A modeling method of a finite element model of a steel structure combined joint
By optimizing data acquisition, preprocessing, and nonlinear mapping formulas, combined with nonlinear dynamic response updates, the problems of component synergy and load adaptability in modeling were solved, achieving accurate simulation and efficient modeling of the stress characteristics of steel structure nodes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- EASTERN GANSU UNIVERSITY
- Filing Date
- 2026-02-10
- Publication Date
- 2026-05-12
AI Technical Summary
Existing modeling methods ignore the synergistic effect of stress on nodal components, have poor adaptability to load simulation and seismic displacement loading, resulting in low modeling efficiency, large stress calculation errors, and inability to accurately adapt to the complex stress scenarios of new reinforced beam flange nodes.
Through data acquisition and preprocessing, an initial three-dimensional geometric model is constructed and geometric parameters are optimized. By combining multi-order nonlinear mapping formulas and nonlinear dynamic response update formulas, the collaborative positioning and stress characteristics of components are accurately quantified, enabling mesh generation and parameter assignment, and dynamic adjustment of stress state.
It improves the construction accuracy of finite element models, significantly enhances the accuracy of stress response simulation in complex scenarios, and provides reliable technical support for the design and seismic analysis of steel structure composite nodes.
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Figure CN121683392B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of finite element modeling methods, and more particularly to a finite element modeling method for composite steel structure nodes. Background Technology
[0002] As the core of force transmission in a building structure, the beam-column joint of a prefabricated steel frame directly determines the seismic safety of the overall structure. It is strongly correlated with section design parameters such as column axial compression ratio, column section type, flange thickness, and stiffener dimensions, as well as load conditions such as monotonic loads and low-cycle repeated loads. The accuracy of the finite element model of the joint directly affects the reliability of the seismic performance assessment results, making it a crucial link in the design and safety management of prefabricated steel structure engineering. Currently, prefabricated steel frame structures are increasingly widely used in the construction field, and new reinforced beam flange joints are being widely promoted due to their superior load-bearing performance. However, these joint components are complex, with significant collaborative load-bearing characteristics between the flange, stiffener, and side plates, placing higher demands on the adaptability and accuracy of the modeling methods. Low-cycle repeated load testing, as a mature and standardized method for simulating seismic loads, has been widely used for testing the mechanical performance of joints. Accurate adaptation of the displacement loading mode is necessary during the modeling process to truly reproduce the seismic stress state of the joint. However, existing modeling methods mostly adopt a single parameter assignment mode, ignoring the synergistic effect of stress on each node component, resulting in insufficient modeling targeting; in load simulation, they lack effective adaptation to seismic displacement loading, making it difficult to accurately reproduce the complex stress characteristics of node components; at the same time, model iteration and correction only focus on stress data comparison, without combining failure modes to carry out full-dimensional verification, resulting in low modeling efficiency, large stress calculation errors, and difficulty in adapting to the complex stress scenarios of new reinforced beam flange nodes. Summary of the Invention
[0003] This invention provides a modeling method for finite element models of composite steel structure nodes to solve the technical problems of ignoring the synergistic effect of node components in single parameter assignment, poor adaptability between load simulation and seismic displacement loading, and model correction focusing only on stress without combining failure mode verification, resulting in low modeling efficiency, large stress calculation errors, and inability to accurately adapt to different cross-sectional parameters and load conditions.
[0004] The present invention provides a modeling method for a finite element model of a steel structure composite node, comprising the following steps:
[0005] S1. Data is collected from the steel structure composite nodes to obtain the collected data; based on the collected data, preprocessing is performed to obtain the preprocessed data; based on the preprocessed data, an initial three-dimensional geometric model is constructed; based on the preprocessed data and the initial three-dimensional geometric model, optimization is performed to obtain the optimized geometric parameters;
[0006] S2. Based on the optimized geometric parameters, preprocessed data, and initial three-dimensional geometric model, output the initial finite element model of the steel structure composite precision nodes; based on the initial finite element model of the steel structure composite precision nodes, construct the nonlinear dynamic response update formula to obtain the equivalent stress.
