Construction Method and Device for Hysteretic Parameter Model of Steel Structure Components under Wind Load

Abstract

The present application is applicable to the technical field of wind-induced dynamic response analysis of steel structures, and provides a method and device for constructing a hysteretic parameter model of a steel structure component under wind load. The method includes: constructing a refined finite element model of the steel structure component; applying a monotonic load to it and simulating the monotonic loading performance of the steel structure component to obtain a simulated monotonic loading curve of the steel structure component under the monotonic load; and applying a wind load to it and simulating the hysteretic performance of the steel structure component to obtain a simulated hysteretic curve of the steel structure component under the wind load; respectively performing parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the component, including skeleton curve parameters and cumulative plastic deformation capacity parameters; according to the skeleton curve parameters and the cumulative plastic deformation capacity parameters, obtaining a hysteretic parameter model of the steel structure component through regression analysis, which can more accurately predict the hysteretic parameters and response performance of the steel structure component under wind load.

Description

Technical Field

[0001] This application belongs to the technical field of wind-induced dynamic response analysis of steel structures, and particularly relates to a method and device for constructing a hysteretic parameter model of steel structure components under wind load. Background Technique

[0002] The hysteretic parameters of steel structure components are the key parameters controlling the strength and stiffness degradation of steel structure components under external loads. The hysteretic parameters of steel structure components usually need to be determined according to the pseudo-static loading tests of the components. At present, in the prior art, the relationship between the component size and the hysteretic parameters of the components (i.e., the hysteretic parameter model of steel structure components) has been obtained through a large number of pseudo-static loading test data of components and statistical analysis methods. Only by substituting the component size into the hysteretic parameter model of steel structure components can the hysteretic parameters of steel structure components be conveniently obtained for structural response calculation and analysis, which has very high practicability.

[0003] However, currently, the existing hysteretic parameter models of steel structure components are usually obtained after a large number of pseudo-static loading tests of steel structure components based on seismic loading protocols. However, the hysteretic performance of steel structure components is greatly related to their loading history; there are very obvious differences between wind loads and seismic loads. Seismic loads can be approximately regarded as zero-mean random loads, while wind loads are non-zero-mean random loads, and there are also significant differences in the load spectrum characteristics of the two. Therefore, the stress and deformation characteristics of steel structure components under wind load are different from those under seismic load. Therefore, using the existing hysteretic parameter models of steel structure components proposed based on seismic loads to analyze the response performance of steel structure components under wind load may lead to inaccurate response analysis results. Summary of the Invention

[0004] The embodiments of this application provide a method and device for constructing a hysteretic parameter model of steel structure components under wind load, which can solve the problem of low accuracy when calculating the response performance of steel structure components under wind load through the existing hysteretic parameter models.

[0005] In the first aspect, the embodiments of this application provide a method for constructing a hysteretic parameter model of steel structure components under wind load, and the method includes:

[0006] Construct a refined finite element model for steel structure components;

[0007] Apply a monotonic load to the refined finite element model and perform a simulation of the monotonic loading performance of the steel structure component to obtain a simulated monotonic loading curve of the steel structure component under the monotonic load;

[0008] Apply wind loads to the refined finite element model and simulate the hysteretic behavior of the steel structure components to obtain the simulated hysteretic curves of the steel structure components under the wind loads;

[0009] Respectively identify the parameters of the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure components; wherein, the hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters;

[0010] According to the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters, obtain a hysteretic parameter model of the steel structure components through regression analysis, wherein the hysteretic parameter model of the steel structure components is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure components under wind loads.

[0011] In a possible implementation manner of the first aspect, the respectively identifying the parameters of the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure components includes:

[0012] Identify the simulated monotonic loading curve by the least square method to obtain a plurality of the skeleton curve parameters in the hysteretic parameters of the steel structure components; wherein, the skeleton curve parameters include stiffness K e 、angle of rotation in the strengthening section θ p 、angle of rotation in the softening section θ pc 、ultimate angle of rotation θ u 、yield moment M y 、peak moment M c 、residual moment M r ;

[0013] According to the modified hysteretic constitutive mIMK model, identify the simulated hysteretic curve by the unscented Kalman filter UKF algorithm to obtain a plurality of the cumulative plastic deformation capacity parameters in the hysteretic parameters of the steel structure components, wherein the cumulative plastic deformation capacity parameters include the cumulative plastic deformation capacity of basic strength degradation Λ s 、the cumulative plastic deformation capacity of strength degradation in the softening section Λ c 、the cumulative plastic deformation capacity of unloading stiffness degradation Λ k .

[0014] In a possible implementation of the first aspect, identifying the simulated monotonic loading curve by the least squares method to obtain multiple of the skeleton curve parameters among the hysteretic parameters of the steel structure member includes:

[0015] Identifying the simulated monotonic loading curve by using a skeleton curve model to obtain the skeleton curve function of the steel structure member;

[0016] Performing a partial derivative calculation on the skeleton curve function of the steel structure member based on the initial value of the parameter vector to obtain the Jacobian matrix corresponding to the skeleton curve function; where the parameter vector is , ; the initial value of the parameter vector is determined according to the hysteretic parameter model of the steel structure member under the seismic load loading mode;

[0017] Performing iterative calculation on the parameter vector according to the residual vector and the Jacobian matrix until the first preset termination condition is met to stop the iteration, and obtaining the updated parameter vector; where the updated parameter vector is the skeleton curve parameter of the steel structure member.

[0018] In a possible implementation of the first aspect, according to the modified hysteretic constitutive mIMK model, identifying the simulated hysteretic curve by the unscented Kalman filter (UKF) algorithm to obtain multiple of the cumulative plastic deformation capacity parameters among the hysteretic parameters of the steel structure member includes:

[0019] Taking the mIMK model as the nonlinear state function of the UKF algorithm, and taking the simulated hysteretic curve of the steel structure member as the nonlinear observation function;

[0020] Constructing a first state point set according to the state vector at the current moment and the first preset generation rule by the unscented transformation method;

[0021] Predicting the state vector and the covariance matrix of the state vector according to the first preset prediction formula to obtain the predicted value of the state vector at the next moment and the predicted value of the covariance matrix of the state vector at the next moment;

[0022] Constructing a second observation point set according to the predicted value of the state vector at the next moment through the nonlinear observation function;

[0023] Updating the predicted value of the state vector at the next moment and the predicted value of the covariance matrix of the state vector at the next moment according to the second preset update formula to obtain the state vector at the next moment and the covariance matrix of the state vector at the next moment;

[0024] Iteratively update the state vector at the next moment and the covariance matrix of the state vector at the next moment until the iteration stops when the second preset termination condition is met, and obtain the updated state vector, where the updated state vector is the cumulative plastic deformation capacity parameter of the steel structure member.

[0025] In a possible implementation manner of the first aspect, the obtaining of the hysteretic parameter model of the steel structure member by regression analysis according to the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters includes:

[0026] Use a general multiple regression model to fit the relationship between the multiple preset dimension parameters of the steel structure member and the multiple skeleton curve parameters and the multiple cumulative plastic deformation capacity parameters, and optimize and analyze the general multiple regression model according to the multiple stepwise regression analysis method to obtain the hysteretic parameter model of the steel structure member.

[0027] In a possible implementation manner of the first aspect, the hysteretic parameter model of the steel structure member is:

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] θ u = 0.15rad ;

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] Where is the stiffness, is the peak moment, is the rotation angle of the strengthening section, is the rotation angle of the softening section, is the residual moment, is the ultimate rotation angle, is the yield moment, F is the peak moment The ratio with the yield moment is the cumulative plastic deformation capacity of the basic strength degradation, is the cumulative plastic deformation capacity of the strength degradation in the softening section, is the cumulative plastic deformation capacity of the unloading stiffness degradation, L is the length of the steel structure member, is the shear stiffness, is the flexural stiffness, is the shear modulus, is the moment of inertia of the cross-section of the steel structure member, I is the web area of the cross-section of the steel structure member, is Young's modulus, is the section plastic development coefficient of the steel structure member, is the elastic section modulus, is the yield stress, is the axial load caused by gravity, P g is the axial yield load of the steel structure member, is the web height of the steel structure member, is the web thickness of the steel structure member, is the radius of gyration of the cross-section of the steel structure member along the weak axis, d is the cross-section height of the steel structure member, is the flange thickness of the steel structure member, is the flange width of the steel structure member. In a possible implementation of the first aspect, the construction of the refined finite element model for the steel structure member includes:

[0039] Using a four-node quadrilateral finite membrane strain linear reduced integration S4R shell element as the body of the steel structure member; wherein, the mesh size is 25mm×25mm; the steel structure member is an H-shaped cross-section member; the material constitutive of the steel structure member is a mixed hardening model;

[0040] Constraining the top and bottom of the steel structure member by a fixed connection method, and adding the overall defect and local defect of the steel structure member to the body of the steel structure member to obtain the refined finite element model; wherein, the overall defect is

[0041] and the local defect is and and L is the length of the steel structure member, d is the cross-section height of the steel structure member, is the cross-section width of the steel structure member.

