Method and device for constructing hysteretic parameter model of steel structural member under action of wind load

Abstract

The invention is suitable for the technical field of steel structure wind-induced dynamic response analysis, and provides a construction method and device for a hysteresis parameter model of a steel structure component under the wind load effect, and the method comprises the steps: constructing a refined finite element model of the steel structure component; monotonic load is applied to the steel structural member, monotonic loading performance simulation of the steel structural member is carried out, and a simulated monotonic loading curve of the steel structural member under the monotonic load effect is obtained; applying a wind load to the steel structural member and simulating the hysteretic performance of the steel structural member to obtain a simulated hysteretic curve of the steel structural member under the action of the wind load; performing parameter identification on the simulated monotonic loading curve and the simulated hysteretic curve to obtain 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, a hysteresis parameter model of the steel structural member is obtained through regression analysis, and hysteresis parameters and response performance of the steel structural member under the wind load effect can be predicted more accurately.

Description

Technical Field

[0001] The present application belongs to the technical field of wind-induced dynamic response analysis of steel structures, and in particular, relates to a method and device for constructing a hysteresis parameter model of a steel structure component under wind load. Background Art

[0002] The hysteresis parameters of steel structure components are key parameters for controlling the strength and stiffness degradation of steel structure components under external loads. The hysteresis parameters of steel structure components are usually determined based on the quasi-static loading test of the components. At present, the existing technology has obtained the relationship between component size and component hysteresis parameters (i.e., the hysteresis parameter model of steel structure components) through the quasi-static loading test data of a large number of components and statistical analysis methods. The hysteresis parameters of steel structure components can be easily obtained by simply bringing the component size into the hysteresis parameter model of steel structure components, which is used for structural response calculation and analysis, and has very high practicality.

[0003] However, the existing hysteresis parameter models of steel structure components are usually obtained after conducting a large number of quasi-static loading tests on steel structure components based on the seismic loading protocol. However, the hysteresis performance of steel structure components is closely related to their loading history. There is a very obvious difference between wind load and seismic load. The seismic load can be approximately regarded as a random load with zero mean, while the wind load is a random load with a non-zero mean, and there is also a significant difference 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, the existing hysteresis parameter model of steel structure components proposed based on seismic load is used to analyze the response performance of steel structure components under wind load, which may lead to inaccurate response analysis results. Summary of the invention

[0004] The embodiments of the present application provide a method and device for constructing a hysteresis parameter model of a steel structure component under wind load, which can solve the problem of low accuracy when calculating the response performance of a steel structure component under wind load using an existing hysteresis parameter model.

[0005] In a first aspect, an embodiment of the present application provides a method for constructing a hysteresis parameter model of a steel structure member under wind load, the method comprising: 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 the steel structure component is obtained through regression analysis, wherein the hysteresis parameter model of the 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.

[0006] In a possible implementation manner of the first aspect, the performing parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve respectively to obtain the hysteresis parameter of the steel structure member includes: 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 .

[0007] In a possible implementation manner of the first aspect, the identifying the simulated monotonic loading curve by the least square method to obtain a plurality of the 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.

[0008] In a possible implementation of the first aspect, the simulated hysteresis curve is identified by an unscented Kalman filter (UKF) algorithm according to the modified hysteresis constitutive mIMK model to obtain a plurality of cumulative plastic deformation capacity parameters in the hysteresis parameters of the steel structure member, 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.

[0009] In a possible implementation manner of the first aspect, obtaining the hysteresis parameter model of the steel structure member through regression analysis according to the multiple skeleton curve parameters and the multiple cumulative plastic deformation capacity parameters includes: 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.

[0010] In a possible implementation manner of the first aspect, 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 gis 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.

[0011] In a possible implementation of the first aspect, constructing a refined finite element model for the 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 cross-sectional width of the steel structure member.

[0012] In a possible implementation of the first aspect, applying a 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.

[0013] In a second aspect, an embodiment of the present application provides a device for constructing a hysteresis parameter model of a steel structure member under wind load, comprising: 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 based on 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 of the steel structure component and the hysteresis parameter under the action of wind load.

[0014] In a third aspect, an embodiment of the present application provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method for constructing a hysteresis parameter model of a steel structure component under wind load as described in any one of the above items.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method for constructing a hysteresis parameter model of a steel structure component under wind load as described in any of the above items.

[0016] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device executes the method for constructing a hysteresis parameter model of a steel structure member under wind load as described in any one of the first aspects above.

