An improved wind resistance design method based on inelastic performance and target reliability

Abstract

This invention relates to an improved wind-resistant design method based on inelastic performance and target reliability. It generates multi-sample wind load time histories based on wind load characteristic parameters and calculates the intensity reduction factor (Ri) corresponding to different storm durations under wind load based on a single-degree-of-freedom system. W The probability distribution function is used; the wind resistance intensity reduction coefficient related to storm duration is introduced to modify the ultimate limit state equation and design expression of wind resistance capacity; based on the set target reliability (β) m Determine R W The representative value (R) Wk ), and by changing the ductility coefficient μ and the structural period T, an R model that is easy to use in engineering design is established. Wk -μ-T relationship curve; wind resistance design according to the modified design expression; the proposed improvement method can solve the problems that the existing wind resistance design does not consider the inelastic performance of the structure and cannot be carried out according to the reliability expected by different owners.

Description

Technical Field

[0001] This invention belongs to the field of wind resistance analysis and wind toughness of building structures in urban areas. It relates to a wind resistance design improvement method based on inelastic performance and target reliability. In particular, it relates to a wind resistance design improvement method applicable to building structures (such as high-rise building structures, flat roof structures, etc.) whose wind vibration response is dominated by a certain mode of vibration and can be simplified to an equivalent single-degree-of-freedom system. Background Technology

[0002] Current building structural wind resistance design standards primarily employ a linear elastic design method. This method stipulates that under frequent strong winds with a 50- or 100-year average return period, the structure must maintain elasticity, and load partial factors are used to ensure that the wind resistance design meets the target reliability set by the standards. This design method uses the entry of structural members into elastoplastic behavior as their ultimate bearing capacity for wind resistance design, without considering the inelastic properties of the structure.

[0003] Similar to earthquakes, wind loads are essentially accidental dynamic loads. Numerous studies have shown that building structures do not immediately fail after entering an elastoplastic state under strong wind loads; instead, they exhibit ductile failure, with failure occurring only after elastoplastic deformation has developed to a certain extent. This process induces inelastic energy dissipation (also known as ductile energy dissipation), leading to a reduction in the required wind resistance capacity. Therefore, using the onset of the structure entering an elastoplastic state as its ultimate limit state for wind resistance design may result in an overly conservative design. In structural wind resistance design, considering the beneficial effects of structural ductility and super-strength on wind resistance can lead to a more rational and economical engineering design.

[0004] In addition, strong winds have occurred frequently and affected a wide area in recent years. Many homeowners hope to have their buildings designed to withstand wind with the reliability they expect, so as to obtain buildings with higher wind resistance reliability.

[0005] To address the aforementioned issues, it is necessary to introduce a wind resistance strength reduction factor and propose a modified ultimate limit state for structural wind resistance design. This would take into account the beneficial effects of structural ductility and super-strength on structural wind resistance. Furthermore, by providing the corresponding strength reduction factor values, a wind resistance design method for building structures based on the owner's target reliability can be established. Summary of the Invention

[0006] In view of this, in order to solve the problems that existing wind-resistant designs do not consider structural inelastic performance and 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] To achieve the above objectives, the present invention provides the following technical solution:

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

[0009] S1, Obtain the wind resistance strength reduction factor R W Probability distribution function; based on wind load characteristic parameter information, generate multi-sample wind load time histories, and calculate the intensity 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 limit state equation for wind resistance capacity; introduce a wind resistance intensity reduction factor R related to storm duration. W Considering the beneficial effect of the structure's inelastic properties on wind resistance, the ultimate limit state equation and design expression for wind resistance capacity are modified.

[0011] S3. Determine R based on target reliability. W Representative value; based on the set target reliability (β) m Determine R W The representative value (R) Wk ), and by changing the ductility coefficient μ and the structural period T, an R model that is easy to use in engineering design is established. Wk -μ-T relationship curve; wind resistance design is carried out according to the modified design expression.

