Method and system for predicting and optimizing anti-seismic property of concrete-filled steel tube structure

Abstract

The invention provides an anti-seismic performance prediction optimization method and system for a concrete-filled steel tube structure, and relates to the technical field of building materials, and the method comprises the steps: interactively obtaining building concrete-filled steel tube design and building anti-seismic performance requirements; performing finite element modeling to obtain an initial structure finite element model; carrying out an earthquake working condition structure response test, and positioning distributed anti-seismic risk nodes; transversely segmenting the initial structure finite element model into W layers of independent risk analysis sub-models according to the distributed anti-seismic risk nodes; according to the node building structure characteristics, hierarchical progressive anti-seismic structure optimization is carried out, and a multivariate anti-seismic optimization scheme set is output and comprises a tie bar structure subset, a reinforcement constraint structure subset and an interface bonding reinforcement subset. The technical problem that in the prior art, due to the fact that response differences of different areas and different components in a building in an earthquake cannot be accurately recognized through aseismic design, weak links of a local area are ignored, and the overall aseismic performance is reduced is solved.

Description

Technical Field

[0001] This invention relates to the field of building materials technology, specifically to a method and system for predicting and optimizing the seismic performance of steel-concrete composite structures. Background Technology

[0002] Concrete-tube steel structures are widely used in the construction of high-rise buildings, bridges and important facilities due to their excellent mechanical and seismic properties. Concrete-tube steel structures usually combine steel tubes and concrete, taking advantage of the advantages of both to improve the load-bearing capacity and seismic performance of the structure. The steel tubes provide good compressive strength and restraint, while the concrete provides higher bending strength and durability.

[0003] However, current seismic design of steel-concrete composite structures is usually based on simplified assumptions, such as assuming that the seismic waves act uniformly and that all parts of the structure are subjected to equal stress. However, these assumptions cannot fully reflect the complex dynamic response of buildings during earthquakes. Especially in the case of high-rise buildings or complex structures, such simplified assumptions cannot accurately assess seismic performance, cannot fully consider the differences in response of different areas and components within the building during earthquakes, and easily overlook weak points in local areas. This can lead to over-strengthening or under-strengthening in the design, which may result in the building failing to perform at its best in real earthquake events, posing safety hazards, wasting resources, and increasing construction costs. Summary of the Invention

[0004] This application provides a method and system for predicting and optimizing the seismic performance of steel-concrete composite structures. It aims to solve the technical problem that existing seismic design technologies cannot accurately identify the differences in response of different areas and components within a building during an earthquake, leading to the neglect of weak points in local areas and thus reducing the overall seismic performance.

[0005] The first aspect disclosed in this application provides a method for predicting and optimizing the seismic performance of steel-concrete composite structures. The method includes: interactively obtaining the steel-concrete composite building design and seismic performance requirements; performing finite element modeling based on the steel-concrete composite building design to obtain an initial structural finite element model; locating distributed seismic risk nodes by conducting seismic response tests on the initial structural finite element model; horizontally dividing the initial structural finite element model into W independent risk analysis sub-models based on the distributed seismic risk nodes; and performing hierarchical progressive seismic structural optimization on the W independent risk analysis sub-models based on the nodal structural characteristics of the distributed seismic risk nodes, outputting a multivariate seismic optimization scheme set, wherein the multivariate seismic optimization scheme set includes a tie-bar construction subset, a reinforced constraint construction subset, and an interface bonding strengthening subset.

[0006] The second aspect of this application discloses a seismic performance prediction and optimization system for steel-concrete composite structures. The system is used in the aforementioned seismic performance prediction and optimization method for steel-concrete composite structures. The system includes: a performance requirement acquisition module for interactively obtaining the design and seismic performance requirements of the steel-concrete composite building; a finite element modeling module for performing finite element modeling based on the steel-concrete composite building design to obtain an initial structural finite element model; a response testing module for locating distributed seismic risk nodes by conducting seismic response tests on the initial structural finite element model; a model segmentation module for horizontally segmenting the initial structural finite element model into W independent risk analysis sub-models based on the distributed seismic risk nodes; and a seismic structure optimization module for performing hierarchical progressive seismic structure optimization on the W independent risk analysis sub-models based on the nodal building structural characteristics of the distributed seismic risk nodes, outputting a multi-element seismic optimization scheme set, wherein the multi-element seismic optimization scheme set includes a tie-bar construction subset, a reinforced constraint construction subset, and an interface bonding strengthening subset.

[0007] One or more technical solutions provided in this application have at least the following beneficial effects:

[0008] Interactive methods were used to obtain the design and seismic performance requirements of steel-concrete composite structures, ensuring that the optimized design was based on accurate and practical needs, thus improving the accuracy of seismic performance prediction. Finite element modeling was performed based on the steel-concrete composite design to obtain an initial structural finite element model, which could accurately simulate the mechanical behavior and deformation modes of the building structure, providing a high-precision initial data foundation for subsequent seismic analysis and ensuring the effectiveness of subsequent optimization. Seismic response testing of the initial structural finite element model effectively identified the most vulnerable distributed seismic risk nodes in the building structure. These nodes are typically areas of maximum stress and severe deformation under seismic loading, and are key areas for seismic optimization. Precise seismic response testing ensured that the seismic optimization scheme could specifically strengthen the building structure. Weak links in the building structure are identified. Based on distributed seismic risk nodes, the initial structural finite element model is horizontally divided into multiple independent risk analysis sub-models, allowing for independent risk analysis of each layer. This hierarchical analysis method enables more precise evaluation of each layer of the building structure, improving analysis efficiency and avoiding oversimplification, thereby optimizing the seismic performance of each layer. By performing hierarchical progressive seismic structural optimization on each independent risk analysis sub-model based on the nodal building structural characteristics of the distributed seismic risk nodes, a multi-dimensional seismic optimization scheme set can be output. These scheme sets include multi-dimensional optimization strategies such as tie-bar construction subsets, reinforced constraint construction subsets, and interface bonding strengthening subsets. The most suitable optimization scheme can be selected according to the specific needs of different nodes, thus providing a flexible and adaptable seismic enhancement design for the structure.