[0017] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: The embodiment of the present application provides a method for constructing a hysteresis parameter model of a steel structure component under wind load, the method comprising: constructing a refined finite element model for the steel structure component; 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; and applying a 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 component; wherein the hysteresis parameters include multiple skeleton curve parameters and multiple 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 the steel structure component is obtained through regression analysis, wherein the hysteresis parameter model of the steel structure component is used to characterize the relationship between the characteristic size of the steel structure component and the hysteresis parameter under wind load. The present application performs parameter identification on a simulated monotonic loading curve and a simulated hysteresis curve obtained by simulating a refined finite element model, determines the hysteresis parameters of a steel structure component, and obtains a hysteresis parameter model of a steel structure component that characterizes the relationship between the characteristic dimensions of the steel structure component under wind load and the hysteresis parameters. The hysteresis parameter model of the steel structure component can be used to more accurately predict the hysteresis parameters of the steel structure component under wind load, thereby more accurately calculating the response performance of the steel structure component under wind load. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 It is a flow chart of a method for constructing a hysteresis parameter model of a steel structure member under wind load provided in one embodiment of the present application; Figure 2 is a schematic diagram of a mIMK model provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the dimensions of a steel structure member provided in one embodiment of the present application; Figure 4 A schematic diagram of a finite element model of an H-section steel structure member provided in one embodiment of the present application; Figure 5 It is a schematic diagram of a comparison between hysteresis curve parameters of a steel structure member under wind load and simulation results of a hysteresis parameter model provided by an embodiment of the present application; Figure 6 It is a structural schematic diagram of a device for constructing a hysteresis parameter model of a steel structure member under wind load provided in one embodiment of the present application; Figure 7 It is a structural diagram of a terminal device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0020] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may 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 prevent unnecessary details from obstructing the description of the present application.

[0021] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of 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 combinations thereof.

[0022] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0023] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0024] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0025] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0026] See also Figure 1 , Figure 1 1 is a flow chart of a method for constructing a hysteresis parameter model of a steel structure component under wind load provided by an embodiment of the present application. The method comprises: S11. Construct a refined finite element model for steel structure components; S12, 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; S13, 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; S14, performing parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve respectively to obtain hysteresis parameters of the steel structure component; wherein the hysteresis parameters include a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters; S15. According to a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters, a hysteresis parameter model of a steel structure member is obtained through regression analysis, wherein the hysteresis parameter model of a steel structure member is used to characterize the relationship between a characteristic size of a steel structure member under wind load and a hysteresis parameter.

[0027] It should be noted that, in this embodiment, the execution subject may be a terminal device such as a server, and no specific limitation is made to this.

[0028] In step S11, the refined finite element model is a digital model used to simulate and analyze the mechanical properties of steel structure components 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 components under monotonic loading or the hysteresis characteristics under wind load, and the refined finite element model is a pre-built model.

[0029] In step S12, monotonic load refers to a load that increases monotonically over time and does not show periodic changes. In the structural analysis process of steel structure components, monotonic loads are used to evaluate the monotonic loading performance of steel structure components. Monotonic loading performance is the mechanical property exhibited by steel structure components when subjected to monotonic loading, including strength, stiffness, ductility, etc. The monotonic loading curve is a relationship curve between the deformation and load of a component under a monotonic load, reflecting the performance of the component under a monotonic load. In this embodiment, a monotonic load is applied to the refined finite element model, and its monotonic loading performance is simulated, thereby obtaining a monotonic loading curve of the steel structure component under this monotonic load, that is, a simulated monotonic loading curve.

[0030] In step S13, wind load refers to the effect on the component caused by wind. Hysteresis performance is the force-deformation relationship of a component under a reciprocating load. In this embodiment, it refers to the energy dissipation capacity and cumulative damage of the component under the action of wind load. Hysteresis performance is usually represented by a hysteresis curve, which reflects the relationship curve between the deformation and load of the component under the action of periodic load. In this embodiment, by applying wind load to the refined finite element model, the hysteresis performance is simulated, so as to obtain the hysteresis curve of the steel structure component under this wind load, that is, the simulated hysteresis curve.

[0031] In step S14, the hysteresis parameters are 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 hysteresis behavior of the component, which is an abstraction and simplification of the hysteresis behavior of the 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 the strength, stiffness, energy dissipation and other parameters of the component under reciprocating loads. Its function is to obtain the strength, stiffness, energy dissipation and other parameters of the component. In this embodiment, the hysteresis parameters of the steel structure component are parameters used to describe the mechanical properties of the component under cyclic loading in the process of simulating the hysteresis curve. These parameters can reflect the deformation, energy dissipation and recovery ability of the component after multiple loading and unloading. The hysteresis parameters of the steel structure component include multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters. Among them, the skeleton curve parameters reflect the characteristic point parameters of the main mechanical properties of the component, such as stiffness K e , Strengthen the corner θ p , Softening section angle θ pc , Extreme turning angle θ u , yield moment M y , Peak bending momentM 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 loads, reflecting the fatigue life and seismic performance of the component, including the basic strength degradation plastic deformation capacity Λ s , Softening stage 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, a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters can be obtained.

[0032] In step S15, the hysteresis parameter model of the steel structure component is a set of mathematical expressions between the component size / stress state and the hysteresis parameter obtained by regression analysis based on a large number of component data. The function of the hysteresis parameter model is to obtain the undetermined parameters in the hysteresis model, that is, the hysteresis parameters. In this embodiment, by performing regression analysis on the identified multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters, a hysteresis 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 hysteresis parameter under the action of wind load.

