of the method for determining the parameters of a modular building seismic isolation structure provided in this application. Figure 7 This is a schematic diagram of the device for determining the parameters of a modular building seismic isolation structure provided in the embodiments of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] It should be noted that the principles of this application are illustrated by example in a suitable computing environment. The following description is based on the specific embodiments of this application that are illustrated, and should not be regarded as limiting other specific embodiments not detailed herein.

[0019] In the following description of this application, "some embodiments" are referred to, which describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subset of all possible embodiments, and may be combined with each other without conflict.

[0020] In the following description of this application, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] To improve the calculation efficiency of seismic isolation structural parameters for modular buildings, embodiments of this application provide a method and related equipment for determining these parameters. The related equipment may include a device for determining the seismic isolation structural parameters of modular buildings, electronic equipment, a computer-readable storage medium, and a computer program product. The method for determining the seismic isolation structural parameters of modular buildings can be executed by the device for determining these parameters, or by an electronic device integrating the device.

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] This application also provides a system for determining the parameters of a modular building seismic isolation structure, which includes electronic equipment. The electronic equipment integrates the device for determining the parameters of the modular building seismic isolation structure provided in this application.

[0025] To better understand the method, apparatus, electronic device, and storage medium for determining the parameters of a modular building seismic isolation structure provided in this application embodiment, the application environment applicable to this application embodiment is described below.

[0026] Please see Figure 1 , Figure 1 This diagram illustrates an application environment for a method for determining the parameters of a modular building seismic isolation structure according to an embodiment of this application. As one implementation, the method for determining the parameters of a modular building seismic isolation structure provided in this embodiment can be applied to an electronic device. This electronic device can be, for example,... Figure 1 The server 110 shown can be connected to the terminal device 120 via a network. The network serves as a medium for providing a communication link between the server 110 and the terminal device 120. The network can include various connection types, such as wired communication links, wireless communication links, etc., and this embodiment does not limit this. Optionally, in other embodiments, the electronic device can also be a smartphone, laptop, or other terminal device.

[0027] It should be understood that Figure 1 The server 110, network, and terminal device 120 shown are merely illustrative. Depending on the implementation requirements, any number of servers, networks, and terminal devices can be included. For example, server 110 can be a physical server, a cloud server, or a server cluster composed of multiple servers, etc., and terminal device 120 can be a mobile phone, tablet computer, desktop computer, laptop computer, smartwatch, smart glasses, in-vehicle terminal, smart home terminal, cloud computer, etc. It is understood that embodiments of this application can also allow multiple terminal devices 120 to access server 110 simultaneously.

[0028] In addition, the system for determining the parameters of the modular building seismic isolation structure may also include a memory for storing the raw data, intermediate data, and result data during the determination process of the modular building seismic isolation structure parameters. In this embodiment of the application, the storage device can be a cloud storage device. Cloud storage is a new concept that is extended and developed from the concept of cloud computing. A distributed cloud storage system (hereinafter referred to as a storage system) refers to a storage system that uses cluster applications, grid technology and distributed storage file system functions to bring together a large number of storage devices of various types in the network (storage devices are also called storage nodes) through application software or application interfaces to work together to provide data storage and business access functions to the outside world.

[0029] Currently, the storage method in storage systems is as follows: Logical volumes are created, and during creation, physical storage space is allocated to each logical volume. This physical storage space may consist of a single storage device or the disks of several storage devices. Clients store data on a logical volume, which means storing the data on the file system. The file system divides the data into many parts, each part being an object. Each object contains not only the data but also additional information such as a data identifier (ID entity). The file system writes each object to the physical storage space of that logical volume, and it records the storage location information of each object. Therefore, when a client requests access to data, the file system can allow the client to access the data based on the storage location information of each object.

[0030] The process by which a storage system allocates physical storage space to a logical volume is as follows: the physical storage space is pre-divided into strips according to the capacity estimate of the objects stored in the logical volume (this estimate often has a large margin relative to the actual capacity of the objects to be stored) and the grouping of Redundant Array of Independent Disks (RAID). A logical volume can be understood as a strip, thus allocating physical storage space to the logical volume.

[0031] It should be noted that, Figure 1 The schematic diagram of the modular building seismic isolation structure parameter determination system shown is merely an example. The modular building seismic isolation structure parameter determination system and scenario described in this application embodiment are for the purpose of more clearly illustrating the technical solution of this application embodiment and do not constitute a limitation on the technical solution provided by this application embodiment. As those skilled in the art will know, with the evolution of the modular building seismic isolation structure parameter determination system and the emergence of new business scenarios, the technical solution provided by this application embodiment is also applicable to similar technical problems.

[0032] The following sections provide detailed descriptions of each example. It should be noted that the sequence numbers of the following embodiments are not intended to limit the preferred order of the embodiments.

[0033] Please refer to Figure 2 , Figure 2 This is a schematic flowchart of an embodiment of the method for determining the parameters of a modular building seismic isolation structure provided in this application. This method for determining the parameters of a modular building seismic isolation structure can be executed by electronic equipment, such as... Figure 2 As shown, the process for determining the parameters of the modular building seismic isolation structure provided in this application is as follows: 201. Construct multiple different detailed finite element models of buildings.

[0034] Among them, several detailed building finite element models have different seismic isolation design strategies.

