Wind resistance design improvement method based on inelastic performance and target reliability

Abstract

The invention relates to a wind resistance design improvement method based on inelastic performance and target reliability, and the method comprises the steps: generating a multi-sample wind load time history according to wind load characteristic parameter information, and carrying out the calculation based on a single-degree-of-freedom system to obtain a strength reduction coefficient (RW) probability distribution function corresponding to different storm durations under the wind load effect; a wind-resistant strength reduction coefficient related to storm duration is introduced, and a wind-resistant bearing capacity limit state equation and a design expression are corrected; determining a representative value (RWk) of the RW based on a set target reliability (beta m), and establishing an RWk-mu-T relation curve convenient for engineering design by changing a ductility coefficient mu and a structure period T; performing wind resistance design according to the corrected design expression; the improved method can solve the problems that the inelastic performance of the structure is not considered in the existing wind-resistant design, and the wind-resistant design cannot be carried out according to the reliability expected by different owners.

Description

Technical Field

[0001] The present invention belongs to the field of wind-resistant analysis of building structures and wind-resistant resilience cities, and relates to a method for improving wind-resistant design based on inelastic performance and target reliability. In particular, it relates to a method for improving wind-resistant design of building structures (such as high-rise building structures, flat roof structures, etc.) whose wind-induced vibration response is dominated by a certain order vibration mode of the structure and can be simplified into an equivalent single-degree-of-freedom system. Background Art

[0002] Current standards for wind-resistant building structures primarily utilize linear elastic design methods, stipulating that structures must maintain elasticity under frequent strong winds with an average return period of 50 or 100 years. Load partial factors are set to ensure that the wind-resistant design meets the target reliability set by the standard. This design method assumes that structural components begin to enter elastic-plastic behavior as their ultimate bearing capacity and does not consider the inelastic properties of the structure.

[0003] Similar to earthquakes, wind loads are essentially occasional dynamic loads. Numerous studies have shown that building structures do not fail immediately after entering elastic-plastic behavior under strong wind loads. Instead, they exhibit ductile failure, with failure occurring only after the elastic-plastic deformation reaches a certain level. This process causes inelastic energy dissipation (also known as ductile energy dissipation), which reduces the required wind bearing capacity of the structure. Therefore, designing for wind resistance based on the initial elastic-plastic state as the ultimate bearing capacity limit may result in an overly conservative design. In structural wind resistance design, considering the beneficial effects of inelastic properties such as structural ductility and super strength on wind resistance can lead to more reasonable and economical engineering designs.

[0004] In addition, in recent years, strong winds have occurred frequently and have a wide impact range. Many owners hope to be able to carry out wind-resistant design according to their expected reliability and obtain housing buildings with higher wind-resistant reliability.

[0005] In order to solve the above problems, it is necessary to introduce a wind resistance strength reduction factor and propose a modified bearing capacity limit state for structural wind resistance design to take into account the beneficial effects of structural ductility and super strength on structural wind resistance. On this basis, by giving the value of the corresponding strength reduction factor, a wind resistance design method for building structures based on the owner's target reliability is established. Summary of the Invention

[0006] In view of this, in order to solve the problem that the existing wind-resistant design does not take the structural inelastic performance into consideration and the existing wind-resistant design cannot be designed according to the reliability expected by different owners, the present invention provides an improved wind-resistant design method based on inelastic performance and target reliability.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A wind resistance design improvement method based on inelastic performance and target reliability includes the following steps:

[0009] S1. Obtain wind resistance reduction factor R W Probability distribution function; according to the wind load characteristic parameter information, generate multiple sample wind load time history, and calculate the strength reduction factor (R) corresponding to different storm durations under wind load based on the single degree of freedom (SODF) system. W ) probability distribution function;

[0010] S2. Modify the ultimate state equation of wind resistance capacity; introduce the wind resistance reduction factor R related to the storm duration W , considering the beneficial effect of the inelastic performance of the structure on wind resistance, the wind resistance bearing capacity limit state equation and design expression are modified;

[0011] S3. Determine R based on target reliability W Representative value; based on the set target reliability (β m ) Determine R W Representative value (R Wk ), and by changing the ductility coefficient μ and the structural period T, an R Wk -μ-T relationship curve; perform wind resistance design according to the revised design expression.