[0033] It can be understood that an embodiment of the present application provides a method for constructing a hysteresis parameter model of a steel structure member under wind load, the method comprising: 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 hysteresis performance of the steel structure member to obtain a simulated hysteresis curve of the steel structure member under the wind load; 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; wherein the hysteresis parameters include multiple skeleton curve parameters and multiple 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 the steel structure member is obtained through regression analysis, wherein the hysteresis parameter model of the steel structure member is used to characterize the relationship between the characteristic dimensions of the steel structure member under wind load and the hysteresis parameters. The present application performs parameter identification on a simulated monotonic loading curve and a simulated hysteresis curve obtained by simulating a refined finite element model, determines the hysteresis parameters of a steel structure component, and obtains a hysteresis parameter model of a steel structure component that characterizes the relationship between the characteristic dimensions of the steel structure component under wind load and the hysteresis parameters. The hysteresis parameter model of the steel structure component can be used to more accurately predict the hysteresis parameters of the steel structure component under wind load, thereby more accurately calculating the response performance of the steel structure component under wind load.

[0034] In a possible implementation, parameter identification is performed on the simulated monotonic loading curve and the simulated hysteresis curve respectively to obtain the hysteresis parameters of the steel structure component, including: The simulated monotonic loading curve is identified by the least square method to obtain multiple 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 multiple cumulative plastic deformation capacity parameters in the hysteresis parameters of the steel structure components, among which the cumulative plastic deformation capacity parameters include basic strength degradation cumulative plastic deformation capacity Λs , Softening stage strength degradation Cumulative plastic deformation capacity Λ c , Unloading stiffness degradation Accumulated plastic deformation capacity Λ k .

[0035] It should be noted that the least square method is to find the best function matching of the data by minimizing the sum of squares of the errors. In this embodiment, the least square method is used to fit the simulated monotonic loading curve to identify multiple skeleton curve parameters. K e Indicates the ratio of the bending moment to the rotation angle of the component in the initial loading stage; the rotation angle of the strengthening section θ p Indicates the turning angle corresponding to the turning point from the elastic stage to the plastic strengthening stage in the monotonic loading curve; softening section turning angle θ pc Indicates the angle at which the load begins to decrease from the peak load (i.e., entering the softening stage); limit angle θ u Indicates the rotation angle when the member reaches the ultimate bearing capacity (usually the bearing capacity drops to a specified value); yield moment M y Indicates the yield moment value when the component begins to enter the plastic stage; peak moment M c Indicates the maximum bending moment that a component can withstand during monotonic loading; residual bending moment M r It indicates the residual bending moment value of the component after loading and unloading cycles.

[0036] The modified hysteretic constitutive model (modified Ibarra Medina Krawinkler, mIMK) is a mathematical model used to describe the mechanical behavior of components under cyclic loading (such as wind load, earthquake load). Figure 2 As shown, Figure 2 Schematic diagram of a mIMK model provided in an embodiment of the present application. Figure 2 In the figure, the skeleton curve of the mIMK model is defined by three strength parameters and four deformation parameters, namely M y represents the yield moment, M c = α×M y represents the peak bending moment of the member, M r represents the residual bending moment of the member, θ y represents the yield angle, θ p represents the rotation angle of the component reinforcement section, θpc represents the softening section angle, θ u Represents the limit rotation angle. The mIMK model has three performance degradation modes, namely basic strength degradation, softening section strength degradation and unloading stiffness degradation, which correspond 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, the component begins to degrade in performance. The degradation rule is shown in formula (1-1).

[0037] (1-1) In formula (1-1), is the cumulative energy consumption capacity of basic strength degradation, is the cumulative energy consumption capacity of the softening section strength degradation, is the cumulative energy dissipation capacity of unloading stiffness degradation, is the accumulated plastic deformation capacity of basic strength degradation, is the accumulated plastic deformation capacity of the softening section strength degradation, The accumulated plastic deformation capacity is the unloading stiffness degradation. >0, The larger the value, the slower the performance degradation rate of the component in this performance degradation mode. Λ = 0, it indicates that the component does not have this performance degradation mode. The degraded strength and degraded stiffness of the component can be calculated by formula (1-2).

[0038] (1-2) 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-1th loading cycle, is the stiffness of the component at the i-1th loading cycle, is the degradation parameter based on hysteresis energy dissipation, subscript There are three performance degradation models, namely, 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. The expression is shown in formula (1-3).

[0039] (1-3) In formula (1-3), For the component i The energy dissipated in a loading cycle is For the component jThe energy dissipated in a loading cycle is For components in Cumulative energy consumption capacity in three performance degradation models, It is an empirical parameter and is usually taken as 1.0.