[0007] Preferably, S1 specifically includes:
[0008] Based on the column axial compression ratio of the component in the preprocessed data, calculate the geometric parameter correction coefficient of the component; based on the preprocessed data and the geometric parameter correction coefficient of the component, calculate the optimized geometric parameters.
[0009] Preferably, S2 specifically includes:
[0010] Based on the optimized geometric parameters and the initial 3D geometric model, the mesh reference size is calculated; based on the mesh reference size and the preprocessed data, the mesh is generated.
[0011] Preferably, S2 specifically includes:
[0012] Based on the mesh generation, the geometric contribution ratio of the components is calculated using the initial 3D geometric model and optimized geometric parameters, and the component positioning calibration is performed.
[0013] Preferably, S2 specifically includes:
[0014] Based on the component positioning and calibration, parameters are assigned using the initial three-dimensional geometric model and preprocessed data to output a precise finite element initial model of the steel structure assembly nodes.
[0015] Preferably, S2 specifically includes:
[0016] Based on the initial finite element model of the steel structure composite precision nodes, the Mises stress of the components is extracted; based on the Mises stress of the components, the linear region division and stress correction terms are obtained.
[0017] Preferably, S2 specifically includes:
[0018] The nonlinear weighting coefficient of the component is calculated based on the geometric contribution ratio.
[0019] Preferably, S2 specifically includes:
[0020] The equivalent stress is calculated based on the nonlinear weighting coefficients of the components, the linear region division, and the stress correction term.
[0021] The beneficial effects of the technical solution of the present invention are:
[0022] 1. By adopting a standardized data collection and preprocessing process, the accuracy and reliability of the modeling data were ensured, laying a solid foundation for subsequent work.
[0023] 2. Based on the optimized formula of the multi-order nonlinear mapping formula, the problems of uneven mesh quality and component cooperative positioning deviation in traditional modeling are solved, which greatly improves the construction accuracy of finite element model.
[0024] 3. An innovative nonlinear dynamic response update formula was designed, which enabled the accurate capture of the nonlinear behavior of nodes under strong seismic loads, significantly improving the accuracy of stress response simulation in complex scenarios and providing reliable technical support for the design and seismic analysis of steel structure composite nodes. Attached Figure Description
[0025] Figure 1 This is a flowchart of a modeling method for a finite element model of a steel structure composite node according to the present invention. Detailed Implementation
[0026] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0028] See attached document Figure 1 The diagram illustrates a modeling method for a finite element model of a steel structure composite node according to an embodiment of the present invention. The method includes the following steps:
[0029] S1. Data is collected from the steel structure composite nodes to obtain the collected data; based on the collected data, preprocessing is performed to obtain the preprocessed data; based on the preprocessed data, an initial three-dimensional geometric model is constructed; based on the preprocessed data and the initial three-dimensional geometric model, optimization is performed to obtain the optimized geometric parameters.
[0030] First, data was collected for steel structure composite nodes, such as components including beam flanges, stiffeners, cover plates, and side plates. The collected data included: foundation design parameters, such as component cross-sectional area, cross-sectional type, actual height, and thickness, as well as column axial compression ratio; material mechanical parameters, such as steel elastic modulus and yield strength; and specimen dimensional parameters, such as reference height and reference cross-sectional area for 1 / 2 scaled-down components. All data collection methods were standardized within the professional field. Geometric dimensions were measured using high-precision vernier calipers. The column axial compression ratio was determined based on the "Code for Seismic Design of Buildings" and the engineering conditions. Material mechanical parameters were determined through standard tensile tests. Specimen dimensional parameters were determined by adapting existing experimental design standards to the actual engineering requirements, ensuring data accuracy and traceability. Furthermore, the collected data undergoes preprocessing to obtain preprocessed data. Specifically, for dimensional parameters, such as component cross-sectional area, actual component height, reference height of 1 / 2 scaled-down components, reference cross-sectional area, steel elastic modulus, and steel yield strength, the dimensional parameters are standardized by dividing them by a reference value, such as cross-sectional area / reference cross-sectional area, to convert the dimensional parameters into standardized parameters. Standardized data for the interval, such as standardized component cross-sectional areas, is used. For dimensionless parameters, such as column axial compression ratio, consistency checks are performed, and outliers deviating from the mean by three times the standard deviation are removed to ensure data reliability. Furthermore, based on the preprocessed data, conventional 3D geometric modeling techniques in ANSYS finite element software, such as solid modeling, are used to complete operations such as creating a new 3D geometric model file, assigning basic material properties, drawing components, and performing Boolean operations, thus initially generating the initial 3D geometric model of the steel structure composite nodes.