[0012] Furthermore, step S1 specifically includes:

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

[0014] S12. Establish the equations of motion for a single-degree-of-freedom (SODF) system under wind load, and define the ductility coefficient μ and the wind resistance strength reduction factor (R). W By specifying the ductility coefficient μ and the structural period T, the R under wind load is calculated. W ;

[0015] (1)

[0016] (2)

[0017] (3)

[0018] In the formula, m and c are the mass and damping of the system, respectively. For system resilience, To obtain the wind load time history, multiple wind speed time histories can be generated using the classic Davenport spectrum, thus yielding multiple... Timeline; These represent the system's displacement, velocity, and speed, respectively; under the same wind load, F e The maximum elastic force for maintaining the elasticity of a single-degree-of-freedom system is F. y For a single-degree-of-freedom system to achieve a yield strength with a specified ductility coefficient, x max x represents the maximum elastoplastic displacement of a single-degree-of-freedom system under wind load. y Yield displacement of a single-degree-of-freedom system;

[0019] Based on equations (1)-(3), and considering wind load parameters and structural parameter information, the wind resistance strength reduction factor R under a specified ductility coefficient 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 loads, R can be fitted to obtain R. W Probability distribution formula .

[0021] Furthermore, the wind load parameter information in step S11 includes turbulence intensity I. u Given the duration t, average wind speed V, and the ductility coefficient μ and structural period T specified in step S12, calculate the wind resistance 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-induced response of the SODF system is calculated using the generated wind load time history through the dynamic time domain method, and its ductility coefficient μ and strength reduction coefficient R are obtained. W The model continuously adjusts the random coefficients 'a' generated by iterative calculations to ensure that the calculated ductility coefficient μ is consistent with the specified ductility coefficient μ. i If the error is less than the limit of 0.05, the iterative calculation stops when the error is less than the limit requirement, thus obtaining the wind resistance strength reduction factor R corresponding to the specified ductility coefficient μ. W .

[0022] Furthermore, in step S13, an R related to 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, and calculate multiple R values. W The data samples are then used to perform fitting analysis according to different probability distribution functions to find the goodness of fit R. 2 The highest, that is, the one that best fits R W Probability distribution formula of data samples Probability distribution functions include the Gumbel distribution, Lognormal distribution, Gamma distribution, Weibull distribution, and Normal distribution. These are frequently used in statistics and engineering to model different types of data, and the R² value for fitting data is... 2 The closer the value is to 1, the better the fit.

[0023] Furthermore, step S2 specifically involves: introducing R W The ultimate limit state and corresponding design limit state expression for the wind resistance design capacity of the structure are revised as follows:

[0024] (4)

[0025] (5)

[0026] In the formula: R, S G S W Represents structural resistance, permanent load effect, and wind load effect, respectively; R k S Gk S Wk These represent the standard values ​​of structural resistance, permanent load effects, and wind load effects, respectively. These are the partial factors for resistance, permanent load, and wind load, respectively.

[0027] Furthermore, step S3 specifically includes:

[0028] S31. Based on step S1, set the target wind resistance reliability (β) according to the specifications or owner's requirements. m R is determined by back-calculation using the limit state equations corrected by equations (4) and (5) in step S2. W The representative value R Wk Used for wind-resistant design of structures;

[0029] S32. By changing the ductility coefficient μ and the structural period T, an R-value that is easy to use in engineering design is established. Wk -μ-T relationship curve;

[0030] By changing the ductility coefficient μ and the natural vibration period T of the structure, and repeating steps S12, S13, S2, and S31, R can be established. Wk -μ-T relationship curve; R Wk The magnitude of R is affected by wind load parameters and structural parameters, among which the duration t of the wind load and the post-yield stiffness ratio α of the structure have a significant impact on R. Wk The size has the most significant impact;

[0031] S33. Verify the wind resistance capacity according to the revised design expression;

[0032] (6)

[0033] R is clearly defined W Representative value (R) Wk After developing a rapid determination method, a wind resistance improvement design method for building structures based on target reliability is established for use in the wind resistance design of structures.