[0040] It should be noted that the Unscented Kalman Filter (UKF) is an algorithm for state assessment 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 suitable for the standard Kalman filter framework under the linear assumption through unscented transformation. It estimates the approximate probability density distribution function of the nonlinear state space model through a series of sample points, avoids the error caused by approximate linearization, and has higher accuracy. In this example, the nonlinear system equation used is the mIMK hysteresis 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 hysteresis curve, thereby obtaining multiple cumulative plastic deformation capacity parameters.

[0041] In a possible implementation, the simulated monotonic loading curve is identified by the least square method to obtain multiple skeleton curve parameters in the hysteresis parameters of the steel structure component, including: The skeleton curve model is used to identify the simulated monotonic loading curve and obtain the 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; where the parameter vector is , ; The initial value of the parameter vector is determined according to the hysteresis parameter model of the steel structure component under the earthquake load mode; According to the residual vector and the Jacobian matrix, the parameter vector is iteratively calculated 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 a skeleton curve parameter of the steel structure component.

[0042] Specifically, firstly, according to the refined finite element model of the steel structure component, the simulated monotonic loading curve of the component is simulated. y = y ( θ ), the skeleton curve of the component is identified based on the simulated monotonic loading curve, and the skeleton curve function parameters of the steel structure component are obtained. Among them, the skeleton curve model used by the identification function is As shown in formula (1-4).

[0043] (1-4) In formula (1-4), is the stiffness, For the corner, is the yield angle, is the peak bending moment, is the yield moment, To strengthen the segment corner, is the softening segment angle, is the residual bending moment. Secondly, set the parameter vector , , parameter vector The initial value of is determined based on the existing hysteresis parameter model of steel structure components under the seismic load loading system. Among them, the parameter vector is the parameter used to describe the skeleton curve function of the steel structure component. The seismic load loading system is an existing hysteresis performance test loading rule formulated based on the response characteristics of steel structure components under seismic loads. 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).

[0044] (1-5) (1-6) (1-7) (1-8) In formula (1-5) to formula (1-8), F is the peak bending moment Yield moment The ratio of To strengthen the segment corner, is the softening segment angle, is the residual bending 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 inertia of the cross section of the steel structure member along the weak axis, γ Represents the cross-section plastic development coefficient. For the strong axis and weak axis of the H-section, γ The values ​​of are 1.05 and 1.2 respectively, and for hollow sections, γ Then 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 It can be calculated using formula (1-9).

[0045] (1-9) 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 = 200GPa, G = 79.3GPa.

[0046] After determining the initial value of the parameter vector, 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 its corresponding Jacobian matrix J, as shown in formula (1-10). The Jacobian matrix J can describe the rate of change of the skeleton curve function with respect to the parameter vector.

[0047] (1-10) In formula (1-10), N represents the number of observations, that is, the number of discrete points of the simulated monotonic loading curve of the steel structure component. represents the Nth observation value, i.e., the Nth rotation angle of the simulated monotonic loading curve of the steel structure component; represents the change of the skeleton curve function with respect to stiffness, represents the change of the skeleton curve function with respect to the angle of the enhanced segment, Represents the change of the skeleton curve function with respect to the softening segment angle, represents the change of the skeleton curve function with respect to the limit rotation angle, represents the variation of the skeleton curve function with respect to the yield moment, represents the variation of the skeleton curve function with respect to the peak bending moment, Represents the variation of the skeleton curve function with respect to the residual bending moment.

[0048] 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).

[0049] (1-11) In formula (1-11), is the residual vector, represents the Nth moment value of the monotonic loading curve of the steel structure member, Represented by parameter vector The bending moment value of the steel structure component is calculated based on the skeleton curve model.

[0050] Then, the parameter vector is calculated based on the residual vector and the Jacobian matrix. Update as shown in formula (1-12) to obtain the updated parameter vector.

[0051] (1-12) In formula (1-12), Represents the iteration i The parameter vector of times, Represents the iteration i +1 degree parameter vector, is the update vector.

[0052] Repeat the above process until the update vector Δ α When it approaches 0, the parameter vector No more updating is done to obtain an updated parameter vector. At this time, the updated parameter vector obtained is the skeleton curve parameter of the hysteresis curve.

[0053] It should be noted that the first preset termination condition is a pre-set condition for stopping iteration. In this embodiment, the first preset termination condition is to update the vector Δ α When it approaches 0, the iteration stops.

[0054] In a possible implementation, according to the modified hysteresis constitutive mIMK model, the simulated hysteresis curve is identified by the unscented Kalman filter UKF algorithm to obtain multiple cumulative plastic deformation capacity parameters in the hysteresis parameters of the steel structure component, including: The mIMK model is used as the nonlinear state function of the UKF algorithm, and the simulated hysteresis curve of the steel structure component is used as the 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 the first preset prediction formula 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; Constructing a second set of observation points according to the predicted value of the state vector at the next moment through a nonlinear observation function; According to a 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; 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, and an updated state vector is obtained, wherein the updated state vector is the cumulative plastic deformation capacity parameter of the steel structure component.

