Simulation evaluation method and platform for stability of steel structure based on finite element analysis

Abstract

The application provides a steel structure stability simulation evaluation method and platform based on finite element analysis, relates to the technical field of finite element analysis, and comprises the following steps: deriving a steel structure geometric model and performing reverse decomposition; calling a material attribute set and a connection type set, and performing finite element discretization processing on a construction step unit group sequence; performing environment data retrieval according to the construction coordinates and the progress plan of the steel structure building; implanting wind-temperature coupling field time-varying data into a standard finite element platform to perform environment field dynamic coupling; performing step-by-step loading simulation on the construction step finite element group sequence in the local finite element platform and diagnosing instability risks in real time; performing instability correction closed-loop iteration according to a plurality of instability risk characteristic parameter sequences until a plurality of instability correction strategies are output. The application solves the technical problem that, in the prior art, static detection cannot reflect time-varying risks in the construction process, it is difficult to capture dynamic instability risks, and the construction safety is affected.

Description

Technical Field

[0001] This application relates to the field of finite element analysis technology, specifically to a method and platform for simulation evaluation of steel structure stability based on finite element analysis. Background Technology

[0002] Currently, structural stability testing for existing steel structure projects is mostly based on static analysis models of pre-formed structures, typically using fixed loads and predetermined boundary conditions to check the overall stability of the structure. However, in the actual construction phase, steel structures are not formed in one go, but rather the force system is gradually established during hoisting. The connection relationships of components, the arrangement of temporary supports, and the overall load path will dynamically change with the construction progress. Under different temporary states, the structure may exhibit complex time-varying mechanical behaviors such as local stiffness deficiency, repeated transitions between tension and compression states, or local buckling initiation.

[0003] Because existing methods generally use static models and fixed loads for analysis, they cannot fully reflect the time-varying response during construction. As a result, it is difficult to identify dynamic instability risks that may only occur under specific temporary conditions. This leads to a deviation between the stability analysis results and the actual stress state on site, which in turn affects risk prediction and safety decisions during construction.

[0004] In summary, existing technologies suffer from the problem that the use of static models and fixed loads for analysis makes it difficult to reflect the time-varying risks during the construction process, resulting in the difficulty in identifying dynamic instability risks and thus affecting construction safety. Summary of the Invention

[0005] The purpose of this application is to provide a simulation evaluation method and platform for the stability of steel structures based on finite element analysis, in order to solve the technical problem in the prior art that the use of static models and fixed loads for analysis makes it difficult to reflect the time-varying risks of the construction process, resulting in the difficulty in identifying dynamic instability risks and thus affecting construction safety.

[0006] To achieve the above objectives, this application provides a method and platform for simulating and evaluating the stability of steel structures based on finite element analysis.

[0007] Firstly, this application provides a steel structure stability simulation and evaluation method based on finite element analysis. This method is implemented through a steel structure stability simulation and evaluation platform based on finite element analysis. The method includes: exporting a steel structure geometric model from BIM software; reverse decomposing the steel structure geometric model based on the hoisting sequence to obtain a construction step unit group sequence; retrieving material property sets and connection type sets, performing finite element discretization processing on the construction step unit group sequence, and outputting a construction step finite element group sequence; and then, based on the construction coordinates of the steel structure building... Environmental data retrieval is performed on the target and schedule to obtain time-varying data of the wind-temperature coupled field mapped to the schedule. The time-varying data of the wind-temperature coupled field is then embedded into a standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform. Using the hoisting sequence as the step-by-step loading sequence, step-by-step loading simulation is performed on the finite element group sequence of the construction steps in the local finite element platform. After each loading step, instability risk is diagnosed in real time, and multiple instability risk characteristic parameter sequences of multiple instability risk nodes are output. Based on the multiple instability risk characteristic parameter sequences, instability correction closed-loop iteration is performed until multiple instability correction strategies covering the entire construction instability landscape are output.

[0008] Optionally, a pre-stored hoisting sequence is extracted from the construction management database, and a steel component installation order dependency relationship is constructed based on the hoisting sequence; the geometric connection relationship of the steel structure geometric model is parsed to generate a spatial topological adjacency matrix; temporal dependency compensation is performed on the spatial topological adjacency matrix based on the steel component installation order dependency relationship to output a temporal topological association matrix; the temporal topological association matrix is ​​recursively cut based on the statically determinate isolation criterion to output the construction step unit group sequence, wherein the steel components within each construction step unit group in the construction step unit group sequence do not affect each other.

[0009] Optionally, based on a preset statically determinate determination rule, the time-series topological correlation matrix is ​​traversed to perform statically determinate subgraph identification to obtain a first component subset; the first component subset is recursively cut to output a first local step unit group sequence; after adding the first component subset to the statically determinate identification taboo domain, the time-series topological correlation matrix is ​​updated with statically determinate subgraph identification to obtain a second component subset; the statically determinate subgraph identification and recursive cutting operation of the time-series topological correlation matrix are iteratively performed until the time-series topological correlation matrix is ​​an empty set to obtain multiple local step unit group sequences; the multiple local step unit group sequences are reorganized according to the construction sequence to output the construction step unit group sequence.

[0010] Optionally, the statically determinate criteria include geometric invariance, boundary independence, and load closure.

[0011] Optionally, S1: Inject virtual boundary constraints based on the boundary node structural attributes of the first component subset to generate a virtual boundary constraint set and a reaction load vector set; S2: Cut the rows and columns of the first component subset and add virtual boundary node rows to generate a reduced-order temporal topological correlation matrix; S3: Push the first component subset into a last-in-first-out storage stack; S4: Use the reduced-order temporal topological correlation matrix as the new input, iterate steps S1~S3 until the reduced-order temporal topological correlation matrix is ​​an empty set, then pop the component update subset sequence from the storage stack in reverse order and output the first local step unit group sequence; S5: Map the virtual boundary constraint set and the reaction load vector set to the first local step unit group sequence to apply load boundary conditions.

[0012] Optionally, using the hoisting sequence as the step-by-step loading sequence, the first construction step finite element group is retrieved and activated from the construction step finite element group sequence; after loading the first construction step finite element group on the local finite element platform, multi-threaded instability risk diagnosis is performed, and multiple first instability risk characteristic parameters of the first instability risk node under various load scenarios are output. The multi-threaded instability risk diagnosis covers buckling diagnosis, geometric diagnosis, and material diagnosis, and the various load scenarios cover permanent loads, temporary loads, and environmentally coupled loads; the multiple first instability risk characteristic parameters are aggregated, and a first instability risk characteristic parameter sequence is output; according to the hoisting sequence, the step-by-step loading simulation and instability risk diagnosis of the construction step finite element group sequence are recursively executed until the multiple instability risk characteristic parameter sequences are output.

[0013] Optionally, using the hoisting sequence as the step loading sequence, the second construction step finite element set is retrieved and activated from the construction step finite element set sequence; the second construction step finite element set is loaded on the local finite element platform, and during the multi-threaded instability risk diagnosis process, the time-varying tracking of the multiple first instability risk characteristic parameters is performed; if the multiple first instability risk characteristic parameters fluctuate, parameter correction iteration is performed based on the historical worst-case value update rule until the construction step finite element set sequence is an empty set, and multiple first iteratively corrected instability characteristic parameters are output.

[0014] Optionally, multiple initialization correction strategies are matched based on structural attributes to the multiple instability risk characteristic parameter sequences; based on the strategy substitutability of the multiple initialization correction strategies, strategy combinations are triggered in a hierarchical manner to obtain a strategy adaptation priority sequence; the effectiveness of the strategy adaptation priority sequence is progressively verified based on virtual construction playback until the multiple instability correction strategies covering the entire construction instability landscape are output.