[0034] Furthermore, in step S31, the target reliability β m The reliability can be determined based on the target reliability given in existing specifications, which 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, R is determined 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, an R-value can be established that covers the range of common parameters in engineering design and different parameter conditions. Wk -μ-T relationship curve, which facilitates rapid determination of R in engineering design. W The representative value.

[0036] Furthermore, in step S32, the structural information required for wind resistance verification is used to obtain the natural vibration period T of the structure. The ductility coefficient μ of the structure is determined by consulting literature databases or standard databases. Based on this, R... Wk Rapid determination of R from μ-T relationship curve Wk value.

[0037] This wind-resistant design improvement method based on inelastic performance and target reliability is applicable to building structures whose wind vibration response is dominated by a certain mode of vibration, 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 this invention are as follows:

[0039] 1. The wind-resistant design improvement method based on inelastic performance and target reliability disclosed in this invention introduces R, which is related to storm duration. W The modification of the ultimate limit state of the structure's wind resistance takes into account the beneficial effect of the structure's inelastic properties on wind resistance and the duration effect of storms in the wind-resistant design, thereby improving the rationality and economy of the wind-resistant design of building structures and making the designed ultimate limit state of bearing capacity closer to the actual wind-resistant failure state of the structure.

[0040] 2. The wind-resistant design improvement method based on inelastic performance and target reliability disclosed in this invention first generates multi-sample wind load time histories based on wind load characteristic parameters (including duration, turbulence intensity, etc.), and calculates the intensity 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 The representative value (R) Wk By changing the ductility coefficient μ, the structural period T, and other parameters, an R model that is easy to use in engineering design is established. Wk -μ-T relationship curve; based on R Wk The μ-T relationship curve, used in structural wind resistance design according to the modified limit state equation, allows for consideration of the structure's inelastic properties and wind resistance design based on the client's target reliability, which has significant scientific research and engineering implications. The entire process is simple, efficient, and convenient for engineering designers.

[0041] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0042] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

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

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

[0045] Figure 3 In step S1 of this invention, μ is specified to solve R. W Flowchart;

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

[0047] Figure 5 This is a flowchart of the structural wind resistance design improvement method in step S3 of the present invention. Detailed Implementation

[0048] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0049] The key and core issue in improving wind-resistant design methods lies in how to determine the wind resistance reduction factor R. W The magnitude of the strength reduction factor is significant. Because wind loads and seismic loads differ significantly—for example, wind loads have both average and fluctuating components while seismic loads only have fluctuating components, and the duration of wind loads is much longer than that of seismic loads—the strength reduction factors for structures under wind and seismic loads differ considerably, and the magnitude of the strength reduction factor in earthquake engineering cannot be directly applied.

[0050] The most direct and accurate way to determine R W The method of size is to establish a finite element model of the structure and then calculate it using the traditional dynamic time history analysis method (THA). However, wind loads have uncertainties. 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 structural systems (such as high-rise structures and flat-roof structures) whose wind-induced vibration response is dominated by a certain mode shape, they can be converted into equivalent single-degree-of-freedom systems using modal decomposition. Therefore, this invention proposes a method for rapidly determining R... W The method, taking structural members subjected to permanent loads and wind loads as an example, utilizes a single-degree-of-freedom system to perform multi-sample load time history analysis, obtaining R under a 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, an R-value based on the target reliability can be established. Wk The -μ-T relationship facilitates the rapid determination of R in engineering design. Wk The specific process is as follows:

[0052] like Figure 1 The wind-resistant design improvement method shown includes the following steps:

[0053] S1, Obtain the wind resistance strength reduction factor R W Probability distribution function; based on wind load characteristic parameter information, generate multi-sample wind load time histories, and calculate the intensity 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 (e.g., duration t, average wind speed V, etc.) to generate multi-sample wind load time histories;