[0055] It should be noted that the nonlinear state function is a function that describes the state of the system and represents 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 information about 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 hysteresis curve of the steel structure component is used as the nonlinear observation function.

[0056] Untraceable transformation is a mathematical method used to generate a set of sample points (i.e., sigma points) from the original probability distribution, which can accurately approximate the higher-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 discreteness between variables. The first preset generation rule is a pre-set rule for generating the first state point set. The first state point set is a set of sigma points generated based on the state vector at the current moment.

[0057] The first preset prediction formula is a mathematical formula set to predict the future state based on the current state. The state vector prediction value of the next moment at the current moment refers to the prediction value obtained by predicting the state vector at the current moment according to the nonlinear state function of the system in the UKF algorithm. The state vector prediction value of the next moment is calculated based on the state vector at the current moment, the system input and the dynamic characteristics of the system. Accordingly, in the UKF algorithm, the covariance matrix of the state vector at the current moment is predicted according to the nonlinear function of the system to obtain the covariance matrix prediction value of the state vector at the next moment.

[0058] The second observation point set is a set of sigma points constructed by a nonlinear observation function based on the state vector prediction value of the next moment at the current moment. The second preset update formula is a formula set to update the state vector prediction value and the covariance matrix prediction value 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 after being updated by the observation data.

[0059] The nonlinear system in the UKF algorithm can be described by formula (2-1).

[0060] (2-1) In formula (2-1), f[·] is a nonlinear state function, which is the mIMK model in this embodiment; h(·) is a nonlinear observation function; x is n dimensional system state vector, which in this embodiment is a vector composed of parameters to be identified; y is an 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 an n-dimensional input vector; k Indicates k time steps, For time, The UKF algorithm includes two stages: state prediction and measurement update at each time step. k Step state prediction k The complete process of +1 step status is as follows.

[0061] Based on the unscented transformation, according to k Step system state vector Construct a set of 2 n +1 sigma point set (i=0,1,...,2n), that is, the first observation point set.

[0062] (2-2) In formula (2-2), for The estimated covariance matrix of , [·] i The square bracket matrix i List, is the scaling parameter, and n is a natural number.

[0063] The generated sigma point set is mapped to a new sigma point set through a nonlinear state function f[·] (i=0,1,...,2n), as shown in formula (2-3).

[0064] (2-3) The new sigma point set is then used to predict the state vector prediction value at the next moment And the covariance matrix prediction value of the state vector at the next moment , as shown in formula (2-4).

[0065] (2-4) In formula (2-4), and is the new sigma point set The weight of each sigma point in is expressed as shown in formula (2-5).

[0066] (2-5) In formula (2-5), , is the scaling parameter; Indicates the degree of discreteness of the sigma point set near the state vector, usually set to a very small positive number; β is the parameter of the probability distribution of the state vector x; κ is the secondary scaling parameter.

[0067] Then, through the nonlinear observation function, 2n+1 observation sigma point sets are generated (i=0,1,...,2n), that is, the second observation point set, as shown in formula (2-6).

[0068] (2-6) According to formula (2-7), the observed sigma point set can be calculated The observation vector and the matrix covariance of the observation vector .

[0069] (2-7) In formula (2-7), For the k step observation vector, for The error covariance matrix of .

[0070] Kalman gain of UKF algorithm at step k+1 Obtained by formula (2-8).

[0071] (2-8) 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 shown in (2-9).

[0072] (2-9) Finally, the updated system state vector is obtained and the covariance matrix of the system state vector , as shown in formula (2-10).

[0073] (2-10) Specifically, first, according to the refined finite element model of the steel structure component, the simulated hysteresis curve of the steel structure component under the wind load mode is simulated, and the cumulative plastic deformation capacity parameter of the component is identified based on the simulated hysteresis 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 hysteresis curve of the steel structure component, where 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 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 , the initial value of the state vector is x0 = [0, 0.5, 0.5, 1.5] T , the initial value of the covariance matrix of the state vector is P0= diag([1×10 -3 , 5×10 -5 , 5×10 -5 , 5×10 -4 ]),in, x 1 represents the first element of the system state vector, and the relevant parameters are set to = 0.001, β= 2, κ =0.

[0074] Afterwards, a set of 2n+1 sigma point sets, i.e., the first state point set, is constructed according to the state vector at the current moment by an untraceable transformation method. The state vector at the next moment and the covariance matrix of the state vector at the next moment are predicted according to formula (2-2) to formula (2-5), and 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 are obtained; subsequently, 2n+1 observation sigma point sets, i.e., the second observation point set, are generated according to the predicted value of the state vector at the next moment by a 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 formula (2-6) to formula (2-10), and the state vector at the next moment and the covariance matrix of the state vector at the next moment are obtained; in this embodiment, n=4. Repeat the above process until the second preset stop condition is met and the iteration is completed, 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 component.