[0009] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0010] Figure 1 A schematic diagram of the seismic performance prediction and optimization method for steel-concrete composite structures provided in this application embodiment.

[0011] Figure 2 A schematic diagram of the seismic performance prediction and optimization system for steel-concrete composite structures provided in this application embodiment.

[0012] Figure labeling: Performance requirement acquisition module 10, Finite element modeling module 20, Response testing module 30, Model segmentation module 40, Seismic structure optimization module 50. Detailed Implementation

[0013] This application provides a method and system for predicting and optimizing the seismic performance of steel-concrete composite structures. It solves the technical problem that existing seismic design cannot accurately identify the differences in response of different areas and components inside a building during an earthquake, leading to the neglect of weak links in local areas and thus reducing the overall seismic performance.

[0014] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0015] Example 1, as Figure 1 As shown in the embodiments of this application, a method for predicting and optimizing the seismic performance of steel-concrete composite structures is provided. The method includes:

[0016] Interactively obtain information on the design of steel-concrete composite structures and the seismic performance requirements of buildings.

[0017] Interactive methods are used to obtain the design and seismic performance requirements of steel-concrete composite buildings. The design of steel-concrete composite buildings includes the building's geometric dimensions (such as height, length, and width), structural layout, material specifications of steel tubes and concrete, and load conditions. Obtaining this design data can provide accurate parameters for subsequent modeling. The seismic performance requirements include seismic fortification intensity, design seismic group, and seismic site conditions. Specific requirements are set according to the building's use, geographical location, and seismic codes. The designer determines the building's seismic targets based on these requirements, such as the maximum allowable structural displacement and the standard for maintaining functionality after an earthquake.

[0018] Finite element modeling was performed based on the steel-concrete composite building design to obtain the initial structural finite element model.

[0019] The building geometry data in the design of steel-concrete composite structures is analyzed to construct a building geometry model, including the floor height, the structure of each floor, and the location and dimensions of the steel-concrete composite components. The building geometry model is then meshed, that is, the building is divided into multiple discrete units to facilitate subsequent finite element calculations. After meshing, material properties are set for each unit. For example, the material parameters of the steel pipe (such as the elastic modulus, density, and yield strength of steel) and the material parameters of the concrete (such as strength grade and elastic modulus) are input. Combined with the building's boundary conditions and load conditions, such as wind load, live load, and seismic load, the building geometry model is modified to form an initial structural finite element model, which reflects the mechanical behavior of the structure under various external forces.

[0020] By conducting seismic response tests on the initial structural finite element model, distributed seismic risk nodes were located.

[0021] Based on the seismic performance requirements of the building, various seismic conditions are set, such as different seismic waves or epicenter locations. Response analysis is performed on the initial structural finite element model. The simulated seismic waves can be standard seismic waves or seismic waves modified according to specific site conditions. Time history analysis is then performed on the initial structural finite element model under seismic conditions. This step simulates the dynamic response of the structure under seismic loading, including acceleration, displacement, and internal forces. Common methods include nonlinear time history analysis, where seismic waves are applied as input loads to the initial structural finite element model to simulate the structure's movement at different time points. By analyzing the structural response data under seismic loading, the nodes with the most severe stress or deformation in the structure are located. These nodes are the most vulnerable points in the structure's seismic performance and are called distributed seismic risk nodes. These nodes include critical connection parts, weak support areas, or steel-concrete composite joints in the structure.

[0022] Based on the distributed seismic risk nodes, the initial structural finite element model is horizontally divided into W independent risk analysis sub-models.

[0023] The spatial locations of distributed seismic risk nodes are projected onto the initial structural finite element model. By calculating the three-dimensional positions of the nodes within the structure, a topological distribution model of the risk nodes is formed. This model reveals which parts of the structure pose greater structural risk and require more attention. By analyzing the vertical distribution of the distributed seismic risk nodes in the initial structural finite element model, the average vertical distance between the nodes is calculated to determine which areas experience concentrated stress or deformation in the vertical direction. Based on the vertical distribution of the nodes, the structure is laterally divided according to a preset hierarchical scale. Each layer can be considered an independent risk analysis unit. Thus, the resulting W-layer independent risk analysis sub-model has different seismic risk characteristics at each layer, allowing for more refined seismic analysis and optimization at each layer.

[0024] Based on the structural characteristics of the distributed seismic risk nodes, a hierarchical progressive seismic structural optimization is performed on the W-layer independent risk analysis sub-model, outputting a multivariate seismic optimization scheme set, wherein the multivariate seismic optimization scheme set includes a tie-bar structure subset, an enhanced constraint structure subset, and an interface bonding reinforcement subset.