[0035] The finite element model (FEM) is a model established using the finite element analysis method. It is a combination of elements connected only at nodes, transmitting forces only at nodes, and constrained only at nodes. The construction of a finite element model mainly includes the following steps: Geometric model establishment and simplification: Abstracting the geometric solution domain based on the shape of the actual physical object. Element selection and material property definition: Selecting an appropriate element type based on the physical shape and expected behavior of the component to be analyzed. For example, one-dimensional beam elements can be used for slender structures, and two-dimensional shell elements can be used for thin-walled structures. Material property definition: Inputting the constitutive model parameters of the material, such as elastic modulus, Poisson's ratio, density, yield strength, etc., and setting it as a linear elastic or plastic, hyperelastic, or other nonlinear model as needed. Meshing: Dividing the continuous geometric model into a finite number of interconnected, simple-shaped micro-elements. During this process, the mesh density and quality need to be controlled. Mesh refinement is usually required in stress concentration or high gradient regions to ensure computational accuracy. Adding constraints: Applying displacement constraints such as fixed, hinged, and sliding constraints to eliminate rigid body motion of the model, making it statically determinate or hyperstatically indeterminate. Add load conditions: Apply external excitations such as force, pressure, torque, acceleration or temperature field to appropriate nodes or element surfaces.

[0036] After establishing the finite element model, the computer can automatically assemble the global equation system based on the established finite element model and perform numerical calculations, converting the calculation results into intuitive graphics (such as stress / strain cloud diagrams, deformation animations, safety factor distributions, etc.) or data reports.

[0037] The number of detailed building finite element models is set according to specific circumstances. For example, the number of detailed building finite element models can be 2, 3, 4, 5 or more.

[0038] In this embodiment of the application, multiple different detailed architectural finite element models are constructed, including: (1) Construct a box element finite element model of multiple prefabricated modular box units, wherein the box element finite element model includes a box frame and six plate elements on the box frame, and the plate elements include at least three shell elements.

[0039] like Figure 3 As shown, multiple prefabricated modular box units are prefabricated box structures in the factory and assembled on-site to form an integrated building. Specifically, to accurately analyze stress performance, each plate unit includes at least three shell units; for example, a plate unit may include 100 shell units.

[0040] Specifically, based on the characteristics of prefabricated modular building structure systems, multiple sets of standardized prefabricated modular box-shaped units were constructed using refined finite element numerical models. Each box-shaped unit's finite element model primarily comprises two core structural systems: the box frame and the cladding panels. The box frame can be modeled using integrated steel beams and columns, accurately reproducing the geometric dimensions, cross-sectional properties, and spatial arrangement of load-bearing components such as corner columns and upper and lower frames, fully preserving the stiffness, load-bearing capacity, and force transmission path of the frame structure. The six plate elements of the box frame correspond to the front, rear, left, right, top, and bottom of the building box. To ensure the accuracy of finite element calculations and to closely match the stress and deformation characteristics of thin-plate components, each plate element in each direction undergoes refined meshing, with each plate surface divided into at least three shell elements. This refined meshing accurately reproduces the planar stress, out-of-plane bending deformation, and shear deformation of the cladding wall panels and prefabricated composite wall panels, eliminating calculation distortion caused by large-size unit modeling and fully replicating the stiffness characteristics and dynamic response characteristics of solid wall panels.

[0041] (2) Generate the support finite element model of the seismic isolation bearing between the adjacent box element finite element models to connect the two adjacent box element finite element models and obtain the fine building finite element model.

[0042] After constructing the finite element model of a single standardized box unit, multiple box units are assembled and molded according to the modular building assembly logic. Between the finite element models of adjacent box units on the upper and lower floors and left and right sides, the support finite element models of the seismic isolation bearings are accurately generated according to the actual seismic isolation design scheme of the project. The adjacent two sets of box unit finite element models are connected by constraint coupling and node binding, which realistically simulates the seismic isolation connection structure between the modular building boxes, accurately restores the vertical bearing capacity, horizontal deformation, and energy dissipation and seismic isolation mechanical functions of the bearings, and completes the construction of a single set of detailed building finite element models.

[0043] Specifically, such as Figure 5 As shown, the seismic isolation bearing includes a support column 31, an upper bearing plate 32, a spherical slider 33, and a lower bearing plate 34. The support column 31 and the lower bearing plate 34 are respectively connected to two prefabricated modular box units. The spherical slider 33 is located between the upper bearing plate 32 and the lower bearing plate 34. The side of the upper bearing plate 32 and the lower bearing plate 34 facing each other is a concave arc surface, the side of the spherical slider 33 that contacts the upper bearing plate 32 is a convex arc surface, and the side of the spherical slider 33 that contacts the lower bearing plate 34 is a convex arc surface.

[0044] like Figure 6 As shown, the raised arc surfaces on the spherical slider 33 and the recessed arc surfaces on the upper and lower seat plates 32 and 34 are made of friction material, such as polytetrafluoroethylene (PTFE). The parameters of the seismic isolation bearing are as follows: Figure 6 As shown, the radius of the raised arc surface on the spherical slider 33 is 285mm, the distance between the outer sides of the upper seat plate 32 and the lower seat plate 34 is 100mm, and the distance between the inner sides of the upper seat plate 32 and the lower seat plate 34 is 70mm.