[0075] In a possible implementation, a hysteresis parameter model of a steel structure member is obtained through regression analysis according to a plurality of skeleton curve parameters and a plurality of cumulative plastic deformation capacity parameters, including: Through a universal multiple regression model, the relationship between multiple preset size parameters of steel structure components and multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters is fitted, and the universal multiple regression model is optimized and analyzed according to the multivariate stepwise regression analysis method to obtain a hysteresis parameter model of steel structure components.

[0076] It should be noted that the general multiple regression model is a mathematical model for regression analysis, which contains multiple regression variables. Stepwise multiple regression analysis is a statistical regression method that can not only identify the key factors affecting the dependent variables, but also eliminate the correlation between multiple dependent variables.

[0077] The general multivariate regression model used in this embodiment is shown in formula (3-1), which fits the five dimensional characteristic parameters of the steel structure component with its hysteresis parameters.

[0078] (3-1) In formula (3-1), m To predict the hysteresis parameters of steel structure components, a 0. a 1. a 2. a 3. a 4. a 5 is the regression coefficient, 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 steel structure section along the weak axis, d is the section height of the steel structure section, 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.

[0079] Then, in the stepwise multiple regression analysis, the backward elimination strategy was used to improve the general multiple regression model by gradually eliminating the independent variables that had no significant effect on the dependent variable. The elimination criterion for the independent variable was that the significance level of its effect on the dependent variable was less than 5%. The goodness of fit of the general multiple regression model was determined using the coefficient of determination. R 2After stepwise multivariate regression analysis, some hysteresis parameter models in the hysteresis parameter model of steel structure components can be obtained, namely, the strengthening section rotation angle θ p , Softening section angle θ pc , Peak bending moment M c , basic strength degradation cumulative plastic deformation capacity Λ s , Softening stage strength degradation Cumulative plastic deformation capacity Λ c and unloading stiffness degradation cumulative plastic deformation capacity Λ k .

[0080] Furthermore, in this embodiment, the hysteresis parameter model of the steel structure member is obtained as shown in Formula (3-2) to Formula (3-11).

[0081] (3-2) (3-3) (3-4) (3-5) (3-6) θ u = 0.15rad (3-7) (3-8) (3-9) (3-10) (3-11) In formula (3-2) - formula (3-11), 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 structure 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 steel structure section along the weak axis, d is the section height of the steel structure section, is the flange thickness of the steel structure member, is the flange width of the steel structure member. Figure 3 As shown, Figure 3 It is a schematic diagram of the dimensions of a steel structure component provided in one embodiment of the present application.

[0082] It should be noted that, K 0. M y , M r , θ u The four parameters do not need to be fitted through multiple regression analysis to obtain their regression models. θ u Determines the limit rotation angle of the steel structure member, which is not affected by the loading system. θ u = 0.15rad, M r is the residual strength of the component. According to existing research, M r =0.4 M y ; K 0 and M y The loading method has little influence on the calculation, and the existing model under the earthquake load method, namely formula (1-8) and formula (1-9), can be used for calculation.

[0083] In one possible implementation, a refined finite element model for a steel structure component is constructed, including: The four-node quadrilateral finite membrane strain linear reduced integral S4R shell element is used as the body of the steel structure component; the mesh size is 25mm×25mm; the steel structure component is an H-section component; the material constitutive model of the steel structure component is a mixed hardening model; The top and bottom of the steel structure are constrained by fixing, and the overall defects and local defects of the steel structure are added to the body of the steel structure to obtain a refined finite element model; 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 cross-sectional width of the steel structure member.

[0084] It should be noted that in the process of constructing a refined finite element model in the finite element software ABAQUS, the finite element model of the H-section steel structure component is usually used to simulate the hysteresis performance of the steel structure component under wind load. Figure 4 As shown, Figure 4 A schematic diagram of a finite element model of an H-section steel structure member provided in one embodiment of the present application. Figure 4 In (4-a) of , the top and bottom surfaces of the steel structure member are constrained by fixed connection; and the overall defects and local defects of the steel structure member are considered in the model, such as Figure 4 (4-b) and Figure 4 As shown in (4-c) in . Figure 4 (4-b) in the figure shows the overall defect of the H-section steel structure member. Figure 4 (4-c) in the figure represents the local defect of the H-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, , 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 25 mm×25 mm, which is the optimal mesh size that takes both computational efficiency and computational accuracy into consideration.

[0085] Since the thickness of the web and flange of the H-section steel structure member is much smaller than the dimensions in the other two directions, in this embodiment, the refined finite element model of the steel structure member is simulated using a four-node quadrilateral finite membrane strain linear reduced integral S4R shell unit, which can effectively capture the overall and local buckling of the steel structure member. The material constitutive model of the steel structure member adopts a mixed hardening model (nonlinear isotropy and kinematic hardening), and the vonMises yield criterion is used to identify the yield and failure of the material, where the mixed hardening model is shown in formula (3-12).