[0042] In a possible implementation of the first aspect, a wind load is applied to the refined finite element model and the hysteretic performance simulation of the steel structure member is carried out to obtain the simulated hysteretic curve of the steel structure member under the wind load, including:

[0043] Obtain the wind load application method for applying the wind load to the refined finite element model; wherein, the formulation process of the wind load application method includes: obtaining a plurality of cycle mean levels and a plurality of cycle amplitude levels according to the requirements of the pseudo-static test on the steel structure member; determining the number of load applications at a plurality of cycle mean levels and the number of load applications at a plurality of cycle amplitude levels from the joint probability distribution of the cycle mean and the cycle amplitude; determining the cumulative probability values at different levels according to the plurality of cycle mean levels and the plurality of cycle amplitude levels; determining the cycle mean and the cycle amplitude at each level according to the cumulative probability distribution of the cycle mean and the cycle amplitude of the inter-story drift angle of the steel structure member and the cumulative probability values at different levels; obtaining the wind load application method of the steel structure member under the wind load according to the cycle mean at each level, the cycle amplitude at each level and the number of cyclic load applications at different levels;

[0044] Use the wind load application method to apply the wind load to the refined finite element model and carry out the hysteretic performance simulation of the steel structure member to obtain the simulated hysteretic curve of the steel structure member under the wind load.

[0045] In a second aspect, an embodiment of the present application provides a device for constructing a hysteretic parameter model of a steel structure member under wind load, including:

[0046] A model construction module for constructing a refined finite element model for the steel structure member;

[0047] A first simulation module for applying a monotonic load to the refined finite element model and carrying out a monotonic loading performance simulation of the steel structure member to obtain the simulated monotonic loading curve of the steel structure member;

[0048] A second simulation module for applying a wind load to the refined finite element model and carrying out a hysteretic performance simulation of the steel structure member to obtain the simulated hysteretic curve of the steel structure member under the wind load;

[0049] A parameter identification module for respectively carrying out parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure member; wherein, the hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters;

[0050] A model determination module, configured to obtain a hysteretic parameter model of a steel structure member through regression analysis according to the multiple skeleton curve parameters and the multiple cumulative plastic deformation capacity parameters, wherein the hysteretic parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load.

[0051] In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for constructing a hysteretic parameter model of a steel structure member under wind load described in any one of the above is implemented.

[0052] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the method for constructing a hysteretic parameter model of a steel structure member under wind load described in any one of the above is implemented.

[0053] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product runs on a terminal device, the terminal device is caused to execute the method for constructing a hysteretic parameter model of a steel structure member under wind load described in any one of the first aspects above.

[0054] The beneficial effects of the embodiments of the present application compared with the prior art are:

[0055] An embodiment of the present application provides a method for constructing a hysteretic parameter model of a steel structure member under wind load. The method includes: constructing a refined finite element model for the steel structure member; applying a monotonic load to the refined finite element model and simulating the monotonic loading performance of the steel structure member to obtain a simulated monotonic loading curve of the steel structure member under the monotonic load; and applying a wind load to the refined finite element model and simulating the hysteretic performance of the steel structure member to obtain a simulated hysteretic curve of the steel structure member under the wind load; respectively performing parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure member; wherein the hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters; according to the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters, a hysteretic parameter model of the steel structure member is obtained through regression analysis, wherein the hysteretic parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load. Through parameter identification of the simulated monotonic loading curve and the simulated hysteretic curve obtained by simulating the refined finite element model in the present application, the hysteretic parameters of the steel structure member are determined, and a hysteretic parameter model of the steel structure member that characterizes the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load is obtained. Through this hysteretic parameter model of the steel structure member, the hysteretic parameters of the steel structure member under wind load can be predicted more accurately, so that the response performance of the steel structure member under wind load can be calculated more accurately. Description of the Drawings

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0057] Figure 1 It is a schematic flow chart of a method for constructing a hysteretic parameter model of a steel structure member under wind load provided by an embodiment of the present application;

[0058] Figure 2 It is a schematic diagram of a mIMK model provided by an embodiment of the present application;

[0059] Figure 3 It is a schematic diagram of the dimensions of a steel structure member provided by an embodiment of the present application;

[0060] Figure 4 It is a schematic diagram of a finite element model of an H-shaped cross-section steel structure member provided by an embodiment of the present application;

[0061] Figure 5It is a schematic comparison diagram of the hysteresis curve parameters and the simulation results of the hysteresis parameter model of a steel structure member under wind load provided by an embodiment of the present application;

[0062] Figure 6 It is a schematic structural diagram of a device for constructing a hysteresis parameter model of a steel structure member under wind load provided by an embodiment of the present application;

[0063] Figure 7 It is a schematic structural diagram of a terminal device provided by an embodiment of the present application. Detailed implementation manners

[0064] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are presented to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0065] It should be understood that when used in the specification and appended claims of the present application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0066] It should also be understood that the term "and / or" used in the specification and appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0067] As used in the specification and appended claims of the present application, the term "if" can be interpreted as "when", "once", "in response to determining", or "in response to detecting" according to the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" according to the context.

[0068] In addition, in the description of the specification and appended claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0069] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that specific features, structures, or characteristics described in connection with that embodiment are included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in some other embodiments", "in still some other embodiments", etc. that appear at different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized.

[0070] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a method for constructing a hysteretic parameter model of a steel structure member under wind load provided by an embodiment of this application. The method includes:

[0071] S11. Construct a refined finite element model for the steel structure member;

[0072] S12. Apply a monotonic load to the refined finite element model and perform a simulation of the monotonic loading performance of the steel structure member to obtain a simulated monotonic loading curve of the steel structure member under the monotonic load;

[0073] S13. Apply a wind load to the refined finite element model and perform a simulation of the hysteretic performance of the steel structure member to obtain a simulated hysteretic curve of the steel structure member under the wind load;

[0074] S14. Perform parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve respectively to obtain the hysteretic parameters of the steel structure member; wherein, the hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters;

[0075] S15. According to a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters, obtain a hysteretic parameter model of the steel structure member through regression analysis, wherein the hysteretic parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load.

[0076] It should be noted that in this embodiment, the execution subject can be a terminal device such as a server, and no specific limitation is made thereto.

[0077] In step S11, the refined finite element model is a digital model used to simulate and analyze the mechanical properties of steel structure members under various loads. In this embodiment, the refined finite element model is a model used to simulate and analyze the monotonic loading characteristics of steel structure members under monotonic loading or the hysteretic characteristics under wind load, and the refined finite element model is a pre-constructed model.

[0078] In step S12, a monotonic load refers to a load that increases monotonically with time and does not exhibit periodic variations. During the structural analysis of steel structure components, monotonic loads are used to evaluate the monotonic loading performance of steel structure components. Monotonic loading performance is the mechanical performance exhibited by steel structure components under monotonic loading, including strength, stiffness, ductility, etc. A monotonic loading curve is the relationship curve between the deformation and the load of a component under a monotonic load, reflecting the performance of the component under a monotonic load. In this embodiment, by applying a monotonic load to the refined finite element model and simulating its monotonic loading performance, the monotonic loading curve of the steel structure component under this monotonic load is obtained, that is, the simulated monotonic loading curve.

[0079] In step S13, the wind load refers to the action on the component caused by the wind. Hysteretic performance is the force-deformation relationship of a component under cyclic loads. In this embodiment, it refers to the energy dissipation capacity and cumulative damage of the component under the wind load. Hysteretic performance is usually represented by a hysteresis curve, which reflects the relationship curve between the deformation and the load of a component under cyclic loads. In this embodiment, by applying a wind load to the refined finite element model and simulating its hysteretic performance, the hysteresis curve of the steel structure component under this wind load is obtained, that is, the simulated hysteresis curve.