[0015] Optionally, the time-varying data of the wind-temperature coupled field is reconstructed using format standardization to obtain a spatiotemporal four-dimensional matrix. The data dimensions of the spatiotemporal four-dimensional matrix include spatial coordinates, time steps, wind speed vectors, and temperature scalars. Based on the spatiotemporal four-dimensional matrix, a dual-channel physical field transformation process is performed through the physical field transformation interface of the standard finite element platform to obtain nodal force load vectors and material thermal expansion coefficients. The nodal force load vectors are obtained by mapping wind speed field data through fluid dynamics formulas, and the material thermal expansion coefficients are obtained by updating material nonlinear parameters driven by temperature field data. An environmental field coupler is created in the solver kernel of the standard finite element platform, and the nodal force load vectors and material thermal expansion coefficients are dynamically superimposed onto the structural equilibrium equations using the environmental field coupler, outputting the results to the local finite element platform.

[0016] Secondly, this application also provides a steel structure stability simulation and evaluation platform based on finite element analysis, used to execute the steel structure stability simulation and evaluation method based on finite element analysis as described in the first aspect. The platform includes: a model export module for exporting a steel structure geometric model from BIM software; a reverse decomposition module for reverse decomposing the steel structure geometric model based on the hoisting sequence to obtain a construction step unit group sequence; a discretization processing module for retrieving material property sets and connection type sets, performing finite element discretization processing on the construction step unit group sequence, and outputting a construction step finite element group sequence; and a data retrieval module for using the construction coordinates of the steel structure building and... The schedule retrieves environmental data to obtain time-varying data of the wind-temperature coupling field mapped to the schedule. A dynamic coupling module embeds this data into a standard finite element platform to dynamically couple the environmental field and generate a local finite element platform. A distributed simulation module performs step-by-step loading simulation on the finite element group sequence of the construction steps, using the hoisting sequence as the step-by-step loading time sequence. After each loading step, it diagnoses instability risks in real time and outputs multiple instability risk characteristic parameter sequences for multiple instability risk nodes. A closed-loop iteration module performs instability correction closed-loop iteration based on the multiple instability risk characteristic parameter sequences until multiple instability correction strategies covering the entire construction instability landscape are output.

[0017] One or more technical solutions provided in this application have at least the following technical effects or advantages: The steel structure geometric model is exported from BIM software; the steel structure geometric model is decomposed in reverse based on the hoisting sequence to obtain a sequence of construction step unit groups; the material property set and connection type set are retrieved, and the sequence of construction step unit groups is discretized by finite element method to output a sequence of construction step finite element groups; environmental data is retrieved according to the construction coordinates and schedule of the steel structure building to obtain time-varying data of the wind-temperature coupling field mapped to the schedule; the time-varying data of the wind-temperature coupling field is implanted into the standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform; step-by-step loading simulation is performed on the sequence of construction step finite element groups in the local finite element platform with the hoisting sequence as the step loading sequence, and the instability risk is diagnosed in real time after each loading step, outputting multiple instability risk characteristic parameter sequences of multiple instability risk nodes; instability correction closed-loop iteration is performed based on the multiple instability risk characteristic parameter sequences until multiple instability correction strategies covering the overall construction instability are output. In other words, the geometric model of the steel structure is reversed and divided into construction step units according to the hoisting sequence. Each construction step is discretized using finite element methods by calling the structural material library and connection type library. Based on the construction coordinates and schedule, time-varying data of the wind-temperature coupling field are retrieved and mapped, and then used as time-varying boundary conditions to be implanted into the local finite element simulation platform. The simulation is performed step by step according to the hoisting sequence, and the instability risk is diagnosed in real time after each loading step. Instability correction is performed based on the risk characteristics, realizing the forward-looking prediction of instability risk throughout the entire steel structure construction process, thus improving the safety and efficiency of steel structure construction.

[0018] The above description is merely an overview of the technical solution of this application. To better understand the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the simulation evaluation method for steel structure stability based on finite element analysis proposed in this application.

[0021] Figure 2This is a schematic diagram of the steel structure stability simulation and evaluation platform based on finite element analysis proposed in this application.

[0022] Figure labeling: Model export module 11, inverse decomposition module 12, discretization module 13, data retrieval module 14, dynamic coupling module 15, distributed simulation module 16, closed-loop iteration module 17. Detailed Implementation

[0023] This application provides a finite element method (FEM)-based simulation and evaluation method and platform for steel structure stability. It addresses the technical problem in existing technologies where static models and fixed loads fail to reflect time-varying risks during construction, leading to difficulty in identifying dynamic instability risks and consequently impacting construction safety. The method reverse-engineers the steel structure's geometric model into construction step units according to the hoisting sequence. Each construction step is discretized using finite element methods from structural material and connection type libraries. Time-varying wind-temperature coupling field data is retrieved and mapped based on construction coordinates and the schedule, and then embedded as time-varying boundary conditions into the local finite element simulation platform. Simulation is performed step-by-step according to the hoisting sequence, and instability risks are diagnosed in real-time after each loading step. Instability corrections are made based on risk characteristics, enabling proactive prediction of instability risks throughout the entire steel structure construction process, thus improving the safety and efficiency of steel structure construction.

[0024] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0025] Example 1, please refer to the appendix. Figure 1 This application provides a method for simulating and evaluating the stability of steel structures based on finite element analysis. The method is applied to a finite element analysis-based steel structure stability simulation and evaluation platform. The method specifically includes the following steps: Export the geometric model of the steel structure from BIM software.

[0026] Specifically, BIM software, or Building Information Modeling software, is not only a 3D drawing tool but also a database containing information such as the geometric dimensions, materials, and attributes of structural members. After completing the design and detailed design of the steel structure in BIM software, the software's export function allows users to select a neutral and highly compatible file format to output the geometric information and necessary attribute information of the steel structure, resulting in a steel structure geometric model. This steel structure geometric model is a digital model created in BIM software that contains the precise 3D spatial coordinates, cross-sectional shapes, dimensions, and spatial relative positions of all steel members. It includes information such as the coordinate points, cross-sectional dimensions, and material numbers of each member.

[0027] Based on the reverse decomposition of the steel structure geometric model according to the hoisting sequence, the sequence of construction step unit groups is obtained.

[0028] Furthermore, this application also includes the following steps: extracting a pre-stored hoisting sequence from a construction management database, and constructing a steel component installation order dependency relationship based on the hoisting sequence; parsing the geometric connection relationship of the steel structure geometric model to generate a spatial topological adjacency matrix; performing temporal dependency compensation on the spatial topological adjacency matrix based on the steel component installation order dependency relationship, and outputting a temporal topological association matrix; recursively cutting the temporal topological association matrix in reverse based on the statically determinate isolation criterion, and outputting the construction step unit group sequence, wherein the steel components within each construction step unit group in the construction step unit group sequence do not affect each other.

[0029] Specifically, the pre-stored hoisting sequence is extracted from the construction management database—that is, the pre-planned installation sequence of steel components—to guide construction operations. The construction management database is a database that stores project management information, typically including construction schedules, hoisting plans, component lists, etc., storing the planned installation dates and order for each steel structure. Based on the hoisting sequence, the installation order dependencies of the steel structure are determined, that is, the installation order between various components within the steel structure; some components can only be installed after other components are installed. For example, column A must be installed before beam B can be installed, and beam B depends on column A.

[0030] The geometric connection relationships of the steel structure geometric model are analyzed, that is, the topological information of the interconnection of steel components in three-dimensional space, including the node connection positions and the connection status of component endpoints, to obtain a spatial topological adjacency matrix. This matrix represents the spatial connection relationships between the various components in the structure and records whether the steel components are directly connected or have a force transfer relationship. If two components are directly connected, the value at the corresponding position in the matrix is ​​1; otherwise, it is 0.

[0031] Temporal dependency compensation is performed on the spatial topological adjacency matrix based on the installation order dependency of steel components. That is, the hoisting order is added to the spatial topological adjacency matrix to obtain the temporal topological correlation matrix, which reflects not only the geometric connection of the steel structure, but also the installation order dependency.