[0086] (3-12) In formula (3-12), is the nonlinear kinematic hardening parameter, is the nonlinear isotropic hardening parameter, is the kinematic hardening modulus, is the accumulated plastic strain, kinematic hardening modulus With the accumulated plastic strain The rate of decrease, is the back stress, is the equivalent yield stress of the material under zero plastic strain, is the maximum change in the yield surface size, b is the rate of change of yield surface size with plastic strain.

[0087] In this embodiment, the material parameters are selected as follows: Young's modulus E = 200GPa, axial yield load of steel structure components F ye = 380MPa, kinematic hardening modulus C = 3378MPa, kinematic hardening modulus With the accumulated plastic strain The rate of decrease η = 20, Maximum change in yield surface size Q ∞ = 90MPa, the rate of change of yield surface size with plastic strain b = 12.

[0088] 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-section steel structure components were selected for verification, including hysteresis test data under different axial compression ratios and different loading protocols. The accuracy of the above refined finite element model was verified by comparing the moment-rotation curves of the steel structure components and the deformation when the components failed. The verification method of the accuracy of the refined finite element model is not specifically described here.

[0089] In a possible implementation, 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, including: Obtain a wind load loading method for applying 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 requirements of the quasi-static test on the steel structure components; 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 components and the cumulative probability values ​​at different levels; obtaining the wind load loading method of the steel structure components 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, wind load is applied to the refined finite element model and the hysteresis performance of the steel structure components is simulated to obtain the simulated hysteresis curve of the steel structure components under the wind load.

[0090] It should be noted that, since the hysteresis performance of steel structure components under wind load is different from that of steel structure components under earthquake load, a wind load loading method specifically for wind load needs to be specified first according to the characteristics of wind load. In this embodiment, three parameters, namely, total cycle, cycle mean and cycle amplitude, are used to characterize the performance requirements of steel structure components under wind load, thereby formulating a wind load loading system for steel structure components under wind load. Specifically, according to the demand for quasi-static test of steel structure components, it is necessary to analyze the response of the refined finite element model from the beginning of vibration to failure, decompose the time history of the displacement angle between structural layers by rain flow counting method, and statistically decompose the mean and amplitude of the cycle, thereby obtaining multiple cycle mean levels and multiple cycle amplitude levels. Among them, the quasi-static test refers to a static test in which multiple reciprocating cycles are applied to steel structure components, which is a process of repeatedly loading and unloading steel structure components to obtain information such as strength, stiffness, energy consumption, etc. of the components in reciprocating vibration, and then establish a hysteresis model of the steel structure components. Afterwards, from the perspective of probability distribution, the number of loadings at each cycle mean level and the number of loadings at each cycle amplitude level are determined from the joint probability distribution of the cycle mean and the cycle amplitude. Then, the cumulative probability values ​​at different levels are determined based on multiple cycle mean levels and multiple cycle amplitude levels; the cycle mean and cycle amplitude at each level are obtained based on 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, and then the wind load loading system of the steel structure component under wind load is obtained based on the cycle mean at each level, the cycle amplitude at each level, and the number of cyclic loadings at different levels. This wind load loading system is used for the aforementioned simulation of the hysteresis performance of the steel structure component under wind load.

[0091] It should be noted that in order to prove that the hysteresis parameter model of steel structure components proposed in this embodiment is better than the existing hysteresis parameter model of steel structure components under seismic load, a comparison is made with the hysteresis parameter empirical model proposed by Lignos, which is currently widely used. The comparison results are as follows: Figure 5 shown. Figure 5 1 is a schematic diagram of a comparison between hysteresis curve parameters of a steel structure component under wind load and hysteresis parameter model simulation results provided by an embodiment of the present application. Figure 5 In the figure, the horizontal axis represents the predicted values ​​of various hysteresis parameters obtained by substituting the dimensions of the steel structure components into different hysteresis parameter models. The orange dots represent the predicted values ​​of various hysteresis parameters obtained by simulating the existing hysteresis parameter model under seismic loads, and the blue dots represent the predicted values ​​of various hysteresis parameters obtained by simulating the hysteresis parameter model under wind loads. The vertical axis represents the actual values ​​of the hysteresis parameters of the steel structure components under wind loads. Figure 5The middle curve represents the hysteresis curve parameters of steel structure components. Among them, the expression of the hysteresis parameter empirical model proposed by Lignos can be expressed by formula (1-5)-formula (1-7), as well as the following formula (4-1), formula (4-2), and stiffness K e and yield moment M y The two parameter models are also compared with the hysteresis parameters of 1028 steel columns in the existing steel column database.

[0092] (4-1) (4-2) In formula (4-1) and formula (4-2), is the accumulated plastic deformation capacity of basic strength degradation, is the accumulated plastic deformation capacity of the softening section strength degradation, The accumulated plastic deformation capacity for unloading stiffness degradation is 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 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.