[0012] Further, step S1 is specifically as follows:

[0013] S11. Generate multiple sample wind load time histories based on wind load parameter information;

[0014] S12. Establish the motion equation of the single degree of freedom system (SODF) under wind load, define the ductility coefficient μ and the wind strength reduction factor (R W ), specify the ductility coefficient μ and the structural period T, and calculate the R under wind load W ;

[0015] (1)

[0016] (2)

[0017] (3)

[0018] Where m and c are the mass and damping of the system respectively, For system resilience, For wind load time history, the classic Davenport spectrum can be used to generate multiple wind speed time histories, thereby obtaining multiple schedule; are the displacement, velocity and speed of the system respectively; under the same wind load, F e The maximum elastic force for a single degree of freedom system to maintain elasticity, F y For a single degree of freedom system, in order to achieve the yield strength of a specified ductility coefficient, x max is the maximum elastic-plastic displacement of the single-degree-of-freedom system under wind load, x y Yield displacement of a single degree of freedom system;

[0019] Based on formulas (1)-(3), considering the wind load parameters and structural parameter information, the wind strength reduction factor R under the specified ductility factor μ is calculated. W ;

[0020] S13. Establish R related to storm duration W Probability distribution function; after performing multi-sample wind load analysis on wind load, R W Probability distribution formula .

[0021] Furthermore, the wind load parameter information in step S11 includes the turbulence intensity I u , duration t, average wind speed V, specify the ductility coefficient μ and structural period T in step S12, and calculate the wind strength reduction factor R W The calculation process includes: first, based on the structural parameter information, the multi-degree-of-freedom structure is equivalent to a single-degree-of-freedom (SODF) system, and the structural period T is determined; then, based on equations (1)-(3), the wind load time history is generated, and the wind-induced response of the SODF system is calculated by the dynamic time domain method to obtain its ductility coefficient μ and strength reduction factor R W , and continuously adjust the random coefficient a generated by the model for iterative calculation, so that the calculated ductility coefficient μ is consistent with the specified ductility coefficient μ i The error is less than the limit of 0.05. When the error is less than the limit, the iterative calculation is stopped to obtain the wind strength reduction factor R corresponding to the specified ductility coefficient μ. W .

[0022] Furthermore, in step S13, the R related to the storm duration is established. W Probability distribution function; using the iterative calculation method in step S12, apply multiple wind load time history samples generated in step S11 to the single degree of freedom system to calculate multiple R W Data samples, and then perform fitting analysis according to different probability distribution functions to find the goodness of fit R 2 The highest, that is, the most consistent with R W Probability distribution formula for data samples , probability distribution functions include Gumbel distribution, Lognormal distribution, Gamma distribution, Weibull distribution, and Normal distribution. They are often used in statistics and engineering to simulate different types of data. 2 The closer the value is to 1, the better the fitting effect is.

[0023] Further, step S2 is specifically as follows: introducing R W Modify the ultimate limit state of the structural wind resistance design bearing capacity and the corresponding design ultimate limit state design expression:

[0024] (4)

[0025] (5)

[0026] Where: R, S G 、S W Represent structural resistance, permanent load effect, and wind load effect respectively; R k 、S Gk 、S Wk They represent the standard value of structural resistance, the standard value of permanent load effect, and the standard value of wind load effect respectively; They are resistance partial factor, permanent load partial factor, and wind load partial factor respectively.

[0027] Further, step S3 is specifically as follows:

[0028] S31. Based on step S1, set the target wind resistance reliability (β m ), use the limit state equation modified by equations (4) and (5) in step S2 to back-calculate R W The representative value R Wk , used for wind-resistant design of structures;

[0029] S32, change the ductility coefficient μ and the structural period T, and establish R Wk -μ-T relationship curve;

[0030] Changing the ductility coefficient μ and the natural vibration period T of the structure, repeating steps S12, S13, S2, and S31 can establish R Wk -μ-T relationship curve; R Wk The size of R is affected by wind load parameters and structural parameters, among which the duration of wind load t and the stiffness ratio of the structure after yielding α have an impact on R Wk The size of the effect is most obvious;

[0031] S33. Verify wind load-bearing capacity according to the revised design expression;

[0032] (6)

[0033] Among them, R W Representative value (R Wk ), an improved design method for wind resistance of building structures based on target reliability is established and used in the wind resistance design of structures.