[0025] The structural features of distributed seismic risk nodes are extracted, including: regional component type, indicating the specific component type of the node, such as beams, columns, walls, etc.; node damage index, indicating the degree of damage or failure mode that the node may suffer during an earthquake; and node stress state, characterizing the stress state of the node under seismic loads, such as compression, tension, shear, etc.

[0026] Based on the extracted nodal building structural features, corresponding seismic optimization strategies are triggered through a preset strategy library. The preset strategy library contains different optimization schemes, such as: a tie-bar construction strategy library, which improves seismic resistance by adding tie bars in the structure and strengthening nodal connections; an enhanced constraint construction strategy library, which prevents excessive deformation of the structure and improves seismic performance by adding constraints to the structure; and an interface bonding strengthening strategy library, which strengthens the interface bonding force between different components to prevent slippage or separation between components during an earthquake.

[0027] The component type, damage index, and stress state of each node are input into the corresponding strategy library. A matching algorithm generates optimal seismic optimization schemes, which propose different design options based on the specific circumstances of each node to enhance its seismic resistance. Finally, through hierarchical optimization, the output multivariate seismic optimization scheme set includes a subset of tie-bar structures, a subset of reinforced constraint structures, and a subset of interface bond strengthening structures. These optimization schemes will provide specific design guidance for improving the seismic performance of steel-concrete composite structures, effectively reducing the impact of earthquakes on the structure.

[0028] Furthermore, based on the aforementioned steel-concrete composite building design, finite element modeling is performed to obtain an initial structural finite element model. The method includes:

[0029] The building geometric data of the steel-concrete composite building design is analyzed to construct a building geometric model. After the building geometric model is meshed based on a preset grid scale, the material properties of the grid-level geometric structure are set to obtain a building property model. Building boundary conditions and building load conditions are extracted from the building steel-concrete composite building design. The structural mechanical behavior of the building property model is corrected using the building boundary conditions and building load conditions to obtain the initial structural finite element model.

[0030] Building geometric data is extracted from the design of steel-concrete composite structures, including the overall layout of the building, the dimensions of each floor, the floor height, the location and specifications of steel-concrete composite components, the dimensions of columns and beams, the layout of walls, etc. Based on this building geometric data, a building geometric model is constructed. This model is represented in three dimensions and can accurately reflect the dimensions, relative positions, and detailed features of each component of the building.

[0031] Based on the building's scale and required analytical precision, a pre-defined grid scale is used. This involves dividing the building's geometric model into small discrete units according to certain rules. The grid scale affects the analytical precision; generally, smaller unit scales achieve higher precision but also require more computation. Through meshing, the building's geometric model is divided into multiple discrete units. Each discrete unit can be a triangle, quadrilateral, hexahedron, etc., adapting to different types of finite element analysis methods. Each discrete unit represents a structural element, such as a small segment of a beam, column, or wall.

[0032] Material properties are assigned to each discrete element, including the elastic modulus, density, yield strength, Poisson's ratio, etc. of steel pipes and concrete. Different components use different materials, so it is necessary to select appropriate material properties according to the architectural design. Based on the architectural design and mesh generation, corresponding material properties are set for each discrete element to obtain the architectural property model. Each discrete element contains the geometric shape and material properties of the building, providing the necessary information for finite element analysis.

[0033] Building boundary conditions and building load conditions are extracted from the design of steel-concrete composite structures. Building boundary conditions are used to define the support conditions, connection conditions, and constraint methods of the structure. Support conditions include column base support, beam end support, etc., which may be fixed support, rolling support, or hinged support. Connection conditions refer to the connection methods between the components in the structure, whether they are rigid connections, hinged connections, etc. Constraint conditions refer to the external constraints of the building, such as the connection with other buildings and the contact with the foundation.

[0034] Building load conditions include: self-weight load, which refers to the load caused by the building's own volume and materials; live load, which refers to the load of people, furniture, etc.; wind load, which refers to the load generated by wind pressure on the building; and seismic load, which refers to the seismic load set according to the seismic fortification intensity and site conditions. Loads are usually unevenly distributed in different parts of the building, therefore it is necessary to accurately extract the load conditions for each floor and each component.

[0035] After incorporating building boundary conditions and building load conditions into the building attribute model, the finite element method is used to calculate and obtain preliminary mechanical behavior analysis results of the structure, including information such as deformation, stress distribution, and vibration modes of the structure under external forces. Finally, an initial structural finite element model is formed, which accurately reflects the building's response under various external forces, providing a foundation for subsequent seismic performance analysis and optimization.

[0036] Furthermore, based on the distributed seismic risk nodes, the initial structural finite element model is horizontally divided into W independent risk analysis sub-models, the method comprising:

[0037] The distributed seismic risk nodes are spatially projected onto the initial structural finite element model to generate a risk node topology distribution model. Based on the spatial vertical distribution of the distributed seismic risk nodes in the risk node topology distribution model, the average vertical distance between the nodes is calculated and output. The average vertical distance between the nodes is used as a horizontal stratification scale to horizontally divide the risk node topology distribution model into the W-layer independent risk analysis sub-model.

[0038] The spatial locations of distributed seismic risk nodes are projected onto the initial structural finite element model, which is a three-dimensional discretized model where each discrete element represents a part of the structure. Here, projection means determining the specific location of each distributed seismic risk node in the three-dimensional finite element model. The information of all distributed seismic risk nodes projected onto the initial structural finite element model is summarized to form a risk node topology distribution model. This model shows the distribution and relative positions of risk nodes in the entire structure, which helps to further analyze the influence range and interrelationships of these nodes.