[0045] (3) The number and position of the support finite element model are updated multiple times to obtain multiple different fine building finite element models.

[0046] Each update of the number and location of the bearing finite element models yields a refined building finite element model, resulting in multiple different refined building finite element models. This allows for the creation of refined building finite element models with varying seismic isolation performance.

[0047] 202. Simplify each detailed building finite element model to obtain the initial simplified finite element model corresponding to each detailed building finite element model.

[0048] The number of component elements in the refined building finite element model is greater than the number of component elements in the initial simplified finite element model.

[0049] To address the challenges of a large number of elements, complex mesh generation, lengthy computational iterations, and difficulty in achieving convergence in refined finite element models, the plate elements in the model are replaced with equivalent replacements.

[0050] like Figure 4 As shown, in a specific embodiment, each detailed building finite element model is simplified to obtain an initial simplified finite element model corresponding to each detailed building finite element model. This includes: replacing each plate element with two equivalent supporting beam elements arranged in an intersecting manner to obtain the initial simplified finite element model corresponding to the detailed building finite element model. The component parameters of each equivalent supporting beam element in the initial simplified finite element model can be adjusted, while other parameters are the same as those in the detailed building finite element model.

[0051] The component elements of the refined building finite element model include beam elements on the box frame and shell elements on the six plate elements of the box frame. The component elements of the initial simplified finite element model include beam elements on the box frame and equivalent support beam elements on the six plate elements of the box frame. Since at least three shell elements are replaced with two equivalent support beam elements, the number of components is reduced.

[0052] For all plate elements in the six directions of the box frame, the original high-precision shell element mesh system was deleted, and the traditional detailed solid modeling method for wall panels was abandoned. Each enclosure plate element was replaced as an equivalent set of spatially intersecting equivalent support beam elements. Two equivalent diagonal beam elements were correspondingly intersected on each plate surface, thus replacing the overall stress and deformation performance of the original wall panel. The equivalent replacement process strictly followed the principle of mechanical equivalence, retaining the original box frame's geometric position, spatial dimensions, node coordinates, boundary constraints, and the arrangement and connection relationship of the seismic isolation supports. Only the wall panel's stress system was simplified and replaced, ensuring that the simplified model and the detailed model were completely consistent in terms of structural force transmission path, overall constraint state, and component spatial layout. The two sets of intersecting equivalent support beam elements were arranged symmetrically in an X-shape, hinged to the four corner frame nodes of the corresponding plate surface. They could respectively bear the horizontal shear force and seismic action in the X and Y directions of the structure, while coordinating with the vertical components to transfer vertical loads, accurately and equivalently replacing the lateral stiffness, bending stiffness, shear stiffness, and ultimate bearing capacity of the original shell unit wall panel. Through the aforementioned equivalent replacement process, the massive number of shell elements in the refined model are completely eliminated, significantly reducing the number of model elements, modeling complexity, and computational dimensionality, ultimately yielding the initial simplified finite element model corresponding to the refined building finite element model. This initial simplified model replaces the traditional massive number of wall panel shell elements with a small number of equivalent beam elements, achieving dimensionality reduction and simplification of the model while preserving the overall dynamic characteristics and mechanical response laws of the original structure to the greatest extent. For example, the number of component elements in the refined building finite element model is 12,000, while the corresponding number of component elements in the initial simplified finite element model is 120.

[0053] 203. Determine the first response parameters of the refined building finite element model under the preset vibration load and the second response parameters of the corresponding initial simplified finite element model under the preset vibration load.

[0054] In this embodiment of the application, the preset vibration load can be any one of El Centro seismic waves, Taft seismic waves, artificial wave seismic waves, or static conditions.

[0055] The first and second response parameters both include response quantities in multiple dimensions. These multiple response quantities include the natural period, acceleration response, and maximum inter-story drift angle.

[0056] The natural period is an inherent dynamic property of the structure, determined by the overall mass and stiffness of the building; the greater the stiffness, the smaller the period. The maximum inter-story drift angle refers to the relative lateral deformation between adjacent floors under seismic loading, directly reflecting the deformation capacity of the walls and equivalent supports against lateral loads. It is a key indicator for evaluating the lateral bearing capacity of the structure and whether the shear stiffness of the wall panels is equivalent. Different floors represent prefabricated modular box units of different heights. The acceleration response can be taken as the peak floor acceleration, characterizing the magnitude of the structural inertial vibration under seismic input, relating to the structural mass distribution and local stiffness, energy dissipation characteristics, and reflecting the equivalent effect of wall panel yield energy dissipation and ultimate bearing capacity.

[0057] In a specific embodiment, determining the first response parameters of the refined building finite element model under a preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load includes: (1) Initialize the component unit parameter set.

[0058] The component element parameter set includes the component parameters of each component element in the initial simplified finite element model, including the component cross-sectional area and yield strength. Further, the component element parameter set includes the component parameters of each equivalent support beam element in the initial simplified finite element model. Since the component parameters of the equivalent support beam elements differ from those of the refined building finite element model only in the initial simplified finite element model, the component parameters of the component elements other than the equivalent support beam elements are the same as those in the refined building finite element model. Therefore, only the component parameters of the equivalent support beam elements need to be optimized.