[0031] Based on the theory of geometric nonlinear mapping, the optimization formula is designed as a multi-order nonlinear mapping formula to optimize the mesh reference size and component cooperative positioning parameters. The core function of the component cooperative positioning parameters is to quantify and correct the component cooperative positioning deviation. By introducing a sinusoidal correction term, the cooperative influence of geometric deformation and material nonlinearity is accurately quantified. The optimization formula is as follows:
[0032]
[0033] in, The optimized geometric parameters are mainly used to optimize the component mesh reference size and component cooperative positioning parameters. The geometric parameters before optimization are the inputs to the optimization formula, including the standardized cross-sectional area of the component, the component cross-sectional type, the actual height of the component, and the reference height of the 1 / 2 scaled-down component, etc., which are derived from the preprocessed data and the collected data. This is an index of the components contained in the composite steel structure node. ; This represents the total number of components contained in the steel structure composite node; For the first The geometric parameter correction coefficients of the first component are used to characterize the first component. The geometric contribution of each component to the overall stress of the steel structure composite node is determined by linear interpolation based on the column axial compression ratio of the component in the preprocessed data and calibration using static test data of similar components. The static test data of similar components are the stress response data of similar components under different column axial compression ratios, obtained through standardized static test measurements. The value range is [insert range here]. ; For the first The standardized cross-sectional area of each component is derived from preprocessed data and is used to characterize the geometric size of the component's cross-section. For the first The actual height of each component is derived from the collected data and is used to characterize the longitudinal geometric dimensions of the component; The reference height for the component, i.e., the reference height for a 1 / 2 scaled-down component, is derived from the collected data; For the first The geometric powers of individual components are used to correct the influence of the actual height of the components on the overall optimized geometric parameters. Based on the correlation theory between cross-sectional geometric properties and stress response in mechanics of materials, and combined with the component cross-section type, the initial value of the geometric powers is determined. Then, based on the test data of the stress characteristics of steel structure composite nodes, the initial geometric parameters are obtained by substituting into a multi-order nonlinear mapping formula. The initial three-dimensional geometric model is improved based on the initial geometric parameters and imported into ANSYS finite element software for linear or nonlinear static analysis. The mechanical response data after analysis is extracted. Combined with the relevant accuracy requirements of existing steel structure design standards, the error between the analyzed mechanical response data and the true values of the test data of the stress characteristics of steel structure composite nodes is compared. If the error does not meet the standard, the initial value of the geometric powers is fine-tuned, and the above iterative process is repeated until the value that meets the modeling accuracy requirements is finally locked. The test data of the stress characteristics of steel structure composite nodes are obtained through mature and targeted overall node stress tests, and the value range is [insert range here]. ; For the first The geometric nonlinearity correction factor for each component is used to quantify the synergistic effect of geometric deformation and material nonlinearity. Stress-strain measurement data in the elastoplastic stage and the uniaxial tensile test report of the component material are obtained through uniaxial tensile tests of steel conducted according to specifications. The stress-strain curve of the component steel is extracted from the uniaxial tensile test report. The nonlinear least squares method is used to input the stress-strain measurement data in the elastoplastic stage, and a suitable nonlinear model is selected. ,in, For the fitted stress, For strain, based on the test stress and strain values, and combined with the steel grade, component cross-section type, tensile testing of metallic materials, steel structure design standards, and relevant specifications of seismic design codes for buildings, nonlinear characteristic parameters are set. Initial values are calculated by iteratively minimizing the nonlinear model. The nonlinear characteristic parameters are obtained by solving the sum of squared errors between the measured stress-strain data and the elastoplastic stage stress-strain data. Based on the nonlinear characterization requirements of the sinusoidal correction term in the multi-order nonlinear mapping formula, and using the nonlinear characteristic parameters extracted from the stress-strain curve as a link, a corresponding formula for the geometric nonlinear correction factor and the nonlinear characteristic parameters is established. The geometric nonlinear correction factor is calculated, and its value range is [value range missing]. The formula is ,in, The calibration coefficient is the experimental coefficient. For steel strain data, , Based on a uniaxial tensile test report, These are nonlinear characteristic parameters; For the first The power-law correction term for the normalized height of each component is used to accurately quantify the influence weight of the actual height of the component on the overall geometric parameters of the steel structure composite node, and to adapt to different component geometries and stress characteristics. This is a sine correction term for the geometric and material nonlinearity co-correction, used to quantify the coupling effect of component geometric deformation and steel material nonlinearity, thereby improving the accuracy of nonlinear characterization in the modeling of steel structure composite nodes.