[0080] In step S14, the hysteretic parameters are the parameters used to describe the characteristics of the hysteresis curve and are also the undetermined parameters in the mathematical formula of the hysteresis model. The size and stress state of the steel structure component are the key influencing factors of these undetermined parameters. Among them, the hysteresis model is a mathematical description of the hysteretic behavior of a component, which is an abstraction and simplification of the hysteretic behavior of a component based on the observation and analysis of physical phenomena. Generally speaking, the hysteresis model defines corresponding rules (or mathematical formulas) according to the characteristics of the component to calculate parameters such as the strength, stiffness, and energy dissipation of the component under cyclic loads, and its role is to obtain parameters such as the strength, stiffness, and energy dissipation of the component. In this embodiment, the hysteretic parameters of the steel structure component are the parameters used to describe the mechanical performance of the component under cyclic loading during the simulation of the hysteresis curve. These parameters can reflect the characteristics such as the deformation, energy dissipation, and recovery ability of the component after experiencing multiple loadings and unloadings. The hysteretic parameters of the steel structure component include multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters. Among them, the skeleton curve parameters are the characteristic point parameters reflecting the main mechanical performance of the component, such as stiffness K e , the slope of the strengthening section θ p , the slope of the softening section θ pc , the ultimate slope θ u , the yield moment M y, Peak bending moment M c , Residual bending moment M r . The cumulative plastic deformation capacity parameter is a parameter that describes the cumulative plastic deformation capacity of a component under cyclic loading, reflecting the fatigue life and seismic performance of the component, including the basic strength degradation plastic deformation capacity Λ s , Softening section strength degradation plastic deformation capacity Λ c , Unloading stiffness degradation plastic deformation capacity Λ k . In this embodiment, by performing parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve respectively, multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters can be obtained.

[0081] In step S15, the hysteretic parameter model of the steel structure component is a set of mathematical expressions between the component size / force state and the hysteretic parameters obtained through regression analysis of a large amount of component data. The role of the hysteretic parameter model is to obtain the undetermined parameters in the hysteretic model, that is, the hysteretic parameters. In this embodiment, by performing regression analysis on the multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters identified, a hysteretic parameter model of the steel structure component can be obtained to describe the relationship between the characteristic size of the steel structure component and the hysteretic parameters under wind load.

[0082] It can be understood that the embodiments of the present application provide a method for constructing a hysteretic parameter model of a steel structure member under wind load. The method includes: constructing a refined finite element model for the steel structure member; applying a monotonic load to the refined finite element model and simulating the monotonic loading performance of the steel structure member to obtain a simulated monotonic loading curve of the steel structure member under the monotonic load; and applying a wind load to the refined finite element model and simulating the hysteretic performance of the steel structure member to obtain a simulated hysteretic curve of the steel structure member under the wind load; respectively performing parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure member; wherein the hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters; according to the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters, a hysteretic parameter model of the steel structure member is obtained through regression analysis, wherein the hysteretic parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load. The present application performs parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve obtained by simulating the refined finite element model, determines the hysteretic parameters of the steel structure member, and obtains a hysteretic parameter model of the steel structure member that characterizes the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load. Through this hysteretic parameter model of the steel structure member, the hysteretic parameters of the steel structure member under wind load can be predicted more accurately, so that the response performance of the steel structure member under wind load can be calculated more accurately.

[0083] In a possible implementation, respectively performing parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure member includes:

[0084] Identifying the simulated monotonic loading curve by the least squares method to obtain a plurality of skeleton curve parameters in the hysteretic parameters of the steel structure member; wherein the skeleton curve parameters include stiffness K e , strengthening section rotation angle θ p , softening section rotation angle θ pc , ultimate rotation angle θ u , yield moment M y , peak moment M c , residual moment M r ;

[0085] According to the modified hysteretic constitutive mIMK model, the simulated hysteretic curve is identified by the unscented Kalman filter (UKF) algorithm to obtain multiple cumulative plastic deformation capacity parameters in the hysteretic parameters of steel structure members. Among them, the cumulative plastic deformation capacity parameters include the cumulative plastic deformation capacity of basic strength degradation Λ s , the cumulative plastic deformation capacity of strength degradation in the softening section Λ c , and the cumulative plastic deformation capacity of unloading stiffness degradation Λ k .

[0086] It should be noted that the least squares method is to find the best function matching of data by minimizing the sum of the squares of errors. In this embodiment, the simulated monotonic loading curve is fitted by the least squares method to identify multiple skeleton curve parameters. Among them, the stiffness K e represents the ratio of the moment to the rotation angle of the member in the initial loading stage; the rotation angle in the strengthening section θ p represents the rotation angle corresponding to the turning point from the elastic stage to the plastic strengthening stage in the monotonic loading curve; the rotation angle in the softening section θ pc represents the rotation angle when the peak bearing capacity starts to decline (i.e., enters the softening stage); the ultimate rotation angle θ u represents the rotation angle when the member reaches the ultimate bearing capacity (usually the bearing capacity drops to a certain specified value); the yield moment M y represents the yield moment value when the member starts to enter the plastic stage; the peak moment M c represents the maximum moment value that the member can bear during monotonic loading; the residual moment M r represents the moment value remaining in the member after the loading and unloading cycle.

[0087] The modified hysteretic constitutive model (modified Ibarra Medina Krawinkler, mIMK) is a mathematical model used to describe the mechanical behavior of members under cyclic loading (such as wind load, earthquake load). As Figure 2 shown, Figure 2 is a schematic diagram of an mIMK model provided by an embodiment of the present application. As Figure 2 shown, the skeleton curve of this mIMK model is defined by three strength parameters and four deformation parameters, that is, M y represents the yield moment, M c = α×M y represents the peak moment of the member,M r Represents the residual bending moment of the component, θ y Represents the yield rotation angle, θ p Represents the rotation angle of the component in the strengthening section, θ pc Represents the rotation angle of the softening section, θ u Represents the ultimate rotation angle. The mIMK model has three performance degradation modes, namely basic strength degradation, softening section strength degradation, and unloading stiffness degradation, corresponding to the degradation of the component's strengthening section strength, softening section strength, and unloading stiffness respectively. When the external load borne by the component exceeds the yield strength of the component and plastic energy dissipation occurs under the action of the external load, at this time, the component begins to produce performance degradation, and the degradation rule is shown in formula (1-1).

[0088] (1-1)

[0089] In formula (1-1), Is the cumulative energy dissipation capacity of basic strength degradation, Is the cumulative energy dissipation capacity of softening section strength degradation, Is the cumulative energy dissipation capacity of unloading stiffness degradation, Is the cumulative plastic deformation capacity of basic strength degradation, Is the cumulative plastic deformation capacity of softening section strength degradation, Is the cumulative plastic deformation capacity of unloading stiffness degradation. Usually, the cumulative plastic deformation capacity >0, The larger it is, the slower the performance degradation rate of the component in this performance degradation mode; when Λ = 0, it indicates that the component does not have this performance degradation mode. The degradation strength and degradation stiffness of the component can be calculated by formula (1-2).

[0090] (1-2)

[0091] In formula (1-2), i is the i-th loading cycle, Is the strength of the component at the i-th loading cycle, Is the stiffness of the component at the i-th loading cycle, Is the strength of the component at the (i-1)-th loading cycle, Is the stiffness of the component at the (i-1)-th loading cycle, Is the degradation parameter based on hysteretic energy dissipation, and the subscript Is three performance degradation models, that is, s corresponds to the basic strength degradation model, c corresponds to the softening section strength degradation model, and k corresponds to the unloading stiffness degradation model. Among them, The expression is shown in Formula (1-3).

[0092] (1-3)

[0093] In Formula (1-3), is the energy dissipated by the component in the i th loading cycle, is the energy dissipated by the component in the j th loading cycle, is the cumulative energy dissipation capacity of the component in the three performance degradation models, is an empirical parameter, usually taken as 1.0.

[0094] It should be noted that the Unscented Kalman Filter (UKF) is an algorithm for state evaluation and parameter identification of nonlinear systems. UKF estimates the state of the system through prediction and update steps and takes into account the uncertainty of the system. The UKF algorithm makes the nonlinear system applicable to the standard Kalman filter framework under linear assumptions through the unscented transformation method, estimates the approximate probability density distribution function of the nonlinear state space model through a series of sample points, avoids the errors caused by approximate linearization, and has higher accuracy. In this example, the nonlinear system equation adopted is the mIMK hysteretic constitutive model, which is a highly nonlinear system. Therefore, the UKF algorithm can be used to identify the parameters of the mIMK model for the simulated hysteretic curve, so as to obtain multiple cumulative plastic deformation capacity parameters.