[0059] In a specific embodiment, for each component element in the initial simplified finite element model, the component cross-sectional area is randomly generated within a preset area range, and the yield strength is randomly generated within a preset yield strength range. For example, the preset area range is [0.0001, 0.01] m², and the preset yield strength range is [200, 400] MPa.

[0060] (2) Input the component element parameter set and the preset vibration load into the initial simplified finite element model to obtain the second response parameters corresponding to the initial simplified finite element model.

[0061] Specifically, a preset vibration load is applied to a refined building finite element model to obtain the first response parameters, and the preset vibration load is applied to an initial simplified finite element model to obtain the second response parameters. The preset vibration load can be applied to the finite element model by changing the load conditions in the finite element model.

[0062] 204. Based on the response difference between the first response parameter and the second response parameter, iteratively update the component parameters of the initial simplified finite element model until the preset stopping condition is met, and obtain the candidate simplified finite element model.

[0063] In this embodiment of the application, based on the response difference between the first response parameter and the second response parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, resulting in a candidate simplified finite element model, including: (1) Obtain multiple second response parameters corresponding to multiple initialized component unit parameter sets.

[0064] In this embodiment of the application, N second response parameters corresponding to N initialized component unit parameter sets are obtained. Here, N is an integer greater than 1, for example, N=30.

[0065] The component element parameter set includes the component parameters of each component element in the initial simplified finite element model. These parameters include the component's cross-sectional area and yield strength. A component element parameter set also includes the component parameters of all equivalent support beam elements in the initial simplified finite element model.

[0066] In a specific embodiment, let the set of parameters for the i-th component element be X. i In the initial simplified finite element model, all equivalent supporting beam elements have the same component parameters. The component element parameter set includes the component cross-sectional area A. i and yield strength f y,i .

[0067] X i = [A i , f y,i ], where i = 1, 2, ..., 30.

[0068] Furthermore, initialize the flight speed set for each component unit parameter set. The flight speed set includes the flight speed of each component parameter. The flight speed of each component parameter is a preset percentage of its value; this preset percentage can be 10%, 15%, or other values, depending on the specific situation. Let V be the flight speed set corresponding to the i-th component unit parameter set. i Flight speed set V i Including the cross-sectional area A of the component i Area of ​​flight speed v A,i and yield strength f y,i Intensity of flight speed v fy ,i.

[0069] V i = [v A,i , v fy ,i],i = 1, 2, ..., 30.

[0070] In other embodiments, the equivalent support beam elements in the initial simplified finite element model are split in the three orthogonal directions X, Y, and Z to obtain equivalent support beam elements in the X-axis direction, Y-axis direction, and Z-axis direction. Specifically, among the six plate elements on the box frame, the two equivalent support beam elements of the horizontal plate elements are determined as equivalent support beam elements in the Z-axis direction, and the two equivalent support beam elements of the vertical plate elements are determined as equivalent support beam elements in the X-axis direction and Y-axis direction, respectively.

[0071] (2) Determine multiple response differences based on the first response parameter and multiple second response parameters, and determine the minimum value of multiple response differences as the global fitness parameter.

[0072] In a specific embodiment, both the first response parameter and the second response parameter include response quantities in multiple dimensions. Based on the first response parameter and the multiple second response parameters, multiple response difference degrees are determined, including: determining the absolute value of the difference between the response quantities of the first response parameter and the second response parameter in each dimension; and performing a weighted summation of the absolute values ​​of the difference between the response quantities in each dimension based on a preset weighting coefficient to obtain the response difference degree.

[0073] Specifically, the response parameters include the natural period, acceleration response, and maximum inter-story drift angle. Preset weighting coefficients include weights for the natural period, acceleration response, and maximum inter-story drift angle. The natural period, acceleration response, and maximum inter-story drift angle in the first response parameters are denoted as f. target a target θ target The natural vibration period, acceleration response, and maximum inter-story drift angle in the second response parameter corresponding to the parameter set of the i-th component element are denoted as f, respectively. i a i θ i The weights of the natural vibration period, acceleration response, and maximum inter-story drift angle are recorded as w1, w2, and w3, respectively, and the response difference degree corresponding to the i-th component element parameter set is F. i The response difference degree corresponding to the parameter set of the i-th component element satisfies the following formula: F i = w1· |f i -f target | / f target + w2· |a i - a target | / a target + w3· |θ i - θ target | / θ target。

[0074] Among them, w1, w2, and w3 can be set according to specific circumstances, for example, w1=0.4, w2=0.3, w3=0.3. The natural vibration period has the highest weight to ensure the matching of structural dynamic characteristics. After obtaining multiple response difference degrees, the minimum value of multiple response difference degrees is determined as the global fitness parameter.

[0075] (3) Based on the global fitness parameter, iteratively update the component parameters of the initial simplified finite element model until the preset stopping condition is met to obtain the candidate simplified finite element model. The preset stopping condition includes the convergence of the global fitness parameter.

[0076] In one specific embodiment, the preset stopping conditions include the convergence of the global fitness parameter or the maximum number of iterations reaching a preset number. For example, the preset number is 100 iterations. The convergence of the global fitness parameter means that the change in the global fitness parameter obtained from multiple iterations is less than a preset change amount, for example, the preset change amount is 0.00001 or other values.