[0034] S2. Based on the optimized geometric parameters, preprocessed data, and initial three-dimensional geometric model, output the initial finite element model of the steel structure composite precision nodes; based on the initial finite element model of the steel structure composite precision nodes, construct the nonlinear dynamic response update formula to obtain the equivalent stress.
[0035] Based on the optimized geometric parameters, preprocessed data, and initial 3D geometric model, mesh generation, component positioning calibration, and parameter assignment were carried out.
[0036] In the mesh generation stage, based on the component morphology and initial mesh size of the initial 3D geometric model, the mesh reference size is calculated according to the optimized geometric parameters. The formula is: Mesh reference size = Optimized geometric parameters × Test calibration reference coefficient, where the test calibration reference coefficient is the reference height of the 1 / 2 scaled-down component in the preprocessed data, determined by the specimen size parameters in the preprocessed data. This is combined with the standardized cross-sectional area of each component. To address the differences, the core stress-bearing areas of steel structure composite nodes, such as the connection between stiffening ribs and beam flanges, are refined through mesh refinement. The mesh size is adjusted according to the mesh reference size. The mesh is scaled up by a factor of 1, and hexahedral structured elements are used. Simultaneously, a mesh density gradient transition setting is enabled to avoid abrupt changes in mesh element size. The mesh is simplified for non-core load-bearing areas of steel structure composite nodes, such as non-connected edge sections of beam flanges and small-sized attached flanges of stiffeners, with the mesh size adjusted to a factor of 1 / 3 of the mesh reference size. For magnification, triangular or tetrahedral free meshes are used. The mesh simplification principle is to ensure that it does not affect the overall stress response characterization of the steel structure composite node and that the mesh quality meets the standards. Mesh quality meets the standards, meaning that for the 1 / 2 scale model of the steel structure composite node, the tetrahedral or hexahedral mesh must be free of geometric defects, have regular element shapes, and the density distribution must match the stress characteristics of the node. This ensures that the mesh can accurately capture the stress and strain details of the core stress areas, such as the connection between stiffeners and beam flanges, while also ensuring computational efficiency for non-core stress areas such as the non-connection edge segments of beam flanges and the small-sized attached folds of stiffeners. At the same time, it avoids non-convergence and result distortion caused by mesh quality issues, which is a prerequisite for subsequent nonlinear stress analysis.
[0037] In the component positioning and calibration stage, based on the completed mesh generation and the component assembly relationship of the initial 3D geometric model, the geometric contribution ratio of each component is decomposed through the sub-item superposition logic of the optimized geometric parameters. Based on the geometric contribution ratio of each component, the relative assembly position of each component is fine-tuned to correct the collaborative positioning deviation, ensure accurate component assembly and collaborative force matching, and avoid the distortion of force analysis caused by positioning deviation.
[0038] In the parameter assignment phase, after completing component positioning calibration and assigning basic material properties to the initial 3D geometric model, the preprocessed data, including standardized steel elastic modulus and yield strength, as well as standardized component cross-sectional area and actual component height, are further imported into the ANSYS finite element software. This process assigns complete and accurate physical and geometric properties to the initial 3D geometric model. The final output is a precise finite element initial model of the steel structure assembly adapted to the ANSYS finite element software.