[0039] Based on the risk node topology distribution model, the vertical position of each distributed seismic risk node in the structure is analyzed, that is, the floor or height position of the node. For example, the node is located at the top, bottom or middle of a certain floor. The average vertical distance of these distributed seismic risk nodes is calculated. That is, by analyzing the vertical distribution between all nodes, an average vertical distance value is calculated. This average vertical distance reflects the approximate vertical distribution range of the risk nodes in the structure.

[0040] Based on the calculated average vertical distance, the structure containing the distributed seismic risk nodes is divided into several layers according to the horizontal stratification scale. Each layer contains a certain number of risk nodes. According to the location and risk level of these risk nodes in the structure, the boundary of each layer is determined. Based on the average vertical distance, the structure is divided into W layers. Each layer is an independent risk analysis unit, that is, each layer represents a group of nodes or components with similar risk characteristics. The nodes in each layer can exhibit similar responses under seismic action, so they can be analyzed independently.

[0041] Furthermore, based on the structural characteristics of the distributed seismic risk nodes, a hierarchical progressive seismic structural optimization is performed on the W-layer independent risk analysis sub-model, outputting a multivariate seismic optimization scheme set. The method includes:

[0042] Extract N regional component types, N node damage indices, and N node stress states from N seismic risk nodes in the Kth-level independent risk analysis sub-model. Based on the hierarchical characteristics of the Kth-level independent risk analysis sub-model, trigger the target strategy library, which includes a tie-bar construction strategy library, an enhanced constraint construction strategy library, and an interface bonding strengthening strategy library. Input the N regional component types, N node damage indices, and N node stress states into the target strategy library to obtain N parameterized seismic optimization schemes. If the target strategy library is an enhanced constraint construction strategy library, then update the N seismic risk nodes and N parameterized seismic optimization schemes to the enhanced constraint construction subset. This process is repeated to perform hierarchical progressive seismic structural optimization on the W-level independent risk analysis sub-model, outputting the multivariate seismic optimization scheme set.

[0043] Each seismic risk node corresponds to a different type of component, such as beams, columns, walls, or connection nodes. By extracting N seismic risk nodes from the Kth layer independent risk analysis sub-model, the type of component in the area corresponding to each seismic risk node is determined. For example, one node may be located at a column connection, while another node may be at the junction of a beam and a column. Each type of component behaves differently in an earthquake, and the optimization strategy will also be different.

[0044] Each seismic risk node may suffer varying degrees of damage under seismic loading. Node damage indicators represent the degree of damage or deformation of the node. For example, whether the node has cracks, the width of the cracks, whether the node has undergone plastic deformation or yielding, and whether there is local damage in the stress area of ​​the node. These node damage indicators help identify which nodes have poor seismic performance and which areas need to be reinforced or optimized.

[0045] The stress state of each seismic risk node under seismic load includes different stress conditions such as compression, tension, and shear, reflecting the mechanical behavior of the node during an earthquake. This helps to determine which areas may be damaged under seismic load or require special design improvements.

[0046] Each independent risk analysis sub-model has different hierarchical characteristics. For example, assuming the Kth floor is a higher floor, its seismic resistance requirements are higher than those of lower floors. The structural performance and requirements of different floors in an earthquake will vary, therefore, different optimizations are needed based on the characteristics of each floor. The corresponding optimization strategies in the target strategy library are triggered based on the hierarchical characteristics. The target strategy library includes a tie-bar construction strategy library, a reinforced constraint construction strategy library, and an interface bonding strengthening strategy library. The tie-bar construction strategy library is used for nodes that require enhanced member connections and improved tensile strength, including adding steel bars or other reinforcing materials to ensure the overall stability of the structure. The reinforced constraint construction strategy library is used for situations requiring increased constraint forces at structural nodes to prevent excessive displacement or deformation during an earthquake; this strategy typically improves seismic resistance by enhancing connections or increasing member stiffness. The interface bonding strengthening strategy library is used for situations requiring enhanced bonding forces at the contact surfaces between members, typically by adding interface bonding materials to reduce structural slippage and ensure coordinated work between members.

[0047] The extracted N regional component types, N node damage indices, and N node stress states are input into the target strategy library to match suitable seismic optimization schemes. For example, if a node is located at a beam-column connection and has significant shear damage, a scheme to enhance constraints is recommended to strengthen the seismic resistance of the node. The seismic optimization scheme is parameterized according to the specific conditions of the node, that is, the optimization scheme is customized according to the different characteristics of the node. This means that the optimization scheme for each node is a customized design for the specific situation of that node.

[0048] If the selected target strategy library is the enhanced constraint construction strategy library, it means that for parts where the nodes are subjected to excessive stress or require increased structural stiffness, the constraint forces of the nodes need to be enhanced to improve their seismic resistance. This strategy achieves the goal by increasing the stiffness of the components, strengthening the connections between components, and improving the constraint conditions. In this case, N seismic risk nodes are associated with N matched parametric seismic optimization schemes and updated in the enhanced constraint construction subset.

[0049] Similarly, if the target strategy library is a tie-bar structure strategy library, then N seismic risk nodes and N parameterized seismic optimization schemes are associated and updated to the enhanced constraint structure subset; if the target strategy library is an interface bonding reinforcement strategy library, then N seismic risk nodes and N parameterized seismic optimization schemes are associated and updated to the tie-bar structure subset.