[0077] In this embodiment, based on the global fitness parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met to obtain a candidate simplified finite element model. This includes: if the global fitness parameter does not meet the preset stopping condition, updating the set of each component element parameter to obtain multiple updated sets of component element parameters; determining the updated global fitness parameter based on the updated sets of component element parameters; and if the global fitness parameter meets the preset stopping condition, determining the set of component element parameters corresponding to the updated global fitness parameter as the component parameters of the initial simplified finite element model to obtain a candidate simplified finite element model.

[0078] In a specific embodiment, updating the parameter sets of each component unit to obtain multiple updated parameter sets of component units includes: determining the individual extreme values ​​and global extreme values ​​of each component unit parameter set, updating the component unit parameter sets based on the individual extreme values ​​and global extreme values, and obtaining the updated parameter sets of component units.

[0079] This involves calculating the individual extreme values ​​of each component element parameter set. Specifically, it involves calculating the multiple response differences F of the component element parameter set across historical iterations. i The minimum value of multiple response variability is determined as the individual fitness parameter F. i,best The individual fitness parameter F i,best The corresponding set of component element parameters is determined as the individual extreme value P. i,best During the first iteration, the individual extreme value P i,best = X i Individual fitness parameter F i,best= F iThe individual extreme values ​​P of the parameter sets of multiple component elements in this iteration are... i,best The minimum value is determined as the global extremum G in this iteration. best Global extremum G best The corresponding global fitness parameter is F. gbest .

[0080] Let X be the set of parameters for the i-th component element in the k-th iteration. i k The set of flight parameters for the i-th iteration in the k-th round is V. i k The set of parameters for the i-th component element in the (k+1)-th iteration is X. i k+ ¹, the set of flight parameters for the (k+1)th iteration is V. i k+ ¹, the individual extreme value of the parameter set of the i-th component element in the k-th iteration is P. i,best k The global extremum of the parameter set of the i-th component element in the k-th iteration is G. best k .

[0081] Specifically, the parameter set of the i-th component element in the k-th iteration is updated based on the individual extreme value and the global extreme value to obtain the parameter set of the i-th component element in the (k+1)-th iteration. The formula for the parameter set of the i-th component element in the (k+1)-th iteration is as follows. V i k+ ¹ = ω · V i k + c1r1(P i,best k - X i k ) + c2r2(G best k - X i k ) X i k+ ¹ = X i k + V i k+ ¹ Where k is the current iteration number, ω=0.729 is the inertia weight (a standard value that balances global search and local search capabilities), c1=1.494 and c2=1.494 are learning factors (representing self-cognition and social cognition weights, respectively), and r1 and r2 are random numbers between [0,1] to increase search randomness and avoid getting trapped in local optima.

[0082] 205. Determine multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads.

[0083] The multiple different target vibration loads can include at least two of the following: El Centro seismic waves, Taft seismic waves, artificial seismic waves, and static conditions. For example, if there are 10 target vibration loads, 10 third response parameters will be obtained.

[0084] 206. Determine the seismic isolation parameters of the candidate simplified finite element model based on multiple third response parameters of the candidate simplified finite element model.

[0085] In this embodiment, each third response parameter includes response quantities in multiple dimensions. These multiple response quantities include natural vibration period, acceleration response, and maximum inter-story drift angle.

[0086] In one specific embodiment, a pre-defined target natural vibration period, target acceleration response, and target maximum inter-story drift angle are obtained. The target natural vibration period, target acceleration response, and target maximum inter-story drift angle are defined as a first vector. The average value of the natural vibration period, the average value of the acceleration response, and the average value of the maximum inter-story drift angle among multiple third response parameters are defined as a second vector. The cosine similarity between the first and second vectors is calculated, and this cosine similarity is used as the isolation parameter for the candidate simplified finite element model, thus obtaining the isolation parameters for multiple candidate simplified finite element models. A larger isolation parameter indicates that the multiple third response parameters under the target vibration load are closer to the pre-defined values, meeting the seismic resistance requirements.

[0087] 207. Based on the seismic isolation parameters, the target simplified finite element model is selected from multiple candidate simplified finite element models.

[0088] The candidate simplified finite element model with the largest isolation parameter was selected as the target simplified finite element model. The largest isolation parameter indicates that multiple third response parameters under the target vibration load are close to the artificially preset values, which meets the seismic requirements.

[0089] 208. Output the refined architectural finite element model corresponding to the simplified finite element model of the target.

[0090] The refined building finite element model corresponding to the target simplified finite element model is the finite element model with the best seismic performance, and construction can be guided based on the refined building finite element model corresponding to the target simplified finite element model.

[0091] In one embodiment, taking a typical two-story prefabricated modular building (6300mm × 3700mm × 3300mm) as an example, the implementation effect of the present invention is as follows: Equivalent support parameters in the X direction: cross-sectional area approximately 729 mm², yield strength approximately 466 MPa; Equivalent support parameters in the Y direction: cross-sectional area approximately 723 mm², yield strength approximately 345 MPa; Z-direction equivalent support parameters: cross-sectional area approximately 727 mm², yield strength approximately 687 MPa.

[0092] The equivalent parameters and the hysteresis curves and natural vibration period errors of the refined building finite element model are stably controlled within 6.5%, which meets the accuracy requirements of engineering analysis and improves the design efficiency by more than 80% compared with the traditional manual experience trial and error method.