[0039] Furthermore, relying on existing high-order finite difference methods and Newmark-β time integration methods, a nonlinear dynamic response update formula is designed to accurately capture the large deformation, local buckling, and nonlinear dynamic response of the initial finite element model of steel structure composite nodes under strong seismic loads. The nonlinear dynamic response update formula is optimized in two ways: first, by introducing a Sigmoid-type nonlinear region partitioning term to accurately partition the elastic, plastic, and buckling stages of node stress, achieving refined simulation of mechanical behavior at different load stages; second, by introducing a variable-step long-time attenuation correction term, which adaptively adjusts the stress update accuracy through a variable-step long-time step size to adapt to the dynamic characteristics of the load. Compared with the traditional linear dynamic response formula, this significantly improves the response simulation accuracy under complex load scenarios. The nonlinear dynamic response update formula is as follows:
[0040]
[0041] in, For steel structure composite nodes in The equivalent stress at a given time is used to represent the overall stress state of a steel structure composite node under load. For the first The nonlinear weighting coefficient of the component is used to characterize the . The influence of individual components on the stress of the overall steel structure composite node is calculated based on the geometric contribution ratio, combined with measured stress contribution data of similar steel structure composite nodes, using existing linear calibration methods. The measured stress contribution data of similar steel structure composite nodes are obtained through low-cycle repeated loading tests on steel structure composite nodes, measuring the Mises stress at key locations of each component, and calculating the proportion of the peak stress of a single component to the total peak stress of the steel structure composite node, i.e., the stress contribution ratio of that component. The value range is [insert range here]. ; For the first Each component The Mises stress at time t is used to measure the stress at time t. Each component The stress state at any given time was extracted from the initial finite element model of the steel structure composite precision nodes using the post-processing module of ANSYS finite element software. For the first The stress-strain nonlinearity coefficient of each component is used to adjust the nonlinear characteristics of the stress-strain relationship, characterizing the degree of nonlinear stress-strain behavior of steel in a specific component, and its value range is [value range missing]. Specifically, based on the measured effective stress-strain data of the elastoplastic stage obtained from uniaxial tensile tests of steel, a power-function nonlinear regression model was used. , The measured stress in a uniaxial tensile test of steel. To correspond to the measured strain; The material hardening coefficient, For yield stress correction term, parameter , , All methods are based on the measured effective stress-strain data of the elastoplastic stage obtained from the uniaxial tensile test of steel. The initial values of parameters are set in combination with the steel grade and the relevant standards for tensile testing of metallic materials. The sum of squared residuals between the calculated values of the power function type nonlinear regression model and the effective stress-strain data of the elastoplastic stage of the uniaxial tensile test of steel is minimized by the Levenberg-Marquardt iterative algorithm. After the iteration converges, the optimal parameters are obtained. The final values are determined after boundary verification and accuracy verification. For the first Each component The strain at time t is used to represent the strain at time t. The degree of deformation of a component under load is obtained by experimental measurement using strain gauges attached to key stress-bearing parts of components in similar steel structure composite nodes. The original values are then calculated using the standardization method described above for dimensional parameters. For the first The stress-strain increment coefficient of the nth component is used to describe the stress-strain increment coefficient of the nth component. The stress response intensity of each component during loading is calculated using the stress-strain increment ratio standardization method based on the measured stress and strain increment data from load increment tests of similar steel structure composite nodes. The value range is [value missing]. ; For the first The attenuation factor of the first component is used to describe the effect of time on the first component. The influence of stress response on individual components was determined using the vibration attenuation curve data from vibration attenuation tests on composite steel structure nodes. The vibration attenuation rate was calculated directly using this method, with a value range of [value missing]. ; Index of the time of load application; This is a linear domain partitioning and stress correction term, i.e., a Sigmoid-type nonlinear domain partitioning term, used to characterize the first... Each component Mises stress at time Correction value after nonlinear region division; It is a Sigmoid-type nonlinear function used to reflect the first... The characteristics of a component's stress transitioning from the elastic stage to the plastic and buckling stages are accurately used to classify the component's stress stages, such as elastic, plastic, and buckling, and to adaptively correct the Mises stress for different stages. This is a variable-step time attenuation correction term used for adaptive correction with variable step size. It adapts to the dynamic changes in seismic loads, avoids stress response distortion caused by fixed-step calculations, and ensures the accuracy of stress calculations under different load durations.
[0042] Finally, by updating the nonlinear dynamic response formula, the stress state of each component is dynamically adjusted, and the overall stress state of the steel structure composite node is gradually simulated to ensure the accurate capture of nonlinear behavior.