[0032] The statically determinate isolation criterion states that a structural system is geometrically invariant and has no redundant constraints, and its equilibrium equations have a unique solution. In other words, a complex, unstable, temporary structural state is decomposed into several smaller substructures that can be mechanically analyzed independently. According to the statically determinate isolation criterion, the temporal topological correlation matrix is ​​recursively cut in reverse. Starting from the completed structural state, the structure is progressively decomposed into smaller unit groups in the opposite direction to the hoisting sequence. These reverse-cut unit groups are then arranged in ascending order to form a sequence of construction step unit groups. Each construction step unit group represents a set of mechanically independent components that will be installed in a particular construction step.

[0033] For example, taking a simple two-story steel frame with 3 axes and 2 spans as an example, the hoisting sequence includes first installing all the first-story columns, then installing the first-story beams from left to right, followed by installing all the second-story columns, and finally installing the second-story beams from left to right. Based on the installation order dependency of the steel components, temporal dependency compensation is performed on the spatial topological adjacency matrix. The first-story beam L1-2 is not only marked as connected to columns C1 and C2, but also as indicating that its installation depends on the earlier installation of columns C1 and C2. The last component to be installed is the second-floor beam L2-3. Before the installation of L2-3, the structure consisting of columns C1, C2, and C3, all the beams on the first floor, columns Z1, Z2, and Z3 on the second floor, and beams L2-1 and L2-2 on the second floor was already a statically determinate system. Therefore, L2-3 was cut out as construction step U12. Among the remaining components, it was identified that the structure before the installation of L2-2 was also statically determinate, so L2-2 was cut out as U11; L2-1 was cut out as U10; and so on, Z3 was cut out as U9; Z2 as U8; Z1 as U7; the first-floor beams L1-3 as U6, L1-2 as U5, and L1-1 as U4; C3 as U3, C2 as U2, and C1 as U1. Reverse the result of the reverse cutting to obtain the forward construction step unit group sequence U1, U2, U3, U4, U5, U6, U7, U8, U9, U10, U11, U12.

[0034] The sequence of construction step units strictly conforms to the on-site hoisting sequence, avoiding a disconnect between simulation and actual construction. Through statically determinate isolation, components within a group do not affect each other and can be analyzed independently, significantly reducing the coupling degree and solution difficulty of the finite element model.

[0035] Furthermore, this application also includes the following steps: based on a preset statically determinate determination rule, traversing the temporal topological correlation matrix to perform statically determinate subgraph identification to obtain a first component subset; performing a recursive cutting operation on the first component subset to output a first local step unit group sequence; adding the first component subset to the statically determinate identification taboo domain, and then performing statically determinate subgraph identification and updating the temporal topological correlation matrix to obtain a second component subset; iteratively performing statically determinate subgraph identification and recursive cutting operations on the temporal topological correlation matrix until the temporal topological correlation matrix is ​​an empty set to obtain multiple local step unit group sequences; reorganizing the multiple local step unit group sequences according to the construction sequence to output the construction step unit group sequence.

[0036] Furthermore, this application also includes the following steps: the statically determinate determination rules include geometric invariance, boundary independence and load closure.

[0037] Furthermore, this application also includes the following steps: S1: Injecting virtual boundary constraints based on the boundary node structural attributes of the first component subset to generate a virtual boundary constraint set and a reaction load vector set; S2: Cutting the rows and columns of the first component subset and adding virtual boundary node rows to generate a reduced-order temporal topological correlation matrix; S3: Pushing the first component subset into a last-in-first-out storage stack; S4: Using the reduced-order temporal topological correlation matrix as new input, iterating steps S1 to S3 until the reduced-order temporal topological correlation matrix is ​​an empty set, then popping the component update subset sequence from the storage stack in reverse order and outputting the first local step unit group sequence; S5: Mapping the virtual boundary constraint set and the reaction load vector set to the first local step unit group sequence to apply load boundary conditions.

[0038] Specifically, a pre-defined static determinate criterion is used to determine whether a set of steel components is a statically determinate subset, ensuring that no statically indeterminate state or unstable system occurs when components within the set are loaded. The static determinate criterion includes geometric invariance, boundary independence, and load closure. Geometric invariance means that the shape of the component subset in space is fixed and will not undergo mechanical motion; boundary independence means that the connection between the component subset and other parts of the structure or the ground is independent, and it can withstand external forces without generating indeterminate solutions; load closure means that all loads acting on the component subset can achieve self-equilibrium through its own components and boundary conditions, without generating suspended or unsupported components.

[0039] The temporal topological correlation matrix is ​​traversed, and each component subset is statically determinate. The set of components that meets the static determinacy criteria is automatically found, and the first component subset is identified. The first component subset is recursively cut into fine-grained installation step sequences, i.e., the first local step unit group sequence.

[0040] The structural properties of the boundary nodes of the first component subset are determined, along with the mechanical properties of the nodes connected to other external components or the foundation, including their spatial coordinates, connection methods, and existing constraints. Virtual boundary constraints are injected at the nodes connected to other parts of the structure. These constraints, temporarily applied to the boundary nodes to simulate the supporting effect of the cut portion, are used to isolate the first component subset and ensure its static determinacy and solvability, resulting in a set of virtual boundary constraints. Simultaneously, a corresponding set of reaction load vectors is generated. After the virtual boundary constraints are applied, the forces exerted by the cut-off component portion on the currently retained portion will appear as reaction forces on these virtual constraints, representing the mechanical impact of the removed portion on the retained portion.

[0041] By cutting rows and columns of the first component subset from the temporal topological incidence matrix and adding virtual boundary node rows, a smaller reduced-order temporal topological incidence matrix is ​​obtained. The reduced-order temporal topological incidence matrix is ​​obtained by pruning the atomic set matrix and adding virtual boundary node rows after applying virtual boundaries, and is used for recursive analysis of the remaining components. The first component subset is pushed onto a last-in-first-out (LIFO) storage stack, where elements can only be inserted and deleted from the same end, and the last pushed element is popped first. This is used to temporarily store the cut component subsets during the recursive process. For example, rows and columns corresponding to columns 1, 2, and the first-floor beams are cut off and pushed onto the stack, with the stack contents from bottom to top being columns 1, 2, and the first-floor beams. Columns 3, 4, and the second-floor beams are identified as the next statically determinate subset, virtual constraints are applied to them, reaction forces are calculated, and then they are cut from the matrix and pushed onto the stack. At this point, the stack contents from bottom to top are columns 1, 2, and the first-floor beams, and columns 3, 4, and the second-floor beams.

[0042] Using the reduced-order temporal topological correlation matrix as new input, iterates steps S1-S3, continuing to search for new statically determinate subsets in the remaining portion for cutting and stacking. The recursion ends when the matrix is ​​cut to an empty set. At this point, the stack stores all the component sets cut from back to front, from top to bottom. Reversing the stack pops the components to obtain the installation order of the structure, thus outputting the first local step unit group sequence. The first local step unit group sequence is a local construction step unit group sequence obtained after virtual boundary constraint processing and recursive cutting. The sequence popped in reverse order is exactly the reverse of the order in which the components were cut, i.e., it matches the actual installation order.

[0043] The virtual boundary constraint set and reaction load vector are mapped to the corresponding construction steps in the first local step element group sequence to ensure that the mechanical model of each simulation step is complete and accurate. The processed first component subset is placed into the statically determinate identification taboo domain, thereby excluding it from the subsequent identification range. The time-series topological correlation matrix is ​​updated by statically determinate subgraph identification, and the identification continues to obtain the second component subset, which is also recursively cut. This identification-cutting-taboo cycle is repeated. In each iteration, the time-series topological correlation matrix is ​​updated by statically determinate subgraph identification, and a statically determinate component is extracted and decomposed until the entire matrix is ​​processed and all components belong to a certain local step element group sequence, that is, the time-series topological correlation matrix is ​​an empty set, resulting in multiple local step element group sequences.

[0044] According to the construction sequence, multiple local step unit groups are reorganized, that is, integrated and sorted along the timeline according to the overall project construction schedule to form a globally unified construction step unit group sequence. For example, the main frame sequence, auxiliary structure sequence, roof sequence, etc., are reorganized into a complete, global construction step unit group sequence according to the order in which they are carried out in actual construction.