[0034] Furthermore, in step S31, the target reliability β m , can be determined based on the target reliability given by the existing specifications. This reliability is the minimum limit of the target reliability. If the owner proposes a higher wind resistance reliability requirement, it can also be determined based on the owner's expected reliability. On this basis, determine R according to the method in step S31. W The representative value R Wk .

[0035] Furthermore, by changing the values of other parameters (damping ratio, turbulence intensity, stiffness ratio, duration, etc.) in step S32, it is possible to establish R under different parameter conditions within the common parameter range of engineering design. Wk -μ-T relationship curve, which is convenient for quickly determining R in engineering design W The representative value of .

[0036] Furthermore, in step S32, the structural information of wind resistance verification is carried out as needed, the natural vibration period T of the structure is obtained, and the ductility coefficient μ of the structure is determined by consulting the literature database or the specification database; on this basis, the ductility coefficient μ of the structure is determined by using R Wk -μ-T relationship curve to quickly determine R Wk value.

[0037] This improved wind-resistant design method based on inelastic performance and target reliability is suitable for building structures whose wind-induced vibration response is dominated by a certain order vibration mode and can be simplified into an equivalent single-degree-of-freedom system, such as high-rise building structures and flat roof structures.

[0038] The beneficial effects of the present invention are:

[0039] 1. The wind-resistant design improvement method based on inelastic performance and target reliability disclosed in the present invention introduces R related to storm duration. W The wind resistance limit state of the structure is corrected. The beneficial effect of the structure's inelastic performance on the structure's wind resistance and the storm duration effect are taken into account in the wind resistance design, which improves the rationality and economy of the wind resistance design of the building structure and makes the designed bearing capacity limit state closer to the actual wind resistance failure state of the structure.

[0040] 2. The improved wind-resistant design method based on inelastic performance and target reliability disclosed in the present invention first generates multiple sample wind load time histories based on wind load characteristic parameter information (including duration, turbulence intensity, etc.), and calculates the strength reduction factor (R) corresponding to different storm durations under wind load based on a single degree of freedom (SODF) system. W ) probability distribution function; then based on the set target reliability (β m ) Determine R W Representative value (R Wk ), and by changing the ductility coefficient μ and the structural period T and other parameters, an R Wk -μ-T relationship curve; based on R Wk The modified limit state equations can be used to design wind-resistant structures based on the μ-μ-T relationship curve. This allows for consideration of the inelastic properties of the structure and allows for wind-resistant design based on the client's target reliability. This approach is of great scientific and engineering significance. The entire process is simple, efficient, and convenient for engineering designers.

[0041] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings, in which:

[0043] Figure 1 This is a basic principle diagram of the wind-resistant design improvement method based on inelastic performance and target reliability of the present invention;

[0044] Figure 2 Schematic diagram of a single degree of freedom system under wind load in step S1 of the present invention;

[0045] Figure 3 Solve R for the specified μ in step S1 of the present invention W Flowchart of

[0046] Figure 4 R in step S1 of the present invention W Probability distribution fitting function graph of ;

[0047] Figure 5 This is a flow chart of the method for improving the structural wind resistance design in step S3 of the present invention. DETAILED DESCRIPTION

[0048] The following describes the embodiments of the present invention through specific examples. Those skilled in the art will readily understand the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention.

[0049] The key and core issue of improving wind resistance design methods lies in how to determine the wind resistance reduction factor R W Since there are obvious differences between wind load and earthquake action, such as wind load has average component and pulsating component while earthquake load has only pulsating component, and wind load lasts much longer than earthquake action, the strength reduction coefficient of the structure under wind load and earthquake action is obviously different, and the strength reduction coefficient in the field of earthquake engineering cannot be directly used as a reference.

[0050] The most direct and accurate way to determine R W The best method is to build a finite element model of the structure and then calculate it through the traditional dynamic time history analysis method (denoted as THA). However, wind loads are uncertain. If multiple samples of wind loads are used for dynamic time history analysis, the calculation efficiency is too low and it is difficult to use in engineering design.