[0050] Similarly, for each independent risk analysis sub-model, optimization is carried out in a progressive manner. Each layer takes into account information such as the damage status and stress state of the nodes. Based on the previous matching and updating process, the most suitable optimization strategy is applied to each node. Progressive optimization means gradually strengthening from the foundation level and improving the overall seismic performance of the structure layer by layer. After optimization, all schemes will be summarized into a multivariate seismic optimization scheme set. This scheme set includes the optimal design for each layer and each node, and outputs different optimization schemes according to the characteristics of different layers and nodes.

[0051] Furthermore, based on the aforementioned steel-concrete composite building design, finite element modeling is performed to obtain an initial structural finite element model. The method includes:

[0052] The seismic performance requirements of the building are analyzed to obtain the seismic fortification intensity, design earthquake group, and seismic site conditions. Multi-scale simulated seismic waves are matched and set according to the seismic fortification intensity, design earthquake group, and seismic site conditions. These multi-scale simulated seismic waves are used as input loads and applied to the initial structural finite element model for nonlinear time history analysis to extract time-series structural response data. The time-series structural response data is traversed to locate structural performance deviation nodes, and the distributed seismic risk nodes are output.

[0053] Seismic fortification intensity is determined based on the seismic risk assessment of the building's location. It reflects the maximum earthquake intensity that the building design should be able to withstand. The seismic fortification intensity varies in different regions, and buildings in high-intensity areas need to have stronger seismic resistance. The design seismic group is determined based on the building's function, importance, and seismic protection requirements. The seismic group includes different seismic wave characteristics, such as period and epicenter location. Seismic site conditions refer to the geological and soil conditions of the ground where the building is located. They directly affect the propagation characteristics of seismic waves. For example, soil type, density, and liquefaction potential will affect the seismic performance of the structure.

[0054] Multi-scale simulated seismic waves refer to the comprehensive evaluation of structural responses under various seismic scenarios by simulating seismic waves of different scales and frequencies. Based on seismic fortification intensity, design seismic grouping, and seismic site conditions, appropriate seismic waves are selected, modified, and adapted to ensure that the characteristics of the simulated waves match the actual situation. Specifically, the seismic fortification intensity is used as the benchmark for generating seismic waves. The amplitude and frequency of the seismic waves are adjusted according to the requirements of different intensities. The periodic characteristics of the seismic waves are determined according to the design seismic grouping. Seismic waves of different intensities and frequencies are simulated. The simulated seismic waves are corrected by considering the influence of seismic site conditions on seismic wave propagation. For example, seismic waves in soft soil areas propagate slowly and have longer periods, while those in hard rock and soil layers propagate faster and have shorter periods, ultimately resulting in multi-scale simulated seismic waves.

[0055] Multi-scale simulated seismic waves are applied as input loads to the initial structural finite element model. These seismic waves act as dynamic loads on various nodes of the structure, simulating the dynamic response of the structure during an actual earthquake. Nonlinear time-history analysis is then performed to analyze the nonlinear behavior of the building structure under seismic loading. The structure may exhibit nonlinear phenomena such as plastic deformation, yielding, and cracking, which need to be accurately simulated in the time-history analysis. The purpose of nonlinear time-history analysis is to simulate the dynamic response process of the structure under seismic loads, capturing the changes in displacement, acceleration, and internal forces at different time points. During the analysis, time-series structural response data, such as node displacement, acceleration, and forces, are extracted. This time-series data records the impact of seismic waves on the building structure at different time points.

[0056] By traversing the time-series structural response data, the performance of each node under seismic load is analyzed. Performance deviation refers to the performance changes of a node under seismic load, such as excessive displacement, stress exceeding the limit, and node damage. By comparing the response data of each node, nodes with large performance deviations are identified. Nodes showing large deviations are marked as distributed seismic risk nodes. These nodes are the parts of the structure most susceptible to being affected, damaged, or destroyed in an earthquake, and are the focus of subsequent seismic optimization.

[0057] Furthermore, the method for setting up multi-scale simulated seismic waves based on the seismic fortification intensity, design earthquake grouping, and seismic site conditions includes:

[0058] The earthquake site conditions are input into a preset earthquake database to obtain multi-scale standard earthquake waves; the peak ground acceleration of the multi-scale standard earthquake waves is corrected according to the seismic fortification intensity; the periodic characteristics of the multi-scale standard earthquake waves are corrected according to the design earthquake grouping; and the multi-scale simulated earthquake waves are output.

[0059] The seismic site conditions are input into a pre-defined seismic database. This database contains seismic wave models for different geological and site conditions, generated based on the unique characteristics of the seismic site, such as soft soil and hard rock. Based on the input seismic site conditions, the database automatically matches suitable multi-scale standard seismic waves for that site. These multi-scale standard seismic waves, derived from extensive experiments and research, represent typical seismic waveforms under specific site conditions. They are seismic wave models capable of covering different magnitudes and frequency ranges, adapting to various seismic events of different scales and intensities, and thus helping to more comprehensively assess the structural response under different types of earthquakes.