[0045] For example, assuming the construction decomposition of a stadium grandstand steel structure with a large cantilevered roof is taken as an example, the entire stadium grandstand structure is scanned to identify all the primary frames above the main concrete structure, including main beams, secondary beams, inter-column bracing, etc., totaling 520 steel components, resulting in the first component subset. This set of 520 components is recursively cut, and after internal reverse decomposition, a first local step unit group sequence containing 48 steps is output, such as main frame 1, main frame 2, ..., main frame 48. These 520 components are added to the statically determinate recognition taboo domain, and the temporal topological correlation matrix is ​​updated by statically determinate subgraph recognition. The scan continues, identifying the large cantilevered roof on the west side (85 components) as the second component subset. This is recursively cut, outputting a second local step unit group sequence containing 12 steps, such as west cantilever 1, west cantilever 2, ..., west cantilever 12. The process continues, further identifying the east cantilever, roof membrane structure, etc., as subsequent component subsets, and generating their respective local sequences. According to the overall construction plan, the construction sequence is reorganized. Assuming the plan requires the installation of the west cantilevered roof to begin interspersed when the main frame construction reaches step 30, the first few steps of the final output global construction step unit group sequence are: steps 1 to 29 are main frame 1 to main frame 29, step 30 is main frame 30, step 31 is west cantilever 1, step 32 is main frame 31, step 33 is west cantilever 2, and so on.

[0046] By employing reverse decomposition, the complex steel structure installation process can be broken down and optimized, ensuring the independence and computability of substructure stress analysis and avoiding convergence issues or uncertainties in mechanical solutions. Furthermore, strictly adhering to the actual hoisting sequence ensures the installation steps are engineering-executable and can be directly used to guide on-site construction planning.

[0047] Retrieve the material property set and connection type set, perform finite element discretization processing on the construction step unit group sequence, and output the construction step finite element group sequence.

[0048] Specifically, the system retrieves material property sets and connection type sets from a central database. The material property set contains the mechanical properties of all steel materials used in the steel structure, such as elastic modulus, Poisson's ratio, density, and yield strength. The connection type set defines how components are connected, including welded connections, bolted friction connections, bolted bearing connections, hinged connections, and rigid connections. Different connection methods affect the transmitted stiffness and constraint conditions. Elastic modulus measures a material's resistance to elastic deformation; for steel, it is typically 2.0 × 10⁵ MPa. Poisson's ratio is the ratio of transverse strain to longitudinal strain; for steel, it is typically 0.3. Density is used to calculate the structure's self-weight; for steel, it is 7850 kg / m³. Yield strength is the stress value at which a material begins to undergo plastic deformation; for example, the yield strength of Q355 steel is 355 MPa. A rigid connection can fully transmit bending moment and shear force at the connection point, and the angle between components remains unchanged. A hinged connection can only transmit shear force and cannot transmit bending moment. For example, the component numbered GZ-1 is made of Q355B and has an elastic modulus of 2.0×105MPa; the connection numbered LJ-5 is a rigid connection, while LJ-8 is a hinged connection.

[0049] The process iterates through the sequence of construction step unit groups, performing finite element discretization on each group. For the first step, the finite element model is a model containing only the foundation. The finite element model of the previous construction step is copied as the base. All newly installed components contained in the current construction step unit group are added to the base model. Simultaneously, based on the component ID, appropriate material properties are assigned to them from the material property set. Connections between the newly installed components and the existing structure are processed according to the connection type set. After completing all additions and settings for the current step, the complete finite element model in this state is saved and included as part of the construction step finite element group sequence. This process is repeated until all steps in the construction step unit group sequence are processed, resulting in the construction step finite element group sequence. The construction step finite element group sequence is a set of finite element models formed after discretizing each construction step, with each model representing a state in the construction process.

[0050] Environmental data is retrieved based on the construction coordinates and schedule of the steel structure building to obtain time-varying data of the wind-temperature coupling field mapped to the schedule.

[0051] Specifically, the construction coordinates and schedule of the steel structure building are obtained. The construction coordinates are the latitude and longitude coordinates of the steel structure building on site or the origin coordinates of the local construction coordinate system. They are obtained from the BIM model or the overall construction plan and are used for geolocation to determine from which geographical location to obtain meteorological data. The schedule is the construction organization design or network plan of the project, which clarifies the start and end dates of each section and sub-item of the project.

[0052] Environmental data is retrieved based on construction coordinates and the schedule. An API interface connects to a historical meteorological database. The spatial scope of the data retrieval is determined by the construction coordinates, and the time scope is determined by the total project duration. Each task in the schedule is matched with a timestamp in the historical meteorological database to obtain time-varying data of the wind-temperature coupled field. This data represents the physical field formed by wind and temperature in both space and time; they are coupled because temperature changes affect air density, thus influencing wind pressure, while wind speed affects convective heat transfer on the structural surface. The retrieved environmental data is precisely aligned with each time node or time period in the schedule to ensure that the simulation of a particular day's construction conditions reflects the actual or potential environmental conditions of that day. In other words, for each simulation point in time, there is a dataset covering the structural space, including wind speed vectors and temperature scalars. This shift from using fixed, conservative design loads to using dynamic, time-varying loads that realistically reflect specific weather conditions during construction significantly improves the realism and accuracy of the simulation results.

[0053] The time-varying data of the wind-temperature coupling field are implanted into the standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform.

[0054] Furthermore, this application also includes the following steps: standardizing and reconstructing the time-varying data of the wind-temperature coupled field to obtain a spatiotemporal four-dimensional matrix, wherein the data dimensions of the spatiotemporal four-dimensional matrix include spatial coordinates, time steps, wind speed vectors, and temperature scalars; based on the spatiotemporal four-dimensional matrix, performing dual-channel physical field transformation processing through the physical field transformation interface of the standard finite element platform to obtain nodal force load vectors and material thermal expansion coefficients, wherein the nodal force load vectors are obtained by mapping wind speed field data through fluid dynamics formulas, and the material thermal expansion coefficients are obtained by updating material nonlinear parameters driven by temperature field data; creating an environmental field coupler in the solver kernel of the standard finite element platform, and applying the environmental field coupler to dynamically superimpose the nodal force load vectors and material thermal expansion coefficients onto the structural equilibrium equations, outputting the local finite element platform.

[0055] Specifically, the time-varying data of the wind-temperature coupled field are reconstructed through format standardization to form a spatiotemporal four-dimensional matrix including spatial coordinates, time steps, wind speed vectors, and temperature scalars. In other words, the data in the time-varying data of the wind-temperature coupled field are formatted and regularized into a spatiotemporal four-dimensional matrix to describe the actual environmental impact on different locations of the structure at a given moment. For example, a data unit in the matrix might have coordinates = [120, 50, 240], time = November 15th, 14:00, wind speed = [15.0, 0.0, 0.0] m / s, and temperature = 8.0℃.

[0056] The physics field conversion interface reads the wind speed vector from the four-dimensional matrix. Based on fluid dynamics formulas, the wind speed is converted into wind pressure, which is then multiplied by the area of ​​the component acting on it, ultimately yielding the nodal force load vector acting on the nodes of the finite element model. The temperature scalar from the four-dimensional matrix is ​​also read. According to materials science models, temperature changes drive updates to material parameters. For example, at an ambient temperature of 8°C, the coefficient of thermal expansion of steel can still be considered 1.2 × 10⁻⁵ / °C. The physics field conversion interface is a set of predefined algorithms or functions specifically designed to convert data from one physics field to another. Dual-channel physics field conversion processing refers to two independent data conversion processes executed in parallel: converting wind speed data into wind loads acting on structural nodes and converting temperature data into changes in the coefficient of thermal expansion of materials. The nodal force load vector is a mathematical vector obtained through the conversion, containing the magnitude and direction of the wind load force acting on each node of the finite element model; the coefficient of thermal expansion of materials refers to the rate at which the length of a material changes when its temperature increases by 1°C.