[0095] In a possible implementation, the simulated monotonic loading curve is identified by the least squares method to obtain multiple skeleton curve parameters among the hysteretic parameters of the steel structure component, including:

[0096] The simulated monotonic loading curve is identified by using the skeleton curve model to obtain the skeleton curve function of the steel structure component;

[0097] Based on the initial value of the parameter vector, the partial derivative calculation is performed on the skeleton curve function of the steel structure component to obtain the Jacobian matrix corresponding to the skeleton curve function; where the parameter vector is , ; the initial value of the parameter vector is determined according to the hysteretic parameter model of the steel structure component under the seismic load loading method;

[0098] According to the residual vector and the Jacobian matrix, iterative calculation is performed on the parameter vector until the first preset termination condition is satisfied and the iteration stops, so as to obtain the updated parameter vector; where the updated parameter vector is the skeleton curve parameter of the steel structure component.

[0099] Specifically, first, according to the refined finite element model of the steel structure component, the simulated monotonic loading curve of the component is obtained y = y ( θ ), and the skeleton curve of the component is identified based on the simulated monotonic loading curve to obtain the skeleton curve function parameters of the steel structure component. Among them, the skeleton curve model adopted by the identification function is as shown in formula (1-4).

[0100] (1-4)

[0101] In formula (1-4), is the stiffness, is the rotation angle, is the yield rotation angle, is the peak moment, is the yield moment, is the rotation angle of the strengthening section, is the rotation angle of the softening section, is the residual moment. Secondly, set the parameter vector , , and the initial value of the parameter vector is determined according to the existing hysteretic parameter model of the steel structure component under the seismic load loading regime. Among them, the parameter vector is used to describe the parameters of the skeleton curve function of the steel structure component. The seismic load loading regime is the existing hysteretic performance test loading rule formulated according to the response characteristics of the steel structure component under the action of seismic load. The initial value of the parameter vector is the value set for the parameter vector before iterative update; among them, =0.15rad, =0.4 ; it can be expressed by the following formulas (1-5)-(1-9).

[0102] (1-5)

[0103] (1-6)

[0104] (1-7)

[0105] (1-8)

[0106] In formulas (1-5)-(1-8), F is the ratio of the peak moment to the yield moment , is the rotation angle of the strengthening section, is the rotation angle of the softening section, is the residual moment, is the yield moment, is the length of the steel structure member, is the web height of the steel structure member, is the web thickness of the steel structure member, is the radius of gyration of the cross-section of the steel structure member about the weak axis, γ represents the section plastic development coefficient. For the strong axis and weak axis of the H-shaped section, γ the values are 1.05 and 1.2 respectively, while for the hollow section, γ it is equal to 1.05; is the elastic section modulus; is the yield stress; P g is the axial load caused by gravity; is the axial yield load of the steel structure member. The stiffness of the steel structure member can be calculated by formula (1-9).

[0107] (1-9)

[0108] In formula (1-9), is the shear stiffness, is the flexural stiffness, L is the length of the steel structure member, I is the moment of inertia of the cross-section of the steel structure member, is the web area of the cross-section of the steel structure member, is Young's modulus, is the shear modulus, where, E = 200 GPa, G = 79.3 GPa.

[0109] After determining the initial value of the parameter vector, the partial derivative of the skeleton curve function of the steel structure member is taken based on the initial value of the parameter vector to obtain the corresponding Jacobian matrix J, as shown in formula (1-10). This Jacobian matrix J can describe the rate of change of the skeleton curve function with respect to the parameter vector.

[0110] (1-10)

[0111] In formula (1-10), N represents the number of observed values, that is, the number of discrete points of the simulated monotonic loading curve of the steel structure member. represents the Nth observed value, that is, the Nth rotation angle of the simulated monotonic loading curve of the steel structure member; represents the change of the skeleton curve function with respect to the stiffness, represents the change of the skeleton curve function with respect to the rotation angle in the strengthening section, represents the change of the skeleton curve function with respect to the rotation angle in the softening section, Indicates the variation of the backbone curve function with respect to the ultimate rotation angle. Indicates the variation of the backbone curve function with respect to the yield moment. Indicates the variation of the backbone curve function with respect to the peak moment. Indicates the variation of the backbone curve function with respect to the residual moment.

[0112] It should be noted that in numerical analysis and optimization, the residual vector represents the difference between the observed value and the simulated predicted value, and is used to measure the accuracy of the model prediction under the current parameter vector. In this embodiment, the residual vector is represented by the following formula (1-11).

[0113] (1-11)

[0114] In formula (1-11), is the residual vector, represents the Nth moment value of the monotonic loading curve of the steel structure member, represents the moment value of the steel structure member calculated by the backbone curve model based on the parameter vector as the basis.

[0115] Subsequently, the parameter vector is updated according to the residual vector and the Jacobian matrix, as shown in Equation (1-12), to obtain the updated parameter vector.

[0116] (1-12)

[0117] In formula (1-12), represents the parameter vector at the i th iteration, represents the parameter vector at the i +1th iteration, is the update vector.

[0118] Repeat the above process until the update vector Δ α approaches 0, and the parameter vector is no longer updated, obtaining the updated parameter vector. At this time, the obtained updated parameter vector is the backbone curve parameter of the hysteretic curve.

[0119] It should be noted that the first preset termination condition is the condition for stopping iteration set in advance. In this embodiment, the first preset termination condition is to stop iteration when the update vector Δ α approaches 0.

[0120] In a possible implementation manner, according to the modified hysteretic constitutive mIMK model, the simulated hysteretic curve is identified by the unscented Kalman filter (UKF) algorithm to obtain multiple cumulative plastic deformation capacity parameters among the hysteretic parameters of the steel structure member, including:

[0121] The mIMK model is used as the nonlinear state function of the UKF algorithm, and the simulated hysteretic curve of the steel structure member is used as the nonlinear observation function;

[0122] By means of unscented transformation, a first state point set is constructed according to the state vector at the current moment and the first preset generation rule;

[0123] According to the first preset prediction formula, the state vector and the covariance matrix of the state vector are predicted to obtain the predicted value of the state vector at the next moment of the current moment and the predicted value of the covariance matrix of the state vector at the next moment;

[0124] Through the nonlinear observation function, a second observation point set is constructed according to the predicted value of the state vector at the next moment;

[0125] According to the second preset update formula, the predicted value of the state vector at the next moment and the predicted value of the covariance matrix of the state vector at the next moment are updated to obtain the state vector at the next moment and the covariance matrix of the state vector at the next moment;

[0126] The state vector at the next moment and the covariance matrix of the state vector at the next moment are iteratively updated until the second preset termination condition is met to stop the iteration, and the updated state vector is obtained, where the updated state vector is the cumulative plastic deformation capacity parameter of the steel structure member.

[0127] It should be noted that the nonlinear state function is a function that describes the state of the system, representing the nonlinear relationship between variables. The nonlinear observation function is a function that maps the true state of the system into the observation space and is used to extract the information of the system state from the observation data. In this embodiment, the mIMK model is used as the nonlinear state function of the UKF algorithm, and the simulated hysteretic curve of the steel structure member is used as the nonlinear observation function.

[0128] Unscented transformation is a mathematical method used to generate a set of sample points (i.e., sigma points) from the original probability distribution, and these points can accurately approximate the high-order statistical characteristics of the original distribution. The state vector is used to describe the complete state of the system at a certain moment. The covariance matrix of the state vector is a matrix that describes the covariance relationship between multiple variables and is used to represent the correlation and dispersion degree between variables. The first preset generation rule is a rule for generating the first state point set set in advance. The first state point set is a set of sigma points generated according to the state vector at the current moment.

[0129] The first preset prediction formula is a set mathematical formula for predicting the future state based on the current state. The predicted value of the state vector at the next moment of the current moment refers to the predicted value obtained by predicting the state vector at the current moment according to the non-linear state function of the system in the UKF algorithm. The predicted value of the state vector at the next moment is calculated based on the state vector at the current moment, the system input, and the system dynamic characteristics. Correspondingly, in the UKF algorithm, the covariance matrix of the state vector at the current moment can be predicted according to the non-linear function of the system to obtain the predicted value of the covariance matrix of the state vector at the next moment.

[0130] The second set of observation points is a set of sigma points constructed based on the predicted value of the state vector at the next moment of the current moment through a non-linear observation function. The second preset update formula is a set formula for updating the predicted value of the state vector and the predicted value of the covariance matrix of the state vector. The second preset termination condition is a pre-set condition for stopping iteration. In this embodiment, the second preset termination condition is to complete the iteration of all time steps. The updated state vector is the system state vector updated with the observed data.