[0055] S12, Establishing the wind load action Figure 2 The equations of motion for the single-degree-of-freedom (SODF) system are shown, defining the ductility coefficient μ and the wind resistance reduction factor (R). W By specifying the ductility coefficient μ and the structural period T, the R under wind load is calculated. W ;

[0056] (1)

[0057] (2)

[0058] (3)

[0059] In the formula, m and c are the mass and damping of the system, respectively. For system resilience, To obtain the wind load time history, multiple wind speed time histories can be generated using the classic Davenport spectrum, thus yielding multiple... Timeline; These represent the system's displacement, velocity, and speed, respectively; under the same wind load, F e The maximum elastic force for maintaining the elasticity of a single-degree-of-freedom system is F. y For a single-degree-of-freedom system to achieve a yield strength with a specified ductility coefficient, x max x represents the maximum elastoplastic displacement of a single-degree-of-freedom system under wind load. y Yield displacement of a single-degree-of-freedom system.

[0060] according to Figure 3 The calculation process shown first involves converting a multi-degree-of-freedom structure into a single-degree-of-freedom (SODF) system based on structural parameter information and determining the structural period T. Then, based on equations (1)-(3), the wind-induced response of the SODF system is calculated using the generated wind load time history through a dynamic time-domain method, yielding its ductility coefficient μ and strength reduction coefficient R. W And continuously adjust the random coefficients 'a' generated by the model to adjust the yield force F. y Perform iterative calculations to make the calculated ductility coefficient μ equal to the specified ductility coefficient μ. i If the error is less than a certain limit (preferred limit is 0.05), the iterative calculation stops when the error is less than the limit requirement, thus obtaining the wind resistance 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, and calculate multiple R values. W The data samples are then used to perform fitting analysis according to different probability distribution functions to find the goodness of fit R. 2 The highest, that is, the one that best fits R W Probability distribution formula of data samples ,like Figure 4 As shown.

[0062] Common probability distribution functions include the Gumbel distribution, Lognormal distribution, Gamma distribution, Weibull distribution, and Normal distribution. These are frequently used in statistics and engineering to model different types of data and to fit the R-squared values ​​of the data. 2 The closer the value is to 1, the better the fit.

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

[0064] S2. Modify the ultimate limit state equation for wind resistance capacity; introduce a wind resistance intensity reduction factor R related to storm duration. W The ultimate state equation and design expression for wind resistance bearing capacity are revised.

[0065] Specifically, we introduce R W The ultimate limit state and corresponding design limit state expression for the wind resistance design capacity of the structure are revised as follows:

[0066] (4)

[0067] (5)

[0068] In the formula: R, S G S W Represents structural resistance, permanent load effect, and wind load effect, respectively; R k S Gk S Wk These represent the standard values ​​of structural resistance, permanent load effects, and wind load effects, respectively. These are the partial factors for resistance, permanent load, and wind load, respectively.

[0069] S3. Wind resistance design based on target reliability; based on the set target reliability (β) m Determine R W The representative value (R) Wk), and by changing the ductility coefficient μ and the structural period T, an R model that is easy to use in engineering design is established. Wk -μ-T relationship curve; wind resistance design is performed according to the revised design expression;

[0070] Specifically, S31, based on step S1, set the target wind resistance reliability (β) according to specifications or owner requirements. m R is determined by back-calculation using the limit state equations corrected by equations (4) and (5) in step S2. W The representative value R Wk Used for wind-resistant design of structures.

[0071] Target reliability β m The reliability can be determined based on the target reliability given in existing specifications, and this reliability level 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. Based on this, R is determined according to the method in step S31. W The representative value R Wk .

[0072] S32. By changing the ductility coefficient μ and the structural period T, and repeating steps S12, S13, S2, and S31, an R model that is easy to use in engineering design can be established. Wk -μ-T relationship curve;

[0073] Because of R Wk The magnitude of R is affected by wind load parameters and structural parameters, among which the duration t of the wind load and the structural stiffness ratio α have a significant impact on R. Wk The magnitude of the damping ratio has the most significant impact. Following the method described above, by changing the values ​​of other parameters (damping ratio, turbulence intensity, stiffness ratio, duration, etc.), it is possible to establish an R-value covering a range of common parameters in engineering design and different parameter conditions. Wk -μ-T relationship curve, which facilitates rapid determination of R in engineering design. W The representative value.