[0057] An environmental field coupler is created within the solver kernel of the standard finite element method (FEM) platform. This is achieved by writing core code using the user subroutine interface provided by the FEM software to create the environmental field coupler within the solver kernel. The environmental field coupler is a functional module used to dynamically superimpose the external environmental physical fields onto the structure. At each step of the solution process, the environmental field coupler instantly queries the spatiotemporal four-dimensional matrix based on the current physical time of the simulation to obtain the wind speed and temperature data. It then calls the dual-channel physics transformation logic to quickly calculate the current nodal force load vector and the updated value of the material's thermal expansion coefficient due to temperature changes. The calculated nodal force vector is dynamically superimposed onto the structural equilibrium equations, and the updated material thermal expansion coefficient is first converted into a thermal expansion effect and also superimposed onto the structural equilibrium equations.

[0058] Based on the updated structural equilibrium equations, a local finite element platform was obtained, which can realistically reflect the dynamic effects of the environment. Through kernel-level coupling, true real-time linkage between environmental load and structural response analysis was achieved, enabling the simulation process to perfectly reproduce the continuous changes in real-world environmental conditions. Instability risks were diagnosed in real time after each loading step, eliminating the risk of misjudgment caused by load simplification and single working conditions.

[0059] Using the hoisting sequence as the step-by-step loading sequence, step-by-step loading simulation is performed on the finite element group sequence of the construction steps in the local finite element platform. After each loading step, the instability risk is diagnosed in real time, and multiple instability risk characteristic parameter sequences of multiple instability risk nodes are output.

[0060] Furthermore, this application also includes the following steps: using the hoisting sequence as the step loading sequence, retrieving and activating the first construction step finite element group from the construction step finite element group sequence; after loading the first construction step finite element group on the local finite element platform, performing multi-threaded instability risk diagnosis, and outputting multiple first instability risk characteristic parameters of the first instability risk node under various load scenarios, wherein the multi-threaded instability risk diagnosis covers buckling diagnosis, geometric diagnosis, and material diagnosis, and the various load scenarios cover permanent loads, temporary loads, and environmentally coupled loads; aggregating the multiple first instability risk characteristic parameters, and outputting a first instability risk characteristic parameter sequence; and recursively executing the step loading simulation and instability risk diagnosis of the construction step finite element group sequence according to the hoisting sequence until the multiple instability risk characteristic parameter sequences are output.

[0061] Specifically, the hoisting sequence is used as the step-by-step loading sequence, meaning the simulation process completely follows the actual hoisting sequence. The corresponding component groups are activated step-by-step in the finite element model according to the order of component installation, simulating the structural formation process. The first construction step finite element group is retrieved and activated from the construction step finite element group sequence, and then loaded into the local finite element platform.

[0062] Multi-threaded instability risk diagnosis is performed on a local finite element platform, which involves simultaneously launching multiple computational tasks to analyze the stability of the current model from different mechanical dimensions to comprehensively identify risks. Multi-threaded instability risk diagnosis covers buckling diagnosis, geometric diagnosis, and material diagnosis. Buckling diagnosis solves for the minimum buckling eigenvalues ​​of the structure, either globally or locally, to determine whether a component or local region is in a critical stable state. Geometric diagnosis analyzes the nodal displacement growth trend within a nonlinear solution framework considering large deformations, identifying risks of geometric softening or deformation jumps. Material diagnosis utilizes a material constitutive model to monitor whether cross-sectional stress exceeds limits, whether local areas have entered the plastic stage, or whether stress concentration and fatigue accumulation exist.

[0063] Independent solutions were performed under three different load scenarios: permanent load, temporary load, and environmental coupled load. Multiple first instability risk characteristic parameters corresponding to the first instability risk node were obtained, clearly recording the safety state of the finite element set in the first construction step under various load scenarios. Permanent loads are constant loads such as the structure's self-weight and curtain wall loads; temporary loads are variable loads that change with the construction stage, such as construction loads and crane loads; environmental coupled loads are dynamic loads calculated from the wind-temperature coupled field, i.e., additional loads generated by the combined effects of aerodynamic forces applied by the wind field and thermal expansion deformation driven by the temperature field.

[0064] Instability risk characteristic parameters are indicators that characterize the potential instability of a structure, obtained through multi-threaded instability risk diagnosis. These include critical load factors, maximum displacement, maximum stress, and stress ratio. Multiple first-stage instability risk characteristic parameters are aggregated to obtain a first-stage instability risk characteristic parameter sequence, recording the safety status of the first stage under various possible working conditions. For example, assuming the first construction step involves installing four 400×400×13×21 steel columns, 9.0m high, made of Q355 steel. Based on the steel density (7850kg / m³) and component volume, the self-weight of a single column is calculated to be 1.2kN, with an additional dead load of 1.5kN / column. The total permanent load is (1.2+1.5)*4=10.8kN. The construction live load is 2.5kN / column, and the total temporary load is 10kN. Based on the wind-temperature coupled field data, with a wind speed of 16 m / s acting on the column, the concentrated force acting on the top node of each column is calculated to be 12.8 kN, and the total wind load is 12.8 kN / column × 4 columns = 51.2 kN. The ambient temperature difference is 19℃, and the coefficient of thermal expansion of steel is 1.2 × 10⁻⁵ / ℃, resulting in a thermal strain of ε = 1.2e⁻⁵ × 19 = 2.28 × 10⁻⁴. Eigenvalue buckling analysis is performed on the structure to solve for its critical instability load. The critical load factor λ = 1.8 is obtained, meaning that when all loads increase to 1.8 times, the structure will experience elastic instability. The requirement for temporary structures is λ ≥ 2.0, which does not meet the code requirements, indicating a risk of overall instability. Static analysis shows that the maximum displacement of the structure under the load combination is Δ = 42 mm, and the ratio of displacement to column height is 1 / 214. The horizontal displacement limit for temporary structures during the construction phase is usually H / 250, i.e., 36 mm. 42 mm > 36 mm, which does not meet the code requirements, indicating insufficient structural stiffness. Static analysis also shows that the stress σ = 185 MPa at the most unfavorable section of the member, and the stress ratio SR = 185 / 355 = 0.52. Since SR = 0.52 < 1.0, this meets the code requirements, and the member strength is within the safe range. The diagnostic results are aggregated to output a comprehensive risk assessment for this construction step, namely, the first instability risk characteristic parameter sequence as follows: Construction Step 1, buckling safety factor 1.8 (exceeding the standard), maximum displacement 42 mm (exceeding the standard), maximum stress ratio 0.52 (qualified).

[0065] Based on the hoisting sequence, the next construction step's finite element set is automatically retrieved and activated, loaded onto the local finite element platform, and multi-threaded instability risk diagnosis is performed to obtain multiple corresponding instability risk characteristic parameters. This process is repeated until the entire construction step finite element set sequence is completed, ultimately outputting a sequence of multiple instability risk characteristic parameters covering all construction steps.

[0066] Furthermore, this application also includes the following steps: using the hoisting sequence as the step loading sequence, retrieving and activating the second construction step finite element set from the construction step finite element set sequence; loading the second construction step finite element set on the local finite element platform, and performing time-varying tracking of the multiple first instability risk characteristic parameters during the multi-threaded instability risk diagnosis process; if the multiple first instability risk characteristic parameters fluctuate, performing parameter correction iterations based on the historical worst-case value update rule until the construction step finite element set sequence is an empty set, and outputting multiple first iteratively corrected instability characteristic parameters.

[0067] Specifically, the loading sequence is based on the hoisting order. The second construction step's finite element set is retrieved and activated from the construction step's finite element set sequence. The second construction step's finite element set is then loaded onto the local finite element platform, and multi-threaded instability risk diagnosis is performed to obtain the risk parameters of the second construction step itself. During the diagnosis process, time-varying tracking is performed in parallel, meaning that not only are the risk parameters of the current construction step monitored, but the changing trends of key risk parameters identified in all previous construction steps are also continuously monitored and recorded.