[0131] The non-linear system in the UKF algorithm can be described by formula (2-1).

[0132] (2-1)

[0133] In formula (2-1), f[·] is the non-linear state function, which is the mIMK model in this embodiment; h(·) is the non-linear observation function; x is the n dimensional system state vector, which is the vector composed of the parameters to be identified in this embodiment; y is the n-dimensional system observation vector; w is the process noise vector of the covariance matrix Q; v is the observation noise vector of the covariance matrix R; is the n-dimensional input vector; k represents the k th time step, is the time, is the time step size. The UKF algorithm includes two stages, state prediction and measurement update, at each time step. The complete process of predicting the state at the k th step and the state at the k +1 step of the system is as follows.

[0134] Based on the unscented transform, according to the k th step system state vector construct a set of sigma points with a total number of 2 n +1 (i = 0, 1,..., 2n), that is, the first set of observation points.

[0135] (2-2)

[0136] In formula (2-2), is the estimated covariance matrix of, [·] i represents the i th column of the matrix in square brackets, is the scaling parameter, and n is a natural number.

[0137] The generated sigma point set is mapped to a new sigma point set through the non-linear state function f[·] (i = 0, 1,..., 2n), as shown in formula (2-3).

[0138] (2-3)

[0139] The new sigma point set is then used to predict the predicted value of the state vector at the next moment and the predicted covariance matrix of the state vector at the next moment , as shown in formula (2-4).

[0140] (2-4)

[0141] In formula (2-4), and are the weights of each sigma point in the new sigma point set , and their expressions are as shown in formula (2-5).

[0142] (2-5)

[0143] In formula (2-5), , is the scaling parameter; represents the degree of dispersion of the sigma point set near the state vector, usually set to a very small positive number; β is the parameter considering the probability distribution of the state vector x; κ is the secondary scaling parameter.

[0144] Subsequently, through the non-linear observation function, 2n + 1 observation sigma point sets (i = 0, 1,..., 2n) are generated, that is, the second observation point set, as shown in formula (2-6).

[0145] (2-6)

[0146] According to formula (2-7), the observation vector of the observation sigma point set and the matrix covariance of the observation vector can be calculated .

[0147] (2 - 7)

[0148] In formula (2 - 7), is the k step observation vector, is error covariance matrix of.

[0149] The Kalman gain of the (k + 1)-th step UKF algorithm is obtained through formula (2 - 8).

[0150] (2 - 8)

[0151] In formula (2 - 8), is the cross-covariance between the predicted value of the state vector at the next moment and the observation vector, and its calculation formula is as shown in (2 - 9).

[0152] (2 - 9)

[0153] Finally, the updated system state vector and the covariance matrix of the system state vector are obtained, as shown in formula (2 - 10).

[0154] (2 - 10)

[0155] Specifically, first, based on the refined finite element model of the steel structure member, the simulated hysteretic curve of the steel structure member under the wind load loading mode is simulated, and the cumulative plastic deformation capacity parameter of the member is identified based on this simulated hysteretic curve. In this embodiment, the mIMK model equation is used as the nonlinear state function of the UKF algorithm, and the nonlinear observation function uses the simulated hysteretic curve of the steel structure member. Among them, the state vector of the system is x = M , Λ s , Λ c , Λ k T , the observation vector is u = x 1 , the covariance matrix of the process noise is Q = diag([1×10 -3 , 5×10 -6 , 5×10 -6 , 5×10 -5 ), the covariance matrix of the observation noise is R = 1×10 -4 , and the initial value of the state vector is x​0 = [0, 0.5, 0.5, 1.5] T , the initial value of the covariance matrix of the state vector is P 0 = diag([1×10 -3 , 5×10 -5 , 5×10 -5 , 5×10 -4 ), where x 1 represents the first element of the system state vector, and the relevant parameters are set as = 0.001, β= 2, κ = 0.

[0156] After that, through the unscented transformation method, a set of sigma point sets with a total number of 2n + 1 is constructed according to the state vector at the current moment, that is, the first state point set. According to formulas (2-2) - (2-5), the state vector at the next moment and the covariance matrix of the state vector at the next moment are predicted to obtain the predicted value of the state vector at the next moment and the predicted value of the covariance matrix of the state vector at the next moment at the current moment; subsequently, through the nonlinear observation function, 2n + 1 observation sigma point sets are generated according to the predicted value of the state vector at the next moment, that is, the second observation point set. According to formulas (2-6) - (2-10), the predicted value of the state vector at the next moment and the predicted value of the covariance matrix of the state vector at the next moment are updated to obtain the state vector at the next moment and the covariance matrix of the state vector at the next moment; in this embodiment, n = 4. Repeat the above process until the iteration is completed when the second preset stop condition is satisfied, and the state vector at the last moment is the updated state vector , which is the cumulative plastic deformation capacity parameter of the steel structure member.

[0157] In a possible implementation manner, according to multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters, a hysteretic parameter model of the steel structure member is obtained through regression analysis, including:

[0158] Through the general multiple regression model, the relationship between multiple preset dimension parameters of the steel structure member and multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters is fitted, and the general multiple regression model is optimized and analyzed according to the multiple stepwise regression analysis method to obtain the hysteretic parameter model of the steel structure member.

[0159] It should be noted that the general multiple regression model is a mathematical model for regression analysis, which contains multiple regression variables. The stepwise multiple regression analysis method is a statistical regression method that can not only identify the key factors affecting the dependent variable but also eliminate the correlation between multiple dependent variables.

[0160] In this embodiment, the general multiple regression model used is as shown in formula (3-1), and the five dimensional characteristic parameters of the steel structure members are fitted with their hysteretic parameters.

[0161] (3-1)

[0162] In formula (3-1), m is the predicted hysteretic parameter of the steel structure member, a 0 、 a 1 、 a 2 、 a 3 、 a 4 、 a 5 are regression coefficients, is the web height of the steel structure member, is the web thickness of the steel structure member, is the radius of gyration of the cross-section of the steel structure member about the weak axis, d is the cross-section height of the steel structure member, P g is the axial load caused by gravity, is the axial yield load of the steel structure member, is the flange thickness of the steel structure member, is the flange width of the steel structure member.

[0163] Then, in the stepwise multiple regression analysis, a backward elimination strategy is adopted to improve the general multiple regression model by gradually eliminating the independent variables that have no significant influence on the dependent variable. The elimination criterion for the independent variable is that the significance level of its influence on the dependent variable is less than 5%. The goodness of fit of the general multiple regression model is evaluated using the coefficient of determination R 2 After stepwise multiple regression analysis, some hysteretic parameter models in the hysteretic parameter model of the steel structure member can be obtained, namely the strengthening section rotation angle θ p 、the softening section rotation angle θ pc 、the peak moment M c 、the basic strength degradation cumulative plastic deformation capacity Λ s 、the softening section strength degradation cumulative plastic deformation capacity Λ c and the unloading stiffness degradation cumulative plastic deformation capacity Λ k .

[0164] Furthermore, in this embodiment, the obtained hysteretic parameter model of the steel structure member is shown in Formulas (3-2) to (3-11).

[0165] (3-2)

[0166] (3-3)

[0167] (3-4)

[0168] (3-5)

[0169] (3-6)

[0170] θ u = 0.15rad (3-7)

[0171] (3-8)

[0172] (3-9)

[0173] (3-10)

[0174] (3-11)

[0175] In Formulas (3-2) to (3-11), is the stiffness, is the peak moment, is the rotation angle of the strengthening section, is the rotation angle of the softening section, is the residual moment; is the ultimate rotation angle, is the yield moment, F is the peak moment and the yield moment ratio, is the basic strength degradation cumulative plastic deformation capacity, is the softening section strength degradation cumulative plastic deformation capacity, is the unloading stiffness degradation cumulative plastic deformation capacity, L is the length of the steel structure member, is the shear stiffness, is the flexural stiffness, is the shear modulus, I is the moment of inertia of the cross-section of the steel structure member, is the web area of the cross-section of the steel structure member, is the Young's modulus, is the sectional plastic development coefficient of the steel structure member, is the elastic sectional modulus, is the yield stress, P g is the axial load caused by gravity, is the axial yield load of the steel structure member, is the web height of the steel structure member, is the web thickness of the steel structure member, is the radius of gyration of the cross-section of the steel structure member about the weak axis, and d is the cross-section height of the steel structure member, is the flange thickness of the steel structure member, is the flange width of the steel structure member. As Figure 3 shown, Figure 3 is a schematic diagram of the dimensions of a steel structure member provided in an embodiment of the present application.