[0093] in, Figure 5 (5-a) is the hysteresis parameter stiffness K e Schematic diagram of the comparison of simulation results; Figure 5 (5-b) is the hysteresis parameter yield moment M y Schematic diagram of the comparison of simulation results; Figure 5 (5-c) is the hysteresis parameter peak moment Yield moment A schematic diagram showing the comparison of the simulation results of the ratio F; Figure 5 (5-d) is the hysteresis parameter strengthening section rotation angle Schematic diagram of the comparison of simulation results; Figure 5 (5-e) is the hysteresis parameter softening section rotation angle Schematic diagram of the comparison of simulation results; Figure 5 (5-f) is the hysteresis parameter basic strength degradation cumulative plastic deformation capacity Schematic diagram of the comparison of simulation results; Figure 5 The (5-g) in the figure is the accumulated plastic deformation capacity of the softening section strength degradation. Schematic diagram of the comparison of simulation results; Figure 5 (5-h) is the hysteresis parameter, unloading stiffness degradation, and accumulated plastic deformation capacity. A comparison diagram of the simulation results. Figure 5 It can be seen from (5-a)-(5-b) that for the stiffness K e and yield moment M y The two parameters can be predicted more accurately by using the existing hysteresis parameter model based on earthquake load. Figure 5 It can be seen from (5-c) to (5-h) that, for other hysteresis parameters of steel structure components, the prediction results of the existing hysteresis parameter model based on seismic load are very different from the actual values ​​of the hysteresis parameters of the steel structure components under wind load; while the hysteresis parameter model based on wind load proposed in this embodiment based on the hysteresis loading test of steel structure components under wind load loading system can more accurately predict the hysteresis parameters of steel structure components under wind load.

[0094] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0095] Corresponding to the method for constructing a hysteresis parameter model of a steel structure member under wind load in the above embodiment, Figure 6 A structural schematic diagram of a device for constructing a hysteresis parameter model of a steel structure member under wind load provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0096] Reference Figure 6 The device 2 for constructing the hysteresis parameter model of the steel structure member under the wind load of this embodiment includes: A model building module 21, used to build a refined finite element model for steel structure components; The first simulation module 22 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; The second simulation module 23 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 24 is 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; The model determination module 25 is used to obtain a hysteresis parameter model of a steel structure component through regression analysis based on multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters, 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.

[0097] It can be understood that, in this embodiment, the construction device 2 of the hysteresis parameter model of the steel structure component under the action of wind load, first, constructs a refined finite element model for the steel structure component through the model construction module 21; then, a monotonic load is applied to the refined finite element model through the first simulation module 22 and the monotonic loading performance of the steel structure component is simulated to obtain a simulated monotonic loading curve of the steel structure component under the action of the monotonic load; and the second simulation module 23 applies a wind load to the refined finite element model and simulates the hysteresis performance of the steel structure component to obtain a simulated monotonic loading curve of the steel structure component under the action of the wind load. The simulated hysteresis curve of the steel structure component; then, the simulated monotonic loading curve and the simulated hysteresis curve are respectively identified by the parameter identification module 24 to obtain the hysteresis parameters of the steel structure component; wherein the hysteresis parameters include multiple skeleton curve parameters and multiple cumulative plastic deformation capacity parameters; finally, the model determination module 25 determines the hysteresis parameter model of the steel structure component 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. The present application determines the hysteresis parameters of the steel structure component by performing parameter identification on the simulated monotonic loading curve and the simulated hysteresis curve obtained by simulating the refined finite element model, and obtains the hysteresis parameter model of the steel structure component that characterizes the relationship between the characteristic size and the hysteresis parameter of the steel structure component under the action of wind load. The hysteresis parameter model of the steel structure component can more accurately predict the hysteresis parameters of the steel structure component under the action of wind load, thereby being able to more accurately calculate the response performance of the steel structure component under the action of wind load.

[0098] It should be noted that the information interaction, execution process, etc. between the modules in the above-mentioned device 2 for constructing the hysteresis parameter model of the steel structure component under the action of wind load are based on the same concept as the method embodiment of the present application. Its specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0099] The present application also provides a terminal device, such as Figure 7 As shown, Figure 7 A schematic diagram of the structure of a terminal device provided in one embodiment of the present application. Figure 7The terminal device 3 of 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, the steps in the method for constructing a hysteresis parameter model of a steel structure member under wind load described above are implemented.

[0100] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0101] An embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0102] 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, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0103] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0104] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0105] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0106] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present 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 the steel structure component is obtained through regression analysis, wherein the hysteresis parameter model of the 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.

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: 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.

7. The method for constructing a hysteresis parameter model of a steel structure member under wind load according to claim 1, characterized in that: The construction of a refined finite element model for a steel structure member 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 cross-sectional width of the steel structure member.

8. 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.

9. 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 based on 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 of the steel structure component and the hysteresis parameter under the action of wind load.

10. 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 8 when executing the computer program.

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