[0068] If multiple first instability risk characteristic parameters fluctuate, meaning the values ​​of the first instability risk characteristic parameters change, the historical worst-case value update rule is activated. This rule assesses risks occurring at a specific location or pattern throughout the entire construction process using the most unfavorable value across all construction steps—based on the most vulnerable state, not the currently improved state. The newly calculated value is compared to the stored historical worst-case values, and the more dangerous value is selected as the updated historical worst-case value. If the parameter does not fluctuate, the original value is retained. For example: if the current buckling characteristic value is smaller, it is updated as the new reference risk value; if the current node displacement growth rate is higher, the original record is replaced; if the current plastic strain peak increases, it is updated and saved.

[0069] As the construction steps are executed recursively, this step is repeated for the finite element set sequence of each construction step until all finite element sets of all construction steps are loaded. This results in the final output of multiple first-iteration corrected instability characteristic parameters covering the entire construction period. These parameters are the final instability risk parameter sequence obtained after recursive updates and hazard value amplification screening in all construction stages. They are used to determine the instability sensitive areas and high-risk nodes throughout the entire construction process.

[0070] By adopting a diagnostic mechanism that combines step-by-step loading with time-varying risk tracking, the system captures time-varying instability risks during the construction process that cannot be identified by static modeling. This yields a sequence of the most dangerous instability risk characteristics covering the entire construction phase, preventing the neglect of extreme dangerous states that occurred in the early stages due to the subsequent stabilization of the structure, and improving the safety of steel structure construction.

[0071] Based on the multiple instability risk characteristic parameter sequences, perform instability correction closed-loop iterations until multiple instability correction strategies covering the entire construction instability landscape are output.

[0072] Furthermore, this application also includes the following steps: matching multiple sets of initialization correction strategies based on structural attributes to the multiple instability risk characteristic parameter sequences; triggering strategy combinations in a hierarchical manner based on the strategy substitutability of the multiple sets of initialization correction strategies to obtain a strategy adaptation priority sequence; and progressively verifying the effectiveness of the strategy adaptation priority sequence based on virtual construction playback until the multiple instability correction strategies covering the entire construction instability landscape are output.

[0073] Specifically, multiple instability risk characteristic parameter sequences are read, and multiple sets of initialization correction strategies are matched from the strategy library based on the structural attributes of each risk point. Structural attributes refer to the characteristics of structural parts or components that trigger instability risks, including type, geometric features, and mechanical state. Initialization correction strategies are preliminary risk intervention measures determined based on structural attributes and risk characteristics, such as adding temporary supports, adjusting the hoisting sequence, and increasing connection stiffness, used to reduce the risk of local or overall structural instability.

[0074] Strategy substitutability refers to the functional equivalence or complementarity between different strategies. For example, guy ropes and temporary supports are functionally equivalent and interchangeable in improving the stability of independent columns; while increasing the cross-section of components is considered an irreplaceable strategy due to low construction feasibility. This paper analyzes the substitutability of multiple initialization correction strategies, triggers strategy combinations in a tiered manner, and ranks and combines multiple feasible strategies based on indicators such as substitutability, cost, and ease of construction, forming a trial order from optimal to suboptimal, generating a strategy adaptation priority sequence. The strategy adaptation priority sequence is an ordered list of strategies that indicates which solution should be tried first when a risk is detected, and if that fails, the suboptimal solution should be tried.

[0075] The process begins with virtual construction replay, where each strategy in the priority sequence is progressively validated for effectiveness. The entire construction process is simulated again on the local finite element platform, with the proposed corrective strategies pre-implemented to verify their effectiveness in mitigating risks. Virtual construction replay tests are performed on each strategy sequentially according to the priority sequence until a validated strategy is found. This process is repeated for each identified risk point, ultimately outputting a comprehensive instability correction strategy report covering the entire construction instability landscape, clearly specifying the validated measures to be taken for each risk point.

[0076] For example, suppose the stability of four independent columns is diagnosed as insufficient. The structural attributes of the risk point include the risk type being overall instability, the risk location being an independent steel column, and the slenderness ratio being 100. Three matching initialization strategies are provided: Strategy A involves installing bidirectional guy ropes (16mm diameter steel strands) at the top of the columns, anchored to the ground; Strategy B involves installing temporary horizontal supports between the columns; and Strategy C replaces the columns with larger cross-section columns. Based on substitutability—that is, A and B can be interchanged to achieve stability—a priority sequence is generated as Strategy A, Strategy B, and Strategy C. In the simulation model, guy rope models are added to the four columns, assigning them realistic material properties and prestress, and the entire construction process is replayed. Simulation results show that from the first step, the critical load factor λ of the structure is consistently greater than 2.5, the displacement meets the requirements, and there is no interference with subsequent hoisting. Strategy A is verified as effective. If Strategy A is ineffective, Strategy B is automatically activated for a second round of replay verification. Since Strategy A has been proven effective, at the start of construction step 1, bidirectional guy ropes were installed for the four independent columns as a final corrective strategy for this risk point, and this was included in the overall report. For other risk points, the above steps were repeated until multiple instability correction strategies covering the overall construction instability situation were obtained.

[0077] By matching risk characteristic sequences with structural attributes, a direct conversion from risk identification to feasible intervention measures is achieved. Through strategy substitutability and priority ranking, on-site strategy optimization is realized, reducing safety intervention costs. Virtual construction replay is used for progressive verification, enabling the correction strategy to cover potential instability risks throughout the entire construction process, improving the reliability and executability of risk control. The final output instability correction strategy can directly guide on-site operations, realizing closed-loop control of dynamic safety management in construction.

[0078] In summary, the finite element analysis-based steel structure stability simulation and evaluation method provided in this application has the following technical advantages: The steel structure geometric model is exported from BIM software; the steel structure geometric model is decomposed in reverse based on the hoisting sequence to obtain a sequence of construction step unit groups; the material property set and connection type set are retrieved, and the sequence of construction step unit groups is discretized by finite element method to output a sequence of construction step finite element groups; environmental data is retrieved according to the construction coordinates and schedule of the steel structure building to obtain time-varying data of the wind-temperature coupling field mapped to the schedule; the time-varying data of the wind-temperature coupling field is implanted into the standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform; step-by-step loading simulation is performed on the sequence of construction step finite element groups in the local finite element platform with the hoisting sequence as the step loading sequence, and the instability risk is diagnosed in real time after each loading step, outputting multiple instability risk characteristic parameter sequences of multiple instability risk nodes; instability correction closed-loop iteration is performed based on the multiple instability risk characteristic parameter sequences until multiple instability correction strategies covering the overall construction instability are output. In other words, the geometric model of the steel structure is reversed and divided into construction step units according to the hoisting sequence. Each construction step is discretized using finite element methods by calling the structural material library and connection type library. Based on the construction coordinates and schedule, time-varying data of the wind-temperature coupling field are retrieved and mapped, and then used as time-varying boundary conditions to be implanted into the local finite element simulation platform. The simulation is performed step by step according to the hoisting sequence, and the instability risk is diagnosed in real time after each loading step. Instability correction is performed based on the risk characteristics, realizing the forward-looking prediction of instability risk throughout the entire steel structure construction process, thus improving the safety and efficiency of steel structure construction.

[0079] Example 2: Based on the same inventive concept as the finite element analysis-based steel structure stability simulation and evaluation method in Example 1, this application also provides a finite element analysis-based steel structure stability simulation and evaluation platform. Please refer to the appendix. Figure 2 The finite element analysis-based steel structure stability simulation and evaluation platform includes: The model export module 11 is used to export the steel structure geometric model from BIM software; the reverse decomposition module 12 is used to reverse decompose the steel structure geometric model based on the hoisting sequence to obtain a construction step unit group sequence; the discretization processing module 13 is used to retrieve the material property set and connection type set, perform finite element discretization processing on the construction step unit group sequence, and output the construction step finite element group sequence; the data retrieval module 14 is used to retrieve environmental data based on the construction coordinates and schedule of the steel structure building to obtain time-varying data of the wind-temperature coupling field mapped to the schedule; the dynamic coupling module 15 is used for... The time-varying data of the wind-temperature coupling field are implanted into the standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform. The distributed simulation module 16 is used to perform step-by-step loading simulation on the construction step finite element group sequence in the local finite element platform with the hoisting sequence as the step loading time sequence, and to diagnose the instability risk in real time after each loading step, and output multiple instability risk characteristic parameter sequences of multiple instability risk nodes. The closed-loop iteration module 17 is used to perform instability correction closed-loop iteration based on the multiple instability risk characteristic parameter sequences until multiple instability correction strategies covering the overall construction instability are output.