[0043] In summary, a modeling method for a finite element model of a steel structure composite node has been completed.
[0044] The order of the embodiments is for illustrative purposes only and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.
[0045] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0046] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A modeling method for a finite element model of a steel structure composite node, characterized in that, Includes the following steps: S1. Data collection is performed on the steel structure composite nodes to obtain the collected data, including basic design parameters, material mechanical parameters, and specimen dimensional parameters; Based on the collected data, preprocessing is performed to obtain preprocessed data; Based on the preprocessed data, an initial 3D geometric model is constructed. Then, based on the preprocessed data and the initial 3D geometric model, and combined with geometric nonlinear mapping theory, the geometric parameters are optimized using sinusoidal correction to obtain the optimized geometric parameters. The specific optimization formula is as follows: in, These are the optimized geometric parameters; This is an index of the components contained in the composite steel structure node; This represents the total number of components contained in the steel structure composite node; For the first Geometric parameter correction coefficients for each component; For the first The standardized cross-sectional area of each component; For the first The actual height of each component; Component reference height; For the first The geometric power of each component; For the first Geometric nonlinearity correction factor for each component; S2. Based on the optimized geometric parameters, preprocessed data, and initial 3D geometric model, mesh generation, component positioning calibration, and parameter assignment are performed to output a precise node finite element initial model of the steel structure composite. Based on the precise node finite element initial model of the steel structure composite, a nonlinear dynamic response update formula is constructed. The equivalent stress is obtained through the nonlinear weight coefficients of the components, the linear region partitioning and stress correction term based on the Sigmoid type nonlinear function, and the variable-step long-time attenuation correction term. The nonlinear dynamic response update formula is as follows: in, For steel structure composite nodes in The equivalent stress at any given time; For the first Nonlinear weighting coefficients for each component; For the first Each component Mises stress at time t; For the first The stress-strain nonlinear coefficient of each component; For the first Each component Adaptability at all times; For the first The stress-strain increment coefficient of each component; For the first The attenuation factor of each component; Index of the time of load application; For linear region division and stress correction terms; This is a time-lapse correction term for variable-step operation.
2. The modeling method for a finite element model of a steel structure composite node according to claim 1, characterized in that, S1 specifically includes: Based on the column axial compression ratio of the component in the preprocessed data, the geometric parameter correction coefficient of the component is calculated; based on the preprocessed data and the geometric parameter correction coefficient of the component, combined with the power correction term and sine correction term of the normalized height of the component, the optimized geometric parameters are calculated.
3. The modeling method for a finite element model of a steel structure composite node according to claim 1, characterized in that, S2 specifically includes: Based on the optimized geometric parameters, combined with the component shapes and initial mesh sizes of the initial 3D geometric model, the mesh reference size is calculated; based on the mesh reference size, combined with the preprocessed data, the mesh is generated.
4. The modeling method for a finite element model of a steel structure composite node according to claim 3, characterized in that, S2 specifically includes: Based on the mesh generation, the geometric contribution ratio of each component is calculated according to the component assembly relationship of the initial 3D geometric model and the sub-item superposition logic of the optimized geometric parameters; the relative assembly position of each component is finely adjusted based on the geometric contribution ratio of each component, and the component positioning calibration is performed.
5. The modeling method for a finite element model of a steel structure composite node according to claim 4, characterized in that, S2 specifically includes: Based on the component positioning and calibration, and using the initial three-dimensional geometric model, combined with the basic design parameters and material mechanics parameters in the preprocessed data, the initial three-dimensional geometric model is given physical and geometric properties, and the precise node finite element initial model of the steel structure combination is output.
6. The modeling method for a finite element model of a steel structure composite node according to claim 5, characterized in that, S2 specifically includes: Based on the initial finite element model of the precise nodes of the steel structure, the Mises stress of the components is extracted; based on the Mises stress of the components, the linear region division and stress correction terms are obtained, and the elastic, plastic and buckling stages of the node stress are divided.
7. The modeling method for a finite element model of a steel structure composite node according to claim 4, characterized in that, S2 specifically includes: The nonlinear weighting coefficient of the component is calculated based on the geometric contribution ratio.