[0176] It should be noted that among them, K 0 、 M y 、 M r 、 θ u The regression models of the four parameters do not need to be obtained by fitting through multiple regression analysis. Among them, θ u determines the ultimate rotation angle of the steel structure member and is not affected by the loading system, that is, take θ u = 0.15rad, M r is the residual strength of the member. According to existing research, take M r =0.4 M y ; K 0 and M y are less affected by the loading method and can be calculated using the models in the existing seismic load loading method, namely Formula (1-8) and Formula (1-9).

[0177] In a possible implementation, a refined finite element model for the steel structure member is constructed, including:

[0178] The four-node quadrilateral finite membrane strain linear reduced integration S4R shell element is used as the body of the steel structure member; among them, the mesh size is 25mm×25mm; the steel structure member is an H-shaped cross-section member; the material constitutive of the steel structure member is a mixed hardening model;

[0179] The top and bottom of the steel structure member are constrained by a fixed connection method, and the overall defects and local defects of the steel structure member are added to the body of the steel structure member to obtain a refined finite element model; among them, the overall defect is , and the local defect is and , L is the length of the steel structure member, d is the cross-sectional height of the steel structure member, is the cross-sectional width of the steel structure member.

[0180] It should be noted that in the process of constructing a refined finite element model through the finite element software ABAQUS, the finite element model of the H-shaped cross-section steel structure member is usually adopted to simulate the hysteretic performance of the steel structure member under wind load. As Figure 4 shown, Figure 4 is a schematic diagram of a finite element model of an H-shaped cross-section steel structure member provided by an embodiment of the present application. In Figure 4 (4-a), the top and bottom surfaces of the steel structure member are constrained by a fixed connection method; and, the overall defects and local defects of the steel structure member are considered in the model, as shown in Figure 4 (4-b) in and Figure 4 (4-c) in. Figure 4 (4-b) in represents the overall defect of the H-shaped cross-section steel structure member, Figure 4 (4-c) in represents the local defect of the H-shaped cross-section steel structure member. In this embodiment, the overall defect of the steel structure member is taken as 1 / 1000 of the specimen length, that is , and the local defect is and , where L is the length of the steel structure member, d is the cross-sectional height of the steel structure member, is the cross-sectional width of the steel structure member. In this embodiment, the mesh size of the refined finite element model of the steel structure member is taken as 25mm×25mm, and this mesh size is the best mesh size considering both calculation efficiency and calculation accuracy.

[0181] Since the thickness of the web and flange of the H-shaped cross-section steel structure member is much smaller than the dimensions in the other two directions, therefore, in this embodiment, the refined finite element model of the steel structure member is simulated by using a four-node quadrilateral finite membrane strain linear reduced integration S4R shell element, and this S4R shell element can effectively capture the overall and local buckling of the steel structure member. The material constitutive of the steel structure member adopts a mixed hardening model (nonlinear isotropic and kinematic hardening), and the von Mises yield criterion is used to identify the yield and failure of the material, where the mixed hardening model is as shown in formula (3-12).

[0182] (3-12)

[0183] In Equation (3-12), is the nonlinear kinematic hardening parameter, is the nonlinear isotropic hardening parameter, is the kinematic hardening modulus, is the cumulative plastic strain, is the kinematic hardening modulus with the cumulative plastic strain decreasing rate, is the back stress, is the equivalent yield stress of the material at zero plastic strain, is the maximum change in the yield surface size, b is the rate of change of the yield surface size with plastic strain.

[0184] In this embodiment, the material parameters are selected as follows: Young's modulus E = 200 GPa, the axial yield load of the steel structure member F ye = 380 MPa, the kinematic hardening modulus C = 3378 MPa, the kinematic hardening modulus with the cumulative plastic strain decreasing rate η = 20, the maximum change in the yield surface size Q ∞ = 90 MPa, the rate of change of the yield surface size with plastic strain b = 12.

[0185] It should be noted that in order to verify the accuracy of the above refined finite element model, the loading test data of existing H-shaped steel structure members were selected for verification, including the hysteresis test data under different axial compression ratios and different loading protocols. By comparing the moment-rotation curves of the steel structure members in the test and the deformations at the failure of the members, the accuracy of the above refined finite element model was verified. The verification method for the accuracy of the refined finite element model will not be specifically described here.

[0186] In one possible implementation, a wind load is applied to the refined finite element model and the hysteretic performance of the steel structure member is simulated to obtain the simulated hysteretic curve of the steel structure member under the wind load, including:

[0187] Obtain the wind load loading method for applying wind loads to a refined finite element model; wherein, the formulation process of the wind load loading method includes: obtaining a plurality of cycle mean levels and a plurality of cycle amplitude levels according to the requirements of the quasi-static test on steel structure members; determining the number of loadings at a plurality of cycle mean levels and the number of loadings at a plurality of cycle amplitude levels from the joint probability distribution of the cycle mean and the cycle amplitude; determining the cumulative probability values at different levels according to the plurality of cycle mean levels and the plurality of cycle amplitude levels; determining the cycle mean and the cycle amplitude at each level according to the cumulative probability distribution of the cycle mean and the cycle amplitude of the inter-story drift angle of the steel structure member and the cumulative probability values at different levels; obtaining the wind load loading method of the steel structure member under the action of wind load according to the cycle mean at each level, the cycle amplitude at each level and the number of cyclic loadings at different levels;

[0188] Use the wind load loading method to apply wind loads to the refined finite element model and perform the hysteretic performance simulation of the steel structure member to obtain the simulated hysteretic curve of the steel structure member under the action of wind load.

[0189] It should be noted that since the hysteretic performance of steel structure components under wind load is different from that under seismic load, in view of the characteristics of wind load, a special wind load loading method for wind load needs to be specified first. In this embodiment, three parameters, namely the total period, the mean period, and the period amplitude, are used to describe the performance requirements of steel structure components under wind load, so as to formulate the wind load loading system for steel structure components under wind load. Specifically, according to the requirements of the quasi-static test on steel structure components, it is necessary to analyze the response of the refined finite element model from the start of vibration to failure. By using the rain-flow counting method to decompose the time history of the structural inter-story drift angle, the mean and amplitude of the decomposed periods are statistically analyzed, so as to obtain multiple mean period levels and multiple period amplitude levels. Among them, the quasi-static test refers to the static test in which multiple reciprocating cyclic actions are applied to the steel structure component, which is a process of repeatedly loading and unloading the steel structure component to obtain information such as the strength, stiffness, and energy dissipation of the component in reciprocating vibration, and then establish the hysteretic model of the steel structure component. Then, from the perspective of probability distribution, the number of loadings at each mean period level and the number of loadings at each period amplitude level are determined from the joint probability distribution of the mean period and the period amplitude. Then, according to multiple mean period levels and multiple period amplitude levels, the cumulative probability values at different levels are determined; according to the cumulative probability distribution of the mean period and the period amplitude of the inter-story drift angle of the steel structure component, and the cumulative probability values at different levels, the mean period and the period amplitude at each level are obtained. Furthermore, according to the mean period at each level, the period amplitude at each level, and the number of cyclic loadings at different levels, the wind load loading system for steel structure components under wind load is obtained. This wind load loading system is used for the hysteretic performance simulation of steel structure components under the aforementioned wind load.

[0190] It should be noted that in order to prove that the hysteretic parameter model of the steel structure component proposed in this embodiment is better than the existing hysteretic parameter model of the steel structure component under seismic load, a comparison is made with the widely used hysteretic parameter empirical model proposed by Lignos as the comparison object. The comparison results are as Figure 5 shown. Figure 5 FIG. is a comparison schematic diagram of the hysteretic curve parameters of the steel structure component under wind load and the simulation results of the hysteretic parameter model provided by an embodiment of the present application. In Figure 5 it, the horizontal axis represents the predicted values of each hysteretic parameter obtained by substituting the dimensions of the steel structure component into different hysteretic parameter models. Among them, the orange dots represent the predicted values of each hysteretic parameter obtained by simulating with the existing hysteretic parameter model under seismic load, and the blue dots represent the predicted values of each hysteretic parameter obtained by simulating with the hysteretic parameter model under wind load; the vertical axis represents the actual values of the hysteretic parameters of the steel structure component under wind load, Figure 5The middle curve represents the hysteretic curve parameters of the steel structure member. Among them, the expressions of the hysteretic parameter empirical model proposed by Lignos can be shown by Formula (1-5) - Formula (1-7), and the following Formula (4-1) and Formula (4-2), and the stiffness K e and the yield moment M y These two parameter models were also compared with the hysteretic parameters of 1028 steel columns in the existing steel column database.