[0080] Furthermore, the reverse decomposition module 12 in the finite element analysis-based steel structure stability simulation and evaluation platform is also used for: extracting pre-stored hoisting sequences from the construction management database and constructing steel component installation order dependencies based on the hoisting sequences; parsing the geometric connection relationships of the steel structure geometric model to generate a spatial topological adjacency matrix; performing temporal dependency compensation on the spatial topological adjacency matrix based on the steel component installation order dependencies to output a temporal topological correlation matrix; and recursively cutting the temporal topological correlation matrix based on the statically determinate isolation criterion to output the construction step unit group sequence, wherein the steel components within each construction step unit group in the construction step unit group sequence do not affect each other.

[0081] Furthermore, the inverse decomposition module 12 in the finite element analysis-based steel structure stability simulation and evaluation platform is also used for: traversing the temporal topological correlation matrix to perform statically determinate subgraph identification based on preset statically determinate judgment rules, obtaining a first component subset; performing recursive cutting operations on the first component subset, outputting a first local step unit group sequence; adding the first component subset to the statically determinate identification taboo domain, and then performing statically determinate subgraph identification and updating the temporal topological correlation matrix to obtain a second component subset; iteratively performing statically determinate subgraph identification and recursive cutting operations on the temporal topological correlation matrix until the temporal topological correlation matrix is ​​an empty set, obtaining multiple local step unit group sequences; reorganizing the multiple local step unit group sequences according to the construction sequence, and outputting the construction step unit group sequence.

[0082] Furthermore, the inverse decomposition module 12 in the steel structure stability simulation and evaluation platform based on finite element analysis is also used for: the statically determinate determination rules include geometric invariance, boundary independence and load closure.

[0083] Furthermore, the inverse decomposition module 12 in the steel structure stability simulation and evaluation platform based on finite element analysis is also used for: S1: injecting virtual boundary constraints based on the boundary node structural attributes of the first component subset to generate a virtual boundary constraint set and a reaction load vector set; S2: cutting the rows and columns of the first component subset and adding virtual boundary node rows to generate a reduced-order temporal topological correlation matrix; S3: pushing the first component subset into a last-in-first-out storage stack; S4: using the reduced-order temporal topological correlation matrix as the new input, iterating steps S1~S3 until the reduced-order temporal topological correlation matrix is ​​an empty set, then popping the component update subset sequence from the storage stack in reverse order and outputting the first local step unit group sequence; S5: mapping the virtual boundary constraint set and the reaction load vector set to the first local step unit group sequence to apply load boundary conditions.

[0084] Furthermore, the dynamic coupling module 15 in the finite element analysis-based steel structure stability simulation and evaluation platform is also used for: format standardization and reconstruction of the time-varying data of the wind-temperature coupling field to obtain a spatiotemporal four-dimensional matrix, wherein the data dimensions of the spatiotemporal four-dimensional matrix include spatial coordinates, time steps, wind speed vectors, and temperature scalars; based on the spatiotemporal four-dimensional matrix, performing dual-channel physical field transformation processing through the physical field transformation interface of the standard finite element platform to obtain nodal force load vectors and material thermal expansion coefficients, wherein the nodal force load vectors are obtained by mapping the wind speed field data through fluid dynamics formulas, and the material thermal expansion coefficients are obtained by updating the material nonlinear parameters driven by the temperature field data; creating an environmental field coupler in the solver kernel of the standard finite element platform, and applying the environmental field coupler to dynamically superimpose the nodal force load vectors and material thermal expansion coefficients to the structural equilibrium equations, and outputting the local finite element platform.

[0085] Furthermore, the distributed simulation module 16 in the steel structure stability simulation and evaluation platform based on finite element analysis is also used for: retrieving and activating the second construction step finite element group from the construction step finite element group sequence, taking the hoisting sequence as the step loading sequence; loading the second construction step finite element group on the local finite element platform and performing time-varying tracking of the multiple first instability risk characteristic parameters during the multi-threaded instability risk diagnosis process; if the multiple first instability risk characteristic parameters fluctuate, performing parameter correction iterations based on the historical worst-case value update rule until the construction step finite element group sequence is an empty set, and outputting multiple first iteratively corrected instability characteristic parameters.

[0086] Furthermore, the distributed simulation module 16 in the steel structure stability simulation and evaluation platform based on finite element analysis is also used for: retrieving and activating the first construction step finite element group from the construction step finite element group sequence, taking the hoisting sequence as the step loading sequence; after loading the first construction step finite element group on the local finite element platform, performing multi-threaded instability risk diagnosis, and outputting multiple first instability risk characteristic parameters of the first instability risk node under various load scenarios, wherein the multi-threaded instability risk diagnosis covers buckling diagnosis, geometric diagnosis, and material diagnosis, and the various load scenarios cover permanent loads, temporary loads, and environmental coupling loads; aggregating the multiple first instability risk characteristic parameters and outputting the first instability risk characteristic parameter sequence; and recursively executing the step loading simulation and instability risk diagnosis of the construction step finite element group sequence according to the hoisting sequence until the multiple instability risk characteristic parameter sequences are output.

[0087] Furthermore, the closed-loop iteration module 17 in the steel structure stability simulation and evaluation platform based on finite element analysis is also used for: matching multiple sets of initialization correction strategies based on structural properties to the multiple instability risk characteristic parameter sequences; triggering strategy combinations in a hierarchical manner based on the strategy replaceability of the multiple sets of initialization correction strategies to obtain a strategy adaptation priority sequence; and progressively verifying the effectiveness of the strategy adaptation priority sequence based on virtual construction playback until the multiple instability correction strategies covering the entire construction instability landscape are output.

[0088] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The steel structure stability simulation evaluation method and specific examples based on finite element analysis in the aforementioned embodiment one are also applicable to the steel structure stability simulation evaluation platform based on finite element analysis in this embodiment. Through the foregoing detailed description of the steel structure stability simulation evaluation method based on finite element analysis, those skilled in the art can clearly understand the steel structure stability simulation evaluation platform based on finite element analysis in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[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.

[0090] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A simulation and evaluation method for the stability of steel structures based on finite element analysis, characterized in that, include: Exporting steel structure geometric models from BIM software; Based on the reverse decomposition of the steel structure geometric model according to the hoisting sequence, a sequence of construction step unit groups is obtained; Retrieve the material property set and connection type set, perform finite element discretization on the construction step unit group sequence, and output the construction step finite element group sequence. Environmental data is retrieved based on the construction coordinates and schedule of the steel structure building to obtain time-varying data of the wind-temperature coupling field mapped to the schedule. The time-varying data of the wind-temperature coupling field are implanted into the standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform. Using the hoisting sequence as the step loading sequence, step loading simulation is performed on the construction step finite element group sequence in the local finite element platform, and the instability risk is diagnosed in real time after each loading step, and multiple instability risk characteristic parameter sequences of multiple instability risk nodes are output. Based on the multiple instability risk characteristic parameter sequences, perform instability correction closed-loop iteration until multiple instability correction strategies covering the entire construction instability landscape are output; The method involves embedding the time-varying data of the wind-temperature coupled field into a standard finite element platform to perform dynamic coupling of the environmental field and generate a local finite element platform. The time-varying data of the wind-temperature coupled field are reconstructed by format standardization to obtain a spatiotemporal four-dimensional matrix, wherein the data dimensions of the spatiotemporal four-dimensional matrix include spatial coordinates, time steps, wind speed vector and temperature scalar; Based on the spatiotemporal four-dimensional matrix, a dual-channel physical field transformation process is performed through the physical field transformation interface of the standard finite element platform to obtain the nodal force load vector and the material thermal expansion coefficient. The nodal force load vector is obtained by mapping wind speed field data through fluid dynamics formulas, and the material thermal expansion coefficient is obtained by updating the material nonlinear parameters driven by temperature field data. An environmental field coupler is created in the solver kernel of the standard finite element platform, and the environmental field coupler is applied to dynamically superimpose the nodal force load vector and the material thermal expansion coefficient to the structural equilibrium equation, and the local finite element platform is output.