[0060] Peak ground acceleration (PGA) refers to the maximum acceleration reached by a seismic wave. It directly affects the vibration intensity of a building structure. The PGA of standard seismic waves is adjusted according to the seismic fortification intensity of the area where the building is located. Higher acceleration is required in high-intensity areas to simulate strong earthquakes, while it is relatively lower in low-intensity areas. The PGA of multi-scale standard seismic waves is adjusted according to the seismic fortification intensity requirements to ensure that it can represent the earthquake intensity required by the design.

[0061] Periodic characteristics refer to the vibration period of seismic waves, i.e., the frequency distribution of seismic waves. Different seismic events have different frequency characteristics, which directly affect the seismic response of structures. Based on the design seismic grouping, the periodic characteristics of multi-scale standard seismic waves are adjusted to match the expected characteristics of actual seismic activity. After peak ground acceleration and periodic characteristic correction, the final multi-scale simulated seismic waves are output. These simulated seismic waves will serve as input loads for subsequent nonlinear time-history analysis, simulating the building's response under different seismic conditions.

[0062] Furthermore, after meshing the building geometry model based on a preset grid scale, the material properties of the grid-level geometry are set to obtain a building property model. The method includes:

[0063] The building geometry model is meshed into multiple discrete grid geometric units based on a preset grid scale; the unit type is mapped and converted according to the component type identifier of the multiple discrete grid geometric units to generate shell unit groups, solid unit groups and interface unit groups; after setting the collaborative material properties of the shell unit groups, solid unit groups and interface unit groups, the building attribute model is obtained by modeling and reconstruction.

[0064] Based on the size of the building and the required analysis accuracy, the grid scale is set. The grid scale determines the size of each unit in the building's geometric model. A grid scale that is too small will increase the computational load but provide higher accuracy; a grid scale that is too large may lose some details.

[0065] Based on the preset grid scale, the building geometry model is discretized. In this process, the building geometry model is divided into multiple discrete grid geometry units. The geometry of each unit can be a triangle, quadrilateral, cube, or hexahedron, etc. The specific shape depends on the finite element method used for analysis. For example, for a floor plan, it is divided into multiple small rectangular units, each of which represents a part of the building.

[0066] Each discrete grid geometric element corresponds to a different part of the building, such as beams, columns, walls, and floors. Each component type has different physical properties (such as stiffness, strength, and stress mode). Based on the component type identifier, element type mapping is performed. Shell elements are used to represent two-dimensional structural components, such as walls and floors. Shell elements are used to analyze stress and deformation in the plane and vertical plane. Solid elements are used to represent three-dimensional components, such as columns and beams. Solid elements are suitable for situations where volumetric stress and three-dimensional deformation need to be analyzed. Interface elements are used to represent the connection interfaces between different components, such as beam-column connections and the contact surface between floor slabs and columns. Interface elements are used to simulate phenomena such as contact, slippage, and bonding.

[0067] Assigning appropriate material properties, such as concrete and steel, to shell element groups is crucial. The elastic modulus, density, and yield strength of these materials will influence the deformation and stress analysis of the building. Similarly, assigning appropriate material properties to solid element groups, typically representing structural members like columns and beams, requires specifying their strength, elastic modulus, and plasticity. Assigning appropriate material properties to interface element groups, including bond strength and coefficient of friction, describes the interaction between components. After assigning the corresponding material properties to each element group, a complete building property model is reconstructed through the finite element modeling process. This model includes the building's geometry, the mechanical properties of its components, and material characteristics, used for subsequent structural mechanical behavior analysis to help evaluate the building's response and performance under loads such as earthquakes.

[0068] In summary, the seismic performance prediction and optimization method for steel-concrete composite structures provided in this application has the following technical effects:

[0069] Interactive methods were used to obtain the design and seismic performance requirements of steel-concrete composite structures, ensuring that the optimized design was based on accurate and practical needs, thus improving the accuracy of seismic performance prediction. Finite element modeling was performed based on the steel-concrete composite design to obtain an initial structural finite element model, which could accurately simulate the mechanical behavior and deformation modes of the building structure, providing a high-precision initial data foundation for subsequent seismic analysis and ensuring the effectiveness of subsequent optimization. Seismic response testing of the initial structural finite element model effectively identified the most vulnerable distributed seismic risk nodes in the building structure. These nodes are typically areas of maximum stress and severe deformation under seismic loading, and are key areas for seismic optimization. Precise seismic response testing ensured that the seismic optimization scheme could specifically strengthen the building structure. Weak links in the building structure are identified. Based on distributed seismic risk nodes, the initial structural finite element model is horizontally divided into multiple independent risk analysis sub-models, allowing for independent risk analysis of each layer. This hierarchical analysis method enables more precise evaluation of each layer of the building structure, improving analysis efficiency and avoiding oversimplification, thereby optimizing the seismic performance of each layer. By performing hierarchical progressive seismic structural optimization on each independent risk analysis sub-model based on the nodal building structural characteristics of the distributed seismic risk nodes, a multi-dimensional seismic optimization scheme set can be output. These scheme sets include multi-dimensional optimization strategies such as tie-bar construction subsets, reinforced constraint construction subsets, and interface bonding strengthening subsets. The most suitable optimization scheme can be selected according to the specific needs of different nodes, thus providing a flexible and adaptable seismic enhancement design for the structure.

[0070] Example 2, based on the same inventive concept as the seismic performance prediction and optimization method for steel-concrete composite structures in the foregoing examples, such as... Figure 2 As shown in the embodiment of this application, a seismic performance prediction and optimization system for steel-concrete composite structures is provided. The system includes:

[0071] The performance requirement acquisition module 10 is used to interactively obtain the design requirements of steel-concrete composite buildings and the seismic performance requirements of buildings.