[0093] Furthermore, this invention uses a two-story prefabricated modular pressurized building to test its seismic resistance. This two-story prefabricated modular pressurized building is used for housing and shelter in high-altitude areas. Engineering design conditions: seismic intensity 8 degrees, site characteristic period 0.45s, design basic seismic acceleration 0.2g.

[0094] Building module parameters: Outer dimensions of a single module: Length 6300mm × Width 3700mm × Height 3300mm; Weight of a single module: Approximately 163kN; Module type: Sealed pressurized box, maintaining positive pressure inside to improve the living environment at high altitudes.

[0095] Seismic isolation bearing arrangement: One seismic isolation bearing is placed at each of the four corners of each module, and they are also placed between the foundation and the bottom layer module, and between the upper and lower layer modules, forming a dual seismic isolation system. Bearing design parameters: equivalent radius of curvature 500mm, design displacement 100mm, ultimate displacement 120mm. The bearing friction surface is made of ultra-high molecular weight polyethylene material, which is resistant to ultraviolet rays and low temperatures.

[0096] Parameter optimization calculation: The particle swarm optimization algorithm proposed in this invention is used to identify the equivalent support parameters of the cross truss. The population size is set to 30, the maximum number of iterations is 100, and the algorithm converges after 20 iterations to obtain the optimal equivalent parameters. X direction: Cross-sectional area 729mm², yield strength 466MPa; Y direction: cross-sectional area 723mm², yield strength 345MPa; Z-direction: cross-sectional area 727mm², yield strength 687MPa.

[0097] Dynamic time history analysis verification: An overall structural analysis model was established using optimized parameters. Dynamic time history analysis was performed using three typical seismic waves: El Centro, Taft, and an artificial wave. The results show that: The structure's first-order natural vibration period is 0.56s, which is 2.8 times longer than that of traditional seismic-resistant structures (0.2s period), effectively avoiding the frequency band where earthquake energy is concentrated; the maximum inter-story drift angle under an 8-degree rare earthquake is 1 / 1250, which is less than the design target of 1 / 1000; the peak ground acceleration at the top floor is 2.7m / s², and the acceleration damping efficiency reaches 83%; all performance indicators meet the requirements of the national seismic design code.

[0098] This embodiment fully verifies the effectiveness and engineering applicability of the method for determining the seismic isolation structural parameters of modular buildings proposed in this invention. It is particularly suitable for prefabricated modular pressurized buildings in high-intensity seismic zones and can also be extended to the seismic isolation design of other types of prefabricated modular buildings.

[0099] To facilitate better implementation of the method for determining the parameters of a modular building seismic isolation structure provided in this application, this application also provides a device for determining the parameters of a modular building seismic isolation structure based on the above-described method. The meanings of the terms used are the same as in the method for determining the parameters of a modular building seismic isolation structure described above; for specific implementation details, please refer to the descriptions in the above method embodiments.

[0100] Please refer to Figure 7 , Figure 7 This is a schematic diagram of an embodiment of the device for determining the parameters of a modular building seismic isolation structure provided in this application. The device may include a construction module 401, a simplification module 402, a first determination module 403, an update module 404, a second determination module 405, a third determination module 406, a filtering module 407, and an output module 408. Module 401 is used to construct multiple different detailed architectural finite element models; The simplification module 402 is used to simplify each of the detailed building finite element models to obtain an initial simplified finite element model corresponding to each of the detailed building finite element models, wherein the number of component elements in the detailed building finite element model is greater than the number of component elements in the initial simplified finite element model. The first determining module 403 is used to determine the first response parameters of the refined building finite element model under the preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load; The update module 404 is used to iteratively update the component parameters of the initial simplified finite element model based on the response difference between the first response parameter and the second response parameter until a preset stopping condition is met, thereby obtaining a candidate simplified finite element model. The second determining module 405 is used to determine multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads; The third determining module 406 is used to determine the seismic isolation parameters of the candidate simplified finite element model based on multiple third response parameters of the candidate simplified finite element model. The filtering module 407 is used to filter out a target simplified finite element model from multiple candidate simplified finite element models based on the seismic isolation parameters. Output module 408 is used to output the detailed architectural finite element model corresponding to the target simplified finite element model.

[0101] This application also provides an electronic device, please refer to... Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0102] The electronic device may include a radio frequency (RF) circuit 501, a memory 502 including one or more computer-readable storage media, an input unit 503, a display unit 504, a sensor 505, an audio circuit 506, a wireless Fidelity (WiFi) module 507, a processor 508 including one or more processing cores, and a power supply 509, etc. Those skilled in the art will understand that... Figure 8 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein: RF circuit 501 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and hands it over to one or more processors 508 for processing; additionally, it transmits uplink data to the base station. Typically, RF circuit 501 includes, but is not limited to, an antenna, at least one amplifier, a tuner, one or more oscillators, a Subscriber Identity Module (SIM) card, a transceiver, a coupler, a low-noise amplifier (LNA), a duplexer, etc. Furthermore, RF circuit 501 can also communicate wirelessly with networks and other devices. Wireless communication can use any communication standard or protocol, including but not limited to GSM, GPRS, CDMA, WCDMA, LTE, email, and SMS.