[0051] For multi-degree-of-freedom systems (such as high-rise structures, flat roof structures, etc.) whose wind-induced vibration response is dominated by a certain order mode, they can be converted into equivalent single-degree-of-freedom systems by mode decomposition. Therefore, the present invention proposes a method for quickly determining R W The method is used to take the structural components subjected to permanent load and wind load as an example. A single degree of freedom system is used to perform multi-sample load time history analysis to obtain the R under the specified ductility coefficient. W probability distribution, and based on a given target reliability β m Determine R W The representative value R Wk By changing the period T, R based on the target reliability can be established. Wk -μ-T relationship, which facilitates rapid determination of R in engineering design Wk , the specific process is as follows:

[0052] like Figure 1 The wind resistance design improvement method based on inelastic performance and target reliability shown in FIG1 includes the following steps:

[0053] S1. Obtain wind resistance reduction factor R W Probability distribution function; according to the wind load characteristic parameter information, generate multiple sample wind load time history, and calculate the strength reduction factor (R) corresponding to different storm durations under wind load based on the single degree of freedom (SODF) system. W ) probability distribution function;

[0054] Specifically, S11, based on wind load parameter information (including turbulence intensity I u , duration t, average wind speed V, etc.), generate multi-sample wind load time history;

[0055] S12. Establish wind load Figure 2 The equation of motion of the single degree of freedom (SODF) system is shown, and the ductility coefficient μ and the wind strength reduction factor (R W ), specify the ductility coefficient μ and the structural period T, and calculate the R under wind load W ;

[0056] (1)

[0057] (2)

[0058] (3)

[0059] Where m and c are the mass and damping of the system respectively, For system resilience, For wind load time history, the classic Davenport spectrum can be used to generate multiple wind speed time histories, thereby obtaining multiple schedule; are the displacement, velocity and speed of the system respectively; under the same wind load, F e The maximum elastic force for a single degree of freedom system to maintain elasticity, F y For a single degree of freedom system, in order to achieve the yield strength of a specified ductility coefficient, x max is the maximum elastic-plastic displacement of the single-degree-of-freedom system under wind load, x y Yield displacement of a single degree of freedom system.

[0060] according to Figure 3 The calculation process shown in the figure first converts the multi-degree-of-freedom structure into a single-degree-of-freedom (SODF) system based on the structural parameter information and determines the structural period T. Then, based on equations (1)-(3), the wind load time history is generated and the wind-induced response of the SODF system is calculated by the dynamic time domain method to obtain its ductility coefficient μ and strength reduction factor R. W , and continuously adjust the random coefficient a generated by the model to adjust the yield force F y Perform iterative calculations to ensure that the calculated ductility coefficient μ is consistent with the specified ductility coefficient μ i The error is less than a certain limit (the preferred limit is 0.05). When the error is less than the limit requirement, the iterative calculation is stopped to obtain the wind strength reduction factor R corresponding to the specified ductility coefficient μ. W .

[0061] S13. Establish R related to storm duration W Probability distribution function; using the iterative calculation method in step S12, apply multiple wind load time history samples generated in step S11 to the single degree of freedom system to calculate multiple R W Data samples, and then perform fitting analysis according to different probability distribution functions to find the goodness of fit R 2 The highest, that is, the most consistent with R W Probability distribution formula for data samples ,like Figure 4 shown.

[0062] Common probability distribution functions include Gumbel distribution, Lognormal distribution, Gamma distribution, Weibull distribution, and Normal distribution. They are often used in statistics and engineering to simulate different types of data. 2 The closer the value is to 1, the better the fitting effect is.

[0063] where R W The probability distribution of is affected by the wind load parameters, especially the duration parameter t.

[0064] S2. Modify the ultimate state equation of wind resistance capacity; introduce the wind resistance reduction factor R related to the storm duration W , the wind resistance bearing capacity limit state equation and design expression are modified;

[0065] Specifically, the introduction of R W Modify the ultimate limit state of the structural wind resistance design bearing capacity and the corresponding design ultimate limit state design expression:

[0066] (4)

[0067] (5)

[0068] Where: R, S G 、S W Represent structural resistance, permanent load effect, and wind load effect respectively; R k 、S Gk 、S Wk They represent the standard value of structural resistance, the standard value of permanent load effect, and the standard value of wind load effect respectively; They are resistance partial factor, permanent load partial factor, and wind load partial factor respectively.