[0072] The finite element modeling module 20 is used to perform finite element modeling based on the steel-concrete composite building design to obtain the initial structural finite element model.

[0073] The response testing module 30 is used to locate distributed seismic risk nodes by performing seismic response tests on the initial structural finite element model.

[0074] The model segmentation module 40 is used to horizontally segment the initial structural finite element model into W independent risk analysis sub-models based on the distributed seismic risk nodes.

[0075] The seismic structure optimization module 50 is used to perform hierarchical progressive seismic structure optimization on the W-layer independent risk analysis sub-model based on the nodal building structure characteristics of the distributed seismic risk nodes, and output a multi-element seismic optimization scheme set, wherein the multi-element seismic optimization scheme set includes a tie-bar structure subset, an enhanced constraint structure subset, and an interface bonding reinforcement subset.

[0076] Furthermore, the finite element modeling module 20 is used to perform the following operation steps:

[0077] The building geometric data of the steel-concrete composite building design is analyzed to construct a building geometric model. After the building geometric model is meshed based on a preset grid scale, the material properties of the grid-level geometric structure are set to obtain a building property model. Building boundary conditions and building load conditions are extracted from the building steel-concrete composite building design. The structural mechanical behavior of the building property model is corrected using the building boundary conditions and building load conditions to obtain the initial structural finite element model.

[0078] Furthermore, the model segmentation module 40 is used to perform the following operation steps:

[0079] The distributed seismic risk nodes are spatially projected onto the initial structural finite element model to generate a risk node topology distribution model. Based on the spatial vertical distribution of the distributed seismic risk nodes in the risk node topology distribution model, the average vertical distance between the nodes is calculated and output. The average vertical distance between the nodes is used as a horizontal stratification scale to horizontally divide the risk node topology distribution model into the W-layer independent risk analysis sub-model.

[0080] Furthermore, the seismic structure optimization module 50 is used to perform the following operation steps:

[0081] Extract N regional component types, N node damage indices, and N node stress states from N seismic risk nodes in the Kth-level independent risk analysis sub-model. Based on the hierarchical characteristics of the Kth-level independent risk analysis sub-model, trigger the target strategy library, which includes a tie-bar construction strategy library, an enhanced constraint construction strategy library, and an interface bonding strengthening strategy library. Input the N regional component types, N node damage indices, and N node stress states into the target strategy library to obtain N parameterized seismic optimization schemes. If the target strategy library is an enhanced constraint construction strategy library, then update the N seismic risk nodes and N parameterized seismic optimization schemes to the enhanced constraint construction subset. This process is repeated to perform hierarchical progressive seismic structural optimization on the W-level independent risk analysis sub-model, outputting the multivariate seismic optimization scheme set.

[0082] Furthermore, the response testing module 30 is used to perform the following operation steps:

[0083] The seismic performance requirements of the building are analyzed to obtain the seismic fortification intensity, design earthquake group, and seismic site conditions. Multi-scale simulated seismic waves are matched and set according to the seismic fortification intensity, design earthquake group, and seismic site conditions. These multi-scale simulated seismic waves are used as input loads and applied to the initial structural finite element model for nonlinear time history analysis to extract time-series structural response data. The time-series structural response data is traversed to locate structural performance deviation nodes, and the distributed seismic risk nodes are output.

[0084] Furthermore, the response testing module 30 is used to perform the following operation steps:

[0085] The earthquake site conditions are input into a preset earthquake database to obtain multi-scale standard earthquake waves; the peak ground acceleration of the multi-scale standard earthquake waves is corrected according to the seismic fortification intensity; the periodic characteristics of the multi-scale standard earthquake waves are corrected according to the design earthquake grouping; and the multi-scale simulated earthquake waves are output.

[0086] Furthermore, the finite element modeling module 20 is used to perform the following operation steps:

[0087] The building geometry model is meshed into multiple discrete grid geometric units based on a preset grid scale; the unit type is mapped and converted according to the component type identifier of the multiple discrete grid geometric units to generate shell unit groups, solid unit groups and interface unit groups; after setting the collaborative material properties of the shell unit groups, solid unit groups and interface unit groups, the building attribute model is obtained by modeling and reconstruction.

[0088] Through the foregoing detailed description of the seismic performance prediction and optimization method for steel-concrete composite structures, those skilled in the art can clearly understand the seismic performance prediction and optimization system for steel-concrete composite structures in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section.

[0089] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for predicting and optimizing the seismic performance of steel-concrete composite structures, characterized in that, The method includes: Interactively obtain the design requirements for steel-concrete composite structures and the seismic performance requirements of buildings; Finite element modeling was performed based on the steel-concrete composite building design to obtain the initial structural finite element model. By conducting seismic structural response tests on the initial structural finite element model, distributed seismic risk nodes are located. Based on the distributed seismic risk nodes, the initial structural finite element model is horizontally divided into W independent risk analysis sub-models; Based on the structural characteristics of the distributed seismic risk nodes, a hierarchical progressive seismic structural optimization is performed on the W-layer independent risk analysis sub-model, outputting a multivariate seismic optimization scheme set, wherein the multivariate seismic optimization scheme set includes a tie-bar structure subset, an enhanced constraint structure subset, and an interface bonding reinforcement subset.