[0103] The memory 502 can be used to store software programs and modules. The processor 508 executes various functional applications by running the software programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as audio data, telephone directory, etc.). In addition, the memory 502 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 502 may also include a memory controller to provide access to the memory 502 for the processor 508 and the input unit 503.

[0104] Input unit 503 can be used to receive input digital or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, in one embodiment, input unit 503 may include a touch-sensitive surface and other input devices. A touch-sensitive surface, also known as a touch display or touchpad, can collect user touch operations on or near it (e.g., user operations using fingers, styluses, or any suitable object or accessory on or near the touch-sensitive surface) and drive corresponding connection devices according to a pre-set program. Optionally, the touch-sensitive surface may include a touch detection device and a touch controller. The touch detection device detects the user's touch orientation and the signal generated by the touch operation, transmitting the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 508, and can receive and execute commands from the processor 508. Furthermore, various types of touch-sensitive surfaces, such as resistive, capacitive, infrared, and surface acoustic wave, can be used. In addition to the touch-sensitive surface, input unit 503 may also include other input devices. Specifically, other input devices may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0105] Display unit 504 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of electronic devices. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Display unit 504 may include a display panel, optionally configured as a liquid crystal display (LCD), organic light-emitting diode (OLED), or similar form. Furthermore, a touch-sensitive surface may cover the display panel. When the touch-sensitive surface detects a touch operation on or near it, it transmits the information to processor 508 to determine the type of touch event. Subsequently, processor 508 provides corresponding visual output on the display panel according to the type of touch event. Although in Figure 8 In this context, the touch-sensitive surface and the display panel are two separate components for implementing input and output functions. However, in some embodiments, the touch-sensitive surface and the display panel can be integrated to achieve input and output functions.

[0106] The electronic device may also include at least one sensor 505, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel according to the ambient light level, and the proximity sensor can turn off the display panel and / or backlight when the electronic device is moved to the ear. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. Other sensors that may be configured in the electronic device, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0107] Audio circuitry 506, a speaker, and a microphone provide an audio interface between the user and the electronic device. Audio circuitry 506 converts received audio data into electrical signals, transmits them to the speaker, and the speaker converts them into sound signals for output. Conversely, the microphone converts collected sound signals into electrical signals, which are then received by audio circuitry 506, converted back into audio data, and processed by processor 508. The processed data is then transmitted via RF circuitry 501 to, for example, another electronic device, or output to memory 502 for further processing. Audio circuitry 506 may also include an earphone jack to facilitate communication between external headphones and the electronic device.

[0108] WiFi is a short-range wireless transmission technology. Electronic devices using the WiFi module 507 can help users send and receive emails, browse web pages, and access streaming media, providing users with wireless broadband internet access. Although Figure 8 WiFi module 507 is shown, but it is understood that it is not a necessary component of an electronic device and can be omitted as needed without changing the nature of the invention.

[0109] The processor 508 is the control center of the electronic device. It connects various parts of the phone via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory 502, and by calling data stored in the memory 502, thereby performing overall detection of the phone. Optionally, the processor 508 may include one or more processing cores; preferably, the processor 508 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 508.

[0110] The electronic device also includes a power supply 509 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 508 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 509 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0111] Although not shown, the electronic device may also include a camera, Bluetooth module, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 508 in the electronic device loads the executable files corresponding to the processes of one or more applications into the memory 502 according to the following instructions, and the processor 508 runs the applications stored in the memory 502 to realize various functions: Multiple detailed building finite element models are constructed, each with a different seismic isolation design strategy. Each detailed building finite element model is simplified to obtain an initial simplified finite element model, where the number of component elements in the detailed building finite element model is greater than that in the initial simplified finite element model. The first response parameters of the detailed building finite element model under a preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the same preset vibration load are determined. Based on the response difference between the first and second response parameters, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, resulting in candidate simplified finite element models. Multiple third response parameters of the candidate simplified finite element models under multiple different target vibration loads are determined. Based on these third response parameters, the seismic isolation parameters of the candidate simplified finite element models are determined. Based on the seismic isolation parameters, a target simplified finite element model is selected from the multiple candidate simplified finite element models, and the detailed building finite element model corresponding to the target simplified finite element model is output.

[0112] It should be noted that the electronic device provided in this application embodiment and the method for determining the parameters of the modular building seismic isolation structure in the above embodiment belong to the same concept. The specific implementation process can be found in the above related embodiments, and will not be repeated here.

[0113] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program stored thereon is executed on the processor of the electronic device provided in the embodiments of this application, the processor of the electronic device performs the steps in the method for determining the parameters of the modular building seismic isolation structure provided in this application. The storage medium may be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0114] This application also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform various optional implementations of the method for determining the parameters of the modular building seismic isolation structure described above.

[0115] The foregoing has provided a detailed description of a method for determining the parameters of a modular building seismic isolation structure and related equipment. This related equipment may include a device for determining the parameters of a modular building seismic isolation structure, electronic equipment, a computer-readable storage medium, and a computer program product. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

[0116] It should be noted that when the above embodiments of this application are applied to specific products or technologies, and user-related data is involved, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

Claims

1. A method for determining the parameters of a modular building seismic isolation structure, characterized in that, The method for determining the parameters of the modular building seismic isolation structure includes: Multiple detailed building finite element models were constructed, each with a different seismic isolation design strategy. Each of the refined building finite element models is simplified to obtain an initial simplified finite element model corresponding to each of the refined building finite element models, wherein the number of component elements in the refined building finite element model is greater than the number of component elements in the initial simplified finite element model; Determine the first response parameters of the refined building finite element model under the preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load; Based on the response difference between the first response parameter and the second response parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, thus obtaining a candidate simplified finite element model. Determine multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads; The seismic isolation parameters of the candidate simplified finite element model are determined based on multiple third response parameters of the candidate simplified finite element model. Based on the isolation parameters, a target simplified finite element model is selected from multiple candidate simplified finite element models. Output the refined architectural finite element model corresponding to the simplified finite element model of the target.