[0191] (4-1)

[0192] (4-2)

[0193] In Formula (4-1) and Formula (4-2), is the cumulative plastic deformation capacity of the basic strength degradation, is the cumulative plastic deformation capacity of the strength degradation in the softening section, is the cumulative plastic deformation capacity of the unloading stiffness degradation, is the length of the steel structure member, is the web height of the steel structure member, is the web thickness of the steel structure member, is the moment of inertia of the cross-section of the steel structure member along the weak axis, P g is the axial load caused by gravity, is the axial yield load of the steel structure member.

[0194] Among them, Figure 5 in (5-a) is the comparison schematic diagram of the simulation results of the hysteretic parameter stiffness K e ; Figure 5 in (5-b) is the comparison schematic diagram of the simulation results of the hysteretic parameter yield moment M y ; Figure 5 in (5-c) is the comparison schematic diagram of the simulation results of the ratio F of the hysteretic parameter peak moment to the yield moment ; Figure 5 in (5-d) is the comparison schematic diagram of the simulation results of the hysteretic parameter strengthening section rotation angle ; Figure 5 in (5-e) is the comparison schematic diagram of the simulation results of the hysteretic parameter softening section rotation angle ; Figure 5 in (5-f) is the comparison schematic diagram of the simulation results of the hysteretic parameter basic strength degradation cumulative plastic deformation capacity ; Figure 5Among them, (5-g) is the cumulative plastic deformation capacity of the softening section strength degradation. Schematic diagram for comparison of simulation results; Figure 5 Among them, (5-h) is the cumulative plastic deformation capacity of the unloading stiffness degradation of the hysteretic parameter. Schematic diagram for comparison of simulation results. From Figure 5 It can be seen from (5-a)-(5-b) in K e and the yield moment M y For these two parameters, the existing hysteretic parameter models based on seismic loads can achieve relatively accurate predictions; while from Figure 5 It can be seen from (5-c)-(5-h) in that for other hysteretic parameters of steel structure members, the prediction results of the existing hysteretic parameter models based on seismic loads are very different from the actual values of the hysteretic parameters of steel structure members under wind loads; while the hysteretic parameter model based on wind loads proposed according to the hysteretic loading test of steel structure members under the wind load loading system provided in this embodiment can relatively accurately predict the hysteretic parameters of steel structure members under wind loads.

[0195] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0196] Corresponding to the method for constructing a hysteretic parameter model of a steel structure member under wind loads in the above embodiment, Figure 6 The structure diagram of a device for constructing a hysteretic parameter model of a steel structure member under wind loads provided in an embodiment of the present application is shown. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown.

[0197] Referring to Figure 6 The device 2 for constructing a hysteretic parameter model of a steel structure member under wind loads in this embodiment includes:

[0198] A model construction module 21 for constructing a refined finite element model for steel structure members;

[0199] A first simulation module 22 for applying a monotonic load to the refined finite element model and simulating the monotonic loading performance of the steel structure member to obtain a simulated monotonic loading curve of the steel structure member;

[0200] A second simulation module 23 for applying a wind load to the refined finite element model and simulating the hysteretic performance of the steel structure member to obtain a simulated hysteretic curve of the steel structure member under the wind load;

[0201] A parameter identification module 24 is configured to respectively identify parameters of the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure member. The hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters.

[0202] A model determination module 25 is configured to obtain a hysteretic parameter model of the steel structure member through regression analysis based on the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters. The hysteretic parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load.

[0203] It can be understood that in this embodiment, for the construction device 2 of the hysteretic parameter model of the steel structure member under wind load, first, a refined finite element model for the steel structure member is constructed by the model construction module 21; then, a monotonic load is applied to the refined finite element model by the first simulation module 22 to simulate the monotonic loading performance of the steel structure member, and a simulated monotonic loading curve of the steel structure member under the monotonic load is obtained; and the second simulation module 23 applies a wind load to the refined finite element model to simulate the hysteretic performance of the steel structure member, and a simulated hysteretic curve of the steel structure member under the wind load is obtained; thereafter, the parameter identification module 24 respectively identifies parameters of the simulated monotonic loading curve and the simulated hysteretic curve to obtain the hysteretic parameters of the steel structure member. The hysteretic parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters; finally, the model determination module 25 determines a hysteretic parameter model of the steel structure member according to the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters. The hysteretic parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load. In this application, by identifying parameters of the simulated monotonic loading curve and the simulated hysteretic curve obtained by simulating the refined finite element model, the hysteretic parameters of the steel structure member are determined, and a hysteretic parameter model of the steel structure member that characterizes the relationship between the characteristic dimensions and the hysteretic parameters of the steel structure member under wind load is obtained. Through this hysteretic parameter model of the steel structure member, the hysteretic parameters of the steel structure member under wind load can be predicted more accurately, so that the response performance of the steel structure member under wind load can be calculated more accurately.

[0204] It should be noted that for the information interaction, execution process, etc. between the modules in the above construction device 2 of the hysteretic parameter model of the steel structure member under wind load, since it is based on the same concept as the method embodiment of this application, its specific functions and the technical effects brought are specifically described in the method embodiment part and will not be elaborated here.

[0205] The embodiment of this application also provides a terminal device, as Figure 7 shown, Figure 7The figure is a schematic structural diagram of a terminal device provided by an embodiment of the present application. Refer to Figure 7 , the terminal device 3 in this embodiment includes: a memory 31, a processor 32, and a computer program stored in the memory 31 and executable on the processor 32. When the processor 32 executes the computer program, it implements the steps in the method embodiment for constructing the hysteretic parameter model of the steel structure member under wind load described in any one of the above.

[0206] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it can implement the steps in the above-mentioned various method embodiments.

[0207] The embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, it enables the mobile terminal to implement the steps in the above-mentioned various method embodiments when executed.

[0208] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps in the above-mentioned various method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0209] In the above embodiments, the descriptions of the various embodiments have their own focuses. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0210] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0211] In the embodiments provided in this application, it should be understood that the disclosed device / network device and method can be implemented in other ways. For example, the device / network device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0212] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0213] The above embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements 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 this application, and should all be included in the protection scope of this application.

Claims

1. A method for constructing a hysteresis parameter model of a steel structure component under wind load, characterized in that: include: Construct a refined finite element model for steel structure components; Applying a monotonic load to the refined finite element model and simulating the monotonic loading performance of the steel structure component to obtain a simulated monotonic loading curve of the steel structure component under the monotonic load; Applying wind load to the refined finite element model and simulating the hysteresis performance of the steel structure component to obtain a simulated hysteresis curve of the steel structure component under the wind load; Performing parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve respectively to obtain hysteresis parameters of the steel structure member; wherein the hysteresis parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters; According to the multiple skeleton curve parameters and the multiple cumulative plastic deformation capacity parameters, a hysteresis parameter model of a steel structure component is obtained through regression analysis, wherein the hysteresis parameter model of a steel structure component is used to characterize the relationship between the characteristic size of the steel structure component and the hysteresis parameter under the action of wind load; wherein, The hysteresis parameter model of the steel structure member is: ； ； ； ； ； θ u = 0.15rad ； ； ； ； ； in, is the stiffness, is the peak bending moment, To strengthen the segment corner, is the softening segment angle, is the residual bending moment, is the limit turning angle, is the yield moment, F Peak bending moment Yield moment The ratio of is the accumulated plastic deformation capacity of basic strength degradation, is the accumulated plastic deformation capacity of the softening section strength degradation, is the accumulated plastic deformation capacity of unloading stiffness degradation, L is the length of the steel structure member, is the shear stiffness, is the flexural stiffness, is the shear modulus, I is the moment of inertia of the cross section of the steel structure member, is the web area of ​​the cross section of the steel structural member, is Young's modulus, is the cross-section plastic development coefficient of the steel structure member, is the elastic section modulus, is the yield stress, P g is the axial load caused by gravity, is the axial yield load of the steel structure member, is the web height of the steel structure member, is the web thickness of the steel structure member, is the radius of inertia of the cross section of the steel structure member along the weak axis, d is the cross section height of the steel structure member, is the flange thickness of the steel structure member, is the flange width of the steel structure member; And, the constructing of a refined finite element model for a steel structure component includes: A four-node quadrilateral finite membrane strain linear reduced integral S4R shell unit is used as the body of the steel structure component; wherein the mesh size is 25 mm×25 mm; the steel structure component is an H-section component; and the material constitutive model of the steel structure component is a mixed hardening model; The top and bottom of the steel structure member are constrained by fixing, and the overall defect and local defect of the steel structure member are added to the body of the steel structure member to obtain the refined finite element model; wherein the overall defect is , the local defect is and , L is the length of the steel structure member, d is the cross-sectional height of the steel structure member, is the flange width of the steel structure member.