[0069] S3. Wind resistance design based on target reliability; based on the set target reliability (β m ) Determine R W Representative value (R Wk), and by changing the ductility coefficient μ and the structural period T, an R Wk -μ-T relationship curve; perform wind resistance design according to the revised design expression;

[0070] Specifically, S31, based on step S1, sets the target wind resistance reliability (β m ), use the limit state equation modified by equations (4) and (5) in step S2 to back-calculate R W The representative value R Wk , used for wind-resistant design of structures.

[0071] Target reliability β m , can be determined based on the target reliability given by the existing specifications. This reliability is the minimum limit of the target reliability. If the owner proposes a higher wind resistance reliability requirement, it can also be determined based on the owner's expected reliability. On this basis, determine R according to the method of step S31 W The representative value R Wk .

[0072] S32, change the ductility coefficient μ and the structural period T, repeat steps S12, S13, S2, S31 to establish an R that is convenient for engineering design. Wk -μ-T relationship curve;

[0073] Since R Wk The size of R is affected by wind load parameters and structural parameters, among which the duration of wind load t and structural stiffness ratio α have an impact on R Wk According to the above method, by changing the values of other parameters (damping ratio, turbulence intensity, stiffness ratio, duration, etc.), we can establish R under different parameter conditions within the common parameter range of engineering design. Wk -μ-T relationship curve, which is convenient for quickly determining R in engineering design W The representative value of .

[0074] According to the structural information of wind resistance verification required, the natural vibration period T of the structure is obtained and the ductility coefficient μ of the structure is determined by consulting the literature database or the specification database; on this basis, the R Wk -μ-T relationship curve to quickly determine R Wk value.

[0075] S33. Verify wind load-bearing capacity according to the revised design expression;

[0076] (6)

[0077] Among them, R W Representative value (R Wk) can be determined according to Figure 5 The process shown establishes an improved method for wind-resistant design of building structures based on target reliability, which is used in wind-resistant design of structures.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should all be included in the scope of the claims of the present invention.

Claims

1. A wind resistance design improvement method based on inelastic performance and target reliability, characterized in that: The following steps are involved: S1. Obtain wind resistance reduction factor R W Probability distribution function; according to the wind load characteristic parameter information, generate multiple sample wind load time history, and calculate the strength reduction factor (R) corresponding to different storm durations under wind load based on the single degree of freedom (SODF) system. W ) probability distribution function; S2. Modify the ultimate state equation of wind resistance capacity; introduce the wind resistance reduction factor R related to the storm duration W , considering the beneficial effect of the inelastic performance of the structure on wind resistance, the wind resistance bearing capacity limit state equation and design expression are modified; S3. Determine R based on target reliability W Representative value; Based on the set target reliability (β m ) Determine R W Representative value (R Wk ), and by changing the ductility coefficient μ and the structural period T, an R Wk -μ-T relationship curve; Carry out wind resistance design according to the revised design expression.

2. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 1, characterized in that: Step S1 is specifically as follows: S11. Generate multiple sample wind load time histories based on wind load parameter information; S12. Establish the motion equation of the single degree of freedom system (SODF) under wind load, define the ductility coefficient μ and the wind strength reduction factor (R W ), specify the ductility coefficient μ and the structural period T, and calculate the R under wind load W ; （1） （2） （3） Where m and c are the mass and damping of the system respectively, For system resilience, For wind load time history, the classic Davenport spectrum can be used to generate multiple wind speed time histories, thereby obtaining multiple schedule; are the displacement, velocity and speed of the system respectively; under the same wind load, F e The maximum elastic force for a single degree of freedom system to maintain elasticity, F y For a single degree of freedom system, in order to achieve the yield strength of a specified ductility coefficient, x max is the maximum elastic-plastic displacement of the single-degree-of-freedom system under wind load, x y Yield displacement of a single degree of freedom system; Based on formulas (1)-(3), considering the wind load parameters and structural parameter information, the wind strength reduction factor R under the specified ductility factor μ is calculated. W ; S13. Establish R related to storm duration W Probability distribution function; after multi-sample wind load analysis of wind load, R is obtained by fitting W Probability distribution formula .

3. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 2, characterized in that: In step S11, the wind load parameter information includes the turbulence intensity I u , duration t, average wind speed V; in step S12, specify the ductility coefficient μ and the structural period T to calculate the wind strength reduction factor R W The calculation process includes: first, based on the structural parameter information, the multi-degree-of-freedom structure is equivalent to a single-degree-of-freedom (SODF) system, and the structural period T is determined; then, based on equations (1)-(3), the wind load time history is generated, and the wind-induced response of the SODF system is calculated by the dynamic time domain method to obtain its ductility coefficient μ and strength reduction factor R W , and continuously adjust the random coefficient a generated by the model to adjust the yield force F y Perform iterative calculations to ensure that the calculated ductility coefficient μ is consistent with the specified ductility coefficient μ i The error is less than the limit of 0.

05. When the error is less than the limit, the iterative calculation is stopped to obtain the wind strength reduction factor R corresponding to the specified ductility coefficient μ. W .

4. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 3, characterized in that: In step S13, the R W Probability distribution function; using the iterative calculation method in step S12, apply multiple wind load time history samples generated in step S11 to the single degree of freedom system to calculate multiple R W Data samples, and then perform fitting analysis according to different probability distribution functions to find the goodness of fit R 2 The highest, that is, the most consistent with R W Probability distribution formula for data samples , probability distribution functions include Gumbel distribution, Lognormal distribution, Gamma distribution, Weibull distribution, and Normal distribution. They are often used in statistics and engineering to simulate different types of data. 2 The closer the value is to 1, the better the fitting effect is.

5. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 2, characterized in that: Step S2 is specifically as follows: introducing R W Modify the ultimate limit state of the structural wind resistance design bearing capacity and the corresponding design ultimate limit state design expression: （4） （5） Where: R, S G 、S W Represent structural resistance, permanent load effect, and wind load effect respectively; R k 、S Gk 、S Wk They represent the standard value of structural resistance, the standard value of permanent load effect, and the standard value of wind load effect respectively; They are resistance partial factor, permanent load partial factor, and wind load partial factor respectively.

6. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 5, characterized in that: Step S3 is specifically as follows: S31. Based on step S1, set the target wind resistance reliability (β m ), use the limit state equation modified by equations (4) and (5) in step S2 to back-calculate R W The representative value R Wk , used for wind-resistant design of structures; S32, change the ductility coefficient μ and the structural period T, and establish R for easy use in engineering design Wk -μ-T relationship curve; Change the ductility coefficient μ and the structural period T, and repeat steps S12, S13, S2, and S31 to establish R Wk -μ-T relationship curve; R Wk The size of R is affected by wind load parameters and structural parameters, among which the duration of wind load t and the stiffness ratio of the structure after yielding α have an impact on R Wk The size of the effect is most obvious; S33. Verify wind load-bearing capacity according to the revised design expression; （6） Among them, R W Representative value (R Wk ), an improved wind-resistant design method for building structures based on target reliability is established and used in the wind-resistant design of structures.

7. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 6, characterized in that: Target reliability β in step S31 m , determined according to the target reliability given by the existing specifications. This reliability is the minimum limit of the target reliability. If the owner proposes a higher wind resistance reliability requirement, it is determined according to the owner's expected reliability. On this basis, R is determined according to the method of step S31. W The representative value R Wk .

8. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 6, characterized in that: In step S32, the damping ratio, turbulence intensity, stiffness ratio and duration parameter values are changed to establish R Wk -μ-T relationship curve, which is convenient for quickly determining R in engineering design W The representative value of .

9. The wind resistance design improvement method based on inelastic performance and target reliability as claimed in claim 6, characterized in that: In step S32, the structural information of wind resistance calculation is carried out as needed, the natural vibration period T of the structure is obtained, and the ductility coefficient μ of the structure is determined by consulting the literature database or the specification database; on this basis, the ductility coefficient μ of the structure is determined by using R Wk -μ-T relationship curve to quickly determine R Wk value.

10. Application of the wind resistance design improvement method based on inelastic performance and target reliability according to any one of claims 1 to 9, characterized in that: The wind-resistant design improvement method based on inelastic performance and target reliability is applicable to the wind-resistant design improvement of a building structure of an equivalent single-degree-of-freedom system, and the building structure is a high-rise building structure or a flat roof structure.

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