2. The method for predicting and optimizing the seismic performance of steel-concrete composite structures as described in claim 1, characterized in that, Based on the steel-concrete composite building design, finite element modeling is performed to obtain an initial structural finite element model. The method includes: The architectural geometric data of the steel-concrete composite building design are analyzed to construct the architectural geometric model. After the building geometry model is meshed based on a preset grid scale, the material properties of the grid-level geometry are set to obtain the building property model. The building boundary conditions and building load conditions are extracted from the steel-concrete composite building design. The structural mechanical behavior of the building attribute model is corrected by using the building boundary conditions and building load conditions to obtain the initial structural finite element model.

3. The method for predicting and optimizing the seismic performance of steel-concrete composite structures as described in claim 1, characterized in that, Based on the distributed seismic risk nodes, the initial structural finite element model is horizontally divided into W independent risk analysis sub-models, the method including: The distributed seismic risk nodes are spatially projected onto the initial structural finite element model to generate a risk node topology distribution model. Based on the spatial vertical distribution of the distributed seismic risk nodes in the risk node topology distribution model, the average vertical distance between the nodes is calculated and output. Using the average vertical distance between the nodes as a horizontal stratification scale, the risk node topology distribution model is horizontally divided into the W-layer independent risk analysis sub-model.

4. The method for predicting and optimizing the seismic performance of steel-concrete composite structures as described in claim 1, characterized in that, Based on the structural characteristics of the distributed seismic risk nodes, a hierarchical progressive seismic structural optimization is performed on the W-layer independent risk analysis sub-model, outputting a multivariate seismic optimization scheme set. The method includes: Extract the N regional component types, N node damage indices, and N node stress states of N seismic risk nodes from the Kth layer independent risk analysis sub-model; Based on the hierarchical characteristics of the Kth layer independent risk analysis sub-model, the target strategy library is triggered, wherein the target strategy library includes a tie rod construction strategy library, an enhanced constraint construction strategy library, and an interface bonding reinforcement strategy library; The N regional component types, N node damage indices, and N node stress states are input into the target strategy library to obtain N parameterized seismic optimization schemes. If the target strategy library is an enhanced constraint construction strategy library, then the N seismic risk nodes and N parameterized seismic optimization schemes will be associated and updated to the enhanced constraint construction subset; Similarly, hierarchical progressive seismic structural optimization is performed on the W-layer independent risk analysis sub-model, outputting the multivariate seismic optimization scheme set.

5. The method for predicting and optimizing the seismic performance of steel-concrete composite structures as described in claim 1, characterized in that, Based on the steel-concrete composite building design, finite element modeling is performed to obtain an initial structural finite element model. The method includes: The seismic performance requirements of the building are analyzed to obtain the seismic fortification intensity, design seismic group, and seismic site conditions. Multi-scale simulated seismic waves are set up based on the seismic fortification intensity, design earthquake grouping, and earthquake site conditions. The multi-scale simulated seismic wave is used as an input load and applied to the initial structural finite element model for nonlinear time history analysis to extract time-series structural response data. The time-series structural response data is traversed to locate structural performance deviation nodes, and the distributed seismic risk nodes are output.

6. The method for predicting and optimizing the seismic performance of steel-concrete composite structures as described in claim 5, characterized in that, The method for setting up multi-scale simulated seismic waves based on the seismic fortification intensity, design earthquake grouping, and seismic site conditions includes: The earthquake site conditions are input into a preset earthquake database to obtain multi-scale standard earthquake waves. The peak ground acceleration of the multi-scale standard seismic wave is corrected according to the seismic fortification intensity, and the periodic characteristics of the multi-scale standard seismic wave are corrected according to the design earthquake grouping, and the multi-scale simulated seismic wave is output.

7. The method for predicting and optimizing the seismic performance of steel-concrete composite structures as described in claim 2, characterized in that, After meshing the building geometry model based on a preset grid scale, material properties of the grid-level geometry are set to obtain a building property model. The method includes: The building geometric model is meshed into multiple discrete grid geometric units based on a preset grid scale; Based on the component type identifiers of the multiple discrete grid geometric units, the unit type mapping conversion is performed to generate shell unit groups, solid unit groups, and interface unit groups; After setting the collaborative material properties of the shell unit group, solid unit group and interface unit group, the building property model is obtained by modeling and reconstruction.

8. A seismic performance prediction and optimization system for steel-concrete composite structures, characterized in that, For implementing the seismic performance prediction and optimization method for steel-concrete composite structures according to any one of claims 1-7, the system comprises: The performance requirements acquisition module is used to interactively obtain the design requirements of steel-concrete composite buildings and the seismic performance requirements of buildings. The finite element modeling module is used to perform finite element modeling based on the steel-concrete composite building design to obtain the initial structural finite element model. The response testing module is used to locate distributed seismic risk nodes by performing seismic response tests on the initial structural finite element model under seismic conditions. The model segmentation module is used to horizontally segment the initial structural finite element model into W independent risk analysis sub-models based on the distributed seismic risk nodes. The seismic structure optimization module is used to perform hierarchical progressive seismic structure optimization on the W-layer independent risk analysis sub-model based on the nodal building structure characteristics of the distributed seismic risk nodes, and output a multi-element seismic optimization scheme set, wherein the multi-element seismic optimization scheme set includes a tie-bar structure subset, an enhanced constraint structure subset, and an interface bonding reinforcement subset.

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