2. The method for determining the parameters of a modular building seismic isolation structure according to claim 1, characterized in that, The construction of multiple different detailed building finite element models includes: A finite element model of a box unit is constructed, comprising a box frame and six plate elements on the box frame, wherein the plate elements include at least three shell elements. A seismic isolation bearing finite element model is generated between adjacent box element finite element models to connect the two adjacent box element finite element models, thus obtaining a refined building finite element model. The number and position of the support finite element model were updated multiple times to obtain several different detailed building finite element models.

3. The method for determining the parameters of a modular building seismic isolation structure according to claim 2, characterized in that, The process of simplifying each of the detailed architectural finite element models to obtain the initial simplified finite element model corresponding to each detailed architectural finite element model includes: Each plate element is equivalently replaced by two cross-arranged equivalent support beam elements to obtain the initial simplified finite element model corresponding to the refined building finite element model.

4. The method for determining the parameters of a modular building seismic isolation structure according to claim 2, characterized in that, Determining the first response parameters of the refined building finite element model under a preset vibration load and the corresponding second response parameters of the initial simplified finite element model under a preset vibration load includes: Initialize the component element parameter set, wherein the component element parameter set includes the component parameters of each component element in the initial simplified finite element model, and the component parameters include the component cross-sectional area and yield strength; The component element parameter set and the preset vibration load are input into the initial simplified finite element model to obtain the second response parameter corresponding to the initial simplified finite element model.

5. The method for determining the parameters of a modular building seismic isolation structure according to claim 4, characterized in that, Based on the response difference between the first response parameter and the second response parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, resulting in a candidate simplified finite element model, including: Obtain multiple second response parameters corresponding to multiple initialized component unit parameter sets; Based on the first response parameter and multiple second response parameters, multiple response difference degrees are determined, and the minimum value of the multiple response difference degrees is determined as the global fitness parameter; Based on the global fitness parameter, the component parameters of the initial simplified finite element model are iteratively updated until a preset stopping condition is met, thereby obtaining a candidate simplified finite element model. The preset stopping condition includes the convergence of the global fitness parameter.

6. The method for determining the parameters of a modular building seismic isolation structure according to claim 5, characterized in that, The process of iteratively updating the component parameters of the initial simplified finite element model based on the global fitness parameter until a preset stopping condition is met, thereby obtaining a candidate simplified finite element model, includes: If the global fitness parameter does not meet the preset stopping condition, then update each of the component unit parameter sets to obtain updated multiple component unit parameter sets; The updated global fitness parameters are determined based on the updated set of multiple component element parameters. If the global fitness parameter satisfies the preset stopping condition, the set of component element parameters corresponding to the updated global fitness parameter is determined as the component parameters of the initial simplified finite element model, thus obtaining a candidate simplified finite element model.

7. The method for determining the parameters of a modular building seismic isolation structure according to claim 1, characterized in that, Both the first response parameter and the second response parameter include response quantities in multiple dimensions. The step of determining multiple response differences based on the first response parameter and the multiple second response parameters includes: Determine the absolute value of the difference in response quantity between the first response parameter and the second response parameter in each dimension; The response difference is obtained by weighting and summing the absolute values ​​of the response differences across each dimension based on preset weighting coefficients.

8. A device for determining the parameters of a modular building seismic isolation structure, characterized in that, The device for determining the parameters of the modular building seismic isolation structure includes: Modules are used to build multiple different detailed finite element models of buildings; A simplification module is used to simplify each of the detailed building finite element models to obtain an initial simplified finite element model corresponding to each of the detailed building finite element models, wherein the number of component elements in the detailed building finite element model is greater than the number of component elements in the initial simplified finite element model. The first determining module is used to determine the first response parameters of the refined building finite element model under the preset vibration load and the corresponding second response parameters of the initial simplified finite element model under the preset vibration load; The update module is used to iteratively update the component parameters of the initial simplified finite element model based on the response difference between the first response parameter and the second response parameter until a preset stopping condition is met, thereby obtaining a candidate simplified finite element model. The second determining module is used to determine multiple third response parameters of the candidate simplified finite element model under multiple different target vibration loads; The third determining module is used to determine the seismic isolation parameters of the candidate simplified finite element model based on multiple third response parameters of the candidate simplified finite element model. The filtering module is used to select a target simplified finite element model from multiple candidate simplified finite element models based on the seismic isolation parameters. The output module is used to output the detailed architectural finite element model corresponding to the target simplified finite element model.

9. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor running the computer program in the memory to perform the steps in the method for determining the parameters of a modular building seismic isolation structure according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted for loading by a processor to perform the steps in the method for determining the parameters of a modular building seismic isolation structure as described in any one of claims 1 to 7.

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