2. The method for simulating and evaluating the stability of steel structures based on finite element analysis as described in claim 1, characterized in that, Based on the reverse decomposition of the steel structure geometric model according to the hoisting sequence, a sequence of construction step unit groups is obtained. The method includes: Extract the pre-stored hoisting sequence from the construction management database, and construct the steel component installation order dependency relationship based on the hoisting sequence; The geometric connection relationships of the steel structure geometric model are analyzed to generate a spatial topological adjacency matrix; Based on the installation order dependency of the steel components, the spatial topological adjacency matrix is ​​compensated for temporal dependency, and a temporal topological association matrix is ​​output. Based on the statically determinate isolation criterion, the temporal topological correlation matrix is ​​recursively cut in reverse to output the construction step unit group sequence, wherein the steel components within each construction step unit group in the construction step unit group sequence do not affect each other.

3. The method for simulating and evaluating the stability of steel structures based on finite element analysis as described in claim 2, characterized in that, The method involves recursively cutting the temporal topological correlation matrix based on the statically determinate isolation criterion to output the sequence of construction step unit groups. Based on the preset statically determinate determination rules, the statically determinate subgraphs are identified by traversing the temporal topological correlation matrix to obtain the first component subset; Perform a recursive cutting operation on the first component subset to output the first local step unit group sequence; After adding the first component subset to the statically determinate recognition taboo domain, the statically determinate subgraph recognition update is performed on the temporal topological correlation matrix to obtain the second component subset; The statically determinate subgraph identification and recursive cutting operation of the temporal topological correlation matrix are performed iteratively until the temporal topological correlation matrix is ​​an empty set, resulting in multiple local step unit group sequences. Reorganize the multiple local step unit group sequences according to the construction sequence, and output the construction step unit group sequence.

4. The method for simulating and evaluating the stability of steel structures based on finite element analysis as described in claim 3, characterized in that, The method involves recursively cutting the first component subset to output a first local step unit group sequence, wherein the recursive cutting operation is performed on the first component subset. S1: Based on the structural attributes of the boundary nodes of the first component subset, inject virtual boundary constraints to generate a set of virtual boundary constraints and a set of reaction load vectors; S2: Cut the rows and columns of the first component subset and add virtual boundary node rows to generate a reduced-order temporal topological correlation matrix; S3: Push the first component subset into the last-in-first-out storage stack; S4: Using the reduced-order temporal topological correlation matrix as the new input, iterate steps S1~S3 until the reduced-order temporal topological correlation matrix is ​​an empty set. Then, pop the component update subset sequence from the storage stack in reverse order and output the first local step unit group sequence. S5: Map the virtual boundary constraint set and reaction load vector set to the first local step unit group sequence to apply load boundary conditions.

5. The method for simulation and evaluation of steel structure stability based on finite element analysis as described in claim 1, characterized in that, Using the hoisting sequence as the step-by-step loading sequence, a step-by-step loading simulation is performed on the finite element group sequence of the construction steps in the local finite element platform. After each loading step, the instability risk is diagnosed in real time, and multiple instability risk characteristic parameter sequences for multiple instability risk nodes are output. The method includes: Using the hoisting sequence as the step loading sequence, the first construction step finite element group is retrieved and activated from the construction step finite element group sequence; After loading the first construction step finite element set on the local finite element platform, multi-threaded instability risk diagnosis is performed, and multiple first instability risk characteristic parameters of the first instability risk node under various load scenarios are output. The multi-threaded instability risk diagnosis covers buckling diagnosis, geometric diagnosis and material diagnosis, and the various load scenarios cover permanent load, temporary load and environmental coupling load. Aggregate the multiple first instability risk characteristic parameters and output the first instability risk characteristic parameter sequence; Based on the hoisting sequence, the step-by-step loading simulation and instability risk diagnosis of the construction step finite element sequence are recursively executed until the multiple instability risk characteristic parameter sequences are output.

6. The method for simulation and evaluation of steel structure stability based on finite element analysis as described in claim 5, characterized in that, The method further includes: Using the hoisting sequence as the step loading sequence, the second construction step finite element set is retrieved and activated from the construction step finite element set sequence; During the process of loading the second construction step finite element set on the local finite element platform and performing multi-threaded instability risk diagnosis, time-varying tracking of the multiple first instability risk characteristic parameters is performed. If the multiple first instability risk characteristic parameters fluctuate, parameter correction iterations are performed based on the historical worst-case value update rule until the construction step finite element sequence is an empty set, and multiple first iteration corrected instability characteristic parameters are output.

7. The method for simulation and evaluation of steel structure stability based on finite element analysis as described in claim 1, characterized in that, Based on the multiple instability risk characteristic parameter sequences, an instability correction closed-loop iteration is performed until multiple instability correction strategies covering the entire construction instability landscape are output. The method includes: Multiple initialization correction strategies are based on structural property matching of the multiple instability risk characteristic parameter sequences; Based on the policy substitutability of the multiple initialization correction strategies, a hierarchical triggering strategy combination is obtained to obtain a policy adaptation priority sequence. Based on virtual construction playback, the effectiveness of the strategy is progressively verified by adapting the priority sequence of the strategy until the multiple instability correction strategies covering the overall construction instability are output.

8. The method for simulation and evaluation of steel structure stability based on finite element analysis as described in claim 3, characterized in that, The statically determinate criteria include geometric invariance, boundary independence, and load closure.

9. A simulation and evaluation platform for the stability of steel structures based on finite element analysis, characterized in that, The steps for implementing the steel structure stability simulation and evaluation method based on finite element analysis according to any one of claims 1 to 8, wherein the steel structure stability simulation and evaluation platform based on finite element analysis includes: The model export module is used to export steel structure geometric models from BIM software; The reverse decomposition module is used to reverse decompose the geometric model of the steel structure based on the hoisting sequence to obtain the sequence of construction step unit groups; The discretization module is used to retrieve the material property set and connection type set, perform finite element discretization on the construction step unit group sequence, and output the construction step finite element group sequence. The data retrieval module is used to retrieve environmental data based on the construction coordinates and schedule of the steel structure building, and obtain time-varying data of the wind-temperature coupling field mapped to the schedule. The dynamic coupling module is used to implant the time-varying data of the wind-temperature coupling field into the standard finite element platform, perform dynamic coupling of the environmental field, and generate a local finite element platform. The distributed simulation module is used to perform step-by-step loading simulation on the construction step finite element group sequence in the local finite element platform with the hoisting sequence as the step loading time sequence, and to diagnose instability risk in real time after each loading step, and output multiple instability risk characteristic parameter sequences of multiple instability risk nodes. The closed-loop iteration module is used to perform instability correction closed-loop iteration based on the multiple instability risk characteristic parameter sequences until multiple instability correction strategies covering the entire construction instability landscape are output. The dynamic coupling module is also used for: The time-varying data of the wind-temperature coupled field are reconstructed by format standardization to obtain a spatiotemporal four-dimensional matrix, wherein the data dimensions of the spatiotemporal four-dimensional matrix include spatial coordinates, time steps, wind speed vector and temperature scalar; Based on the spatiotemporal four-dimensional matrix, a dual-channel physical field transformation process is performed through the physical field transformation interface of the standard finite element platform to obtain the nodal force load vector and the material thermal expansion coefficient. The nodal force load vector is obtained by mapping wind speed field data through fluid dynamics formulas, and the material thermal expansion coefficient is obtained by updating the material nonlinear parameters driven by temperature field data. An environmental field coupler is created in the solver kernel of the standard finite element platform, and the environmental field coupler is applied to dynamically superimpose the nodal force load vector and the material thermal expansion coefficient to the structural equilibrium equation, and the local finite element platform is output.

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