2. The method for constructing a hysteresis parameter model of a steel structure member under wind load according to claim 1, characterized in that: The performing parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve respectively to obtain the hysteresis parameters of the steel structure member comprises: The simulated monotonic loading curve is identified by the least square method to obtain a plurality of skeleton curve parameters in the hysteresis parameters of the steel structure component; wherein the skeleton curve parameters include stiffness K e , Strengthen the corner θ p , Softening section angle θ pc , Extreme turning angle θ u , yield moment M y , Peak bending moment M c , residual bending moment M r ; According to the modified hysteresis constitutive mIMK model, the simulated hysteresis curve is identified by the unscented Kalman filter UKF algorithm to obtain a plurality of cumulative plastic deformation capacity parameters in the hysteresis parameters of the steel structure component, wherein the cumulative plastic deformation capacity parameters include basic strength degradation cumulative plastic deformation capacity Λ s , Softening stage strength degradation Cumulative plastic deformation capacity Λ c , Unloading stiffness degradation Accumulated plastic deformation capacity Λ k .

3. The method for constructing a hysteresis parameter model of a steel structure member under wind load according to claim 2, characterized in that: The method of identifying the simulated monotonic loading curve by the least square method to obtain a plurality of skeleton curve parameters in the hysteresis parameters of the steel structure component includes: Using a skeleton curve model to identify the simulated monotonic loading curve, and obtaining a skeleton curve function of the steel structure component; The partial derivative of the skeleton curve function of the steel structure component is calculated based on the initial value of the parameter vector to obtain the Jacobian matrix corresponding to the skeleton curve function; wherein the parameter vector is , ; The initial value of the parameter vector is determined according to the hysteresis parameter model of the steel structure member under the earthquake load mode; The parameter vector is iteratively calculated according to the residual vector and the Jacobian matrix until the iteration is stopped when a first preset termination condition is met, thereby obtaining an updated parameter vector; wherein the updated parameter vector is the skeleton curve parameter of the steel structure component.

4. The method for constructing a hysteresis parameter model of a steel structure member under wind load according to claim 2, characterized in that: According to the modified hysteresis constitutive mIMK model, the simulated hysteresis curve is identified by using the unscented Kalman filter UKF algorithm to obtain multiple cumulative plastic deformation capacity parameters in the hysteresis parameters of the steel structure component, including: Using the mIMK model as a nonlinear state function of the UKF algorithm, and using the simulated hysteresis curve of the steel structure member as a nonlinear observation function; Constructing a first state point set according to the state vector at the current moment and a first preset generation rule by an untraceable transformation method; Predict the state vector and the covariance matrix of the state vector according to a first preset prediction formula to obtain a predicted value of the state vector at the next moment of the current moment and a predicted value of the covariance matrix of the state vector at the next moment; Constructing a second set of observation points according to the predicted value of the state vector at the next moment through the nonlinear observation function; The predicted value of the state vector at the next moment and the predicted value of the covariance matrix of the state vector at the next moment are updated according to a second preset update formula to obtain the state vector at the next moment and the covariance matrix of the state vector at the next moment; The state vector at the next moment and the covariance matrix of the state vector at the next moment are iteratively updated until the iteration is stopped when a second preset termination condition is met, to obtain an updated state vector, wherein the updated state vector is the cumulative plastic deformation capacity parameter of the steel structure component.

5. The method for constructing a hysteresis parameter model of a steel structure member under wind load according to claim 3 or claim 4, characterized in that: The method of obtaining a hysteresis parameter model of a steel structure member by regression analysis based on the plurality of skeleton curve parameters and the plurality of cumulative plastic deformation capacity parameters comprises: Through a universal multivariate regression model, the relationship between multiple preset size parameters of the steel structure component and the multiple skeleton curve parameters and the multiple cumulative plastic deformation capacity parameters is fitted, and the universal multivariate regression model is optimized and analyzed according to the multivariate stepwise regression analysis method to obtain the hysteresis parameter model of the steel structure component.

6. The method for constructing a hysteresis parameter model of a steel structure member under wind load according to claim 1, characterized in that: Applying wind load to the refined finite element model and simulating the hysteresis performance of the steel structure component to obtain a simulated hysteresis curve of the steel structure component under the wind load includes: Obtain a wind load loading method for applying the wind load to the refined finite element model; wherein the formulation process of the wind load loading method includes: obtaining multiple cycle mean levels and multiple cycle amplitude levels according to the requirement of conducting a quasi-static test on the steel structure component; determining the number of loading times at multiple cycle mean levels and the number of loading times at multiple cycle amplitude levels from the joint probability distribution of the cycle mean and the cycle amplitude; determining the cumulative probability values ​​at different levels according to the multiple cycle mean levels and the multiple cycle amplitude levels; determining the cycle mean and cycle amplitude at each level according to the cumulative probability distribution of the cycle mean and cycle amplitude of the inter-story displacement angle of the steel structure component and the cumulative probability values ​​at different levels; obtaining the wind load loading method of the steel structure component under the action of wind load according to the cycle mean at each level, the cycle amplitude at each level and the number of cyclic loading at different levels; Using the wind load loading method, a wind load is applied to the refined finite element model and the hysteresis performance of the steel structure component is simulated to obtain a simulated hysteresis curve of the steel structure component under the wind load.

7. A device for constructing a hysteresis parameter model of a steel structure member under wind load, characterized in that: include: Model building module, used to build refined finite element models for steel structure components; A first simulation module is used to apply a monotonic load to the refined finite element model and simulate the monotonic loading performance of the steel structure component to obtain a simulated monotonic loading curve of the steel structure component; A second simulation module is used to apply wind load to the refined finite element model and simulate the hysteresis performance of the steel structure component to obtain a simulated hysteresis curve of the steel structure component under the wind load; A parameter identification module, used to perform parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve respectively, to obtain hysteresis parameters of the steel structure member; wherein the hysteresis parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters; A model determination module is used to obtain a hysteresis parameter model of a steel structure component through regression analysis according to the multiple skeleton curve parameters and the multiple cumulative plastic deformation capacity parameters, wherein the hysteresis parameter model of the steel structure component is used to characterize the relationship between the characteristic size and the hysteresis parameter of the steel structure component under the action of wind load; wherein, The hysteresis parameter model of the steel structure member is: ； ； ； ； ； θ u = 0.15rad ； ； ； ； ； in, is the stiffness, is the peak bending moment, To strengthen the segment corner, is the softening segment angle, is the residual bending moment, is the limit turning angle, is the yield moment, F Peak bending moment and yield moment The ratio of is the accumulated plastic deformation capacity of basic strength degradation, is the accumulated plastic deformation capacity of the softening section strength degradation, is the accumulated plastic deformation capacity of unloading stiffness degradation, L is the length of the steel structure member, is the shear stiffness, is the flexural stiffness, is the shear modulus, I is the moment of inertia of the cross section of the steel structure member, is the web area of ​​the cross section of the steel structural member, is Young's modulus, is the cross-section plastic development coefficient of the steel structure member, is the elastic section modulus, is the yield stress, P g is the axial load caused by gravity, is the axial yield load of the steel structure member, is the web height of the steel structure member, is the web thickness of the steel structure member, is the radius of inertia of the cross section of the steel structure member along the weak axis, d is the cross section height of the steel structure member, is the flange thickness of the steel structure member, is the flange width of the steel structure member; And, the model building module is specifically used for: A four-node quadrilateral finite membrane strain linear reduced integral S4R shell unit is used as the body of the steel structure component; wherein the mesh size is 25 mm×25 mm; the steel structure component is an H-section component; and the material constitutive model of the steel structure component is a mixed hardening model; The top and bottom of the steel structure member are constrained by fixing, and the overall defect and local defect of the steel structure member are added to the body of the steel structure member to obtain the refined finite element model; wherein the overall defect is , the local defect is and , L is the length of the steel structure member, d is the cross-sectional height of the steel structure member, is the flange width of the steel structure member.

8. A terminal device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

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