[0074] Based on the structural information required for wind resistance verification, the natural vibration period T of the structure is obtained, and the ductility coefficient μ of the structure is determined by consulting literature databases or code databases; on this basis, R... Wk Rapid determination of R from μ-T relationship curve Wk value.

[0075] S33. Verify the wind resistance capacity according to the revised design expression;

[0076] (6)

[0077] R is clearly defined W Representative value (R) WkAfter determining the quick method for ), it can be based on Figure 5 The process shown establishes an improved method for wind-resistant design of building structures based on target reliability, which can be used in the 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 intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A wind-resistant design improvement method based on inelastic performance and target reliability, characterized in that, Includes the following steps: S1, obtain wind resistance reduction factor R W Probability distribution function; generate multi-sample wind load time history according to wind load characteristic parameter information, and calculate the strength reduction factor R corresponding to different wind storm durations under wind load based on single degree of freedom (SDOF) system W Probability distribution function; S2, revision of wind load carrying capacity limit state equation; introduction of wind-resistant strength reduction factor R related to storm duration W , revision of wind load carrying capacity limit state equation and design expression considering the beneficial effect of structural inelastic performance on wind resistance; Step S2 specifically includes: introducing R W Amendment of the wind design load bearing capacity limit state and the corresponding design limit state design expression: （4） （5） In the formula: R, S G S W Represents structural resistance, permanent load effect, and wind load effect, respectively; R k S Gk S Wk These represent the standard values ​​of structural resistance, permanent load effects, and wind load effects, respectively. These are the partial factors for resistance, permanent load, and wind load, respectively. 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, establish the R Wk -μ-T relationship curve; Wind resistance design shall be carried out according to the revised design expression.

2. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 1, characterized in that, Step S1 is as follows: S11. Generate multi-sample wind load time histories based on wind load parameter information; S12. Establish the SDOF equations of motion for a single-degree-of-freedom system under wind load, and define the ductility coefficient μ and the wind resistance reduction factor R. W Given the ductility coefficient μ and the structural period T, the R under wind load is calculated. W ; （1） （2） （3） In the formula, m and c are the mass and damping of the system, respectively. For system resilience, To obtain the wind load time history, multiple wind speed time histories can be generated using the classic Davenport spectrum, thus yielding multiple... Timeline; These represent the system's displacement, velocity, and speed, respectively; under the same wind load, F e The maximum elastic force for maintaining the elasticity of a single-degree-of-freedom system is F. y For a single-degree-of-freedom system to achieve a yield strength with a specified ductility coefficient, x max x represents the maximum elastoplastic displacement of a single-degree-of-freedom system under wind load. y Yield displacement of a single-degree-of-freedom system; Based on equations (1)-(3), and considering wind load parameters and structural parameter information, the wind resistance strength reduction factor R under a specified ductility coefficient μ is calculated. W ; S13, Establish R related to storm duration W Probability distribution function; after performing multi-sample wind load analysis on the wind load, the R-value is obtained by fitting. W Probability distribution formula .

3. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 2, characterized in that, The wind load parameter information in step S11 includes turbulence intensity I. u The duration t and average wind speed V are specified in step S12; the ductility coefficient μ and structural period T are specified to calculate the wind resistance 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 SDOF system, and the structural period T is determined; then, based on equations (1)-(3), the wind-induced response of the SDOF system is calculated using the generated wind load time history through the dynamic time domain method, and its ductility coefficient μ and strength reduction coefficient R are obtained. W And continuously adjust the random coefficients 'a' generated by the model to adjust the yield force F. y Perform iterative calculations to make the calculated ductility coefficient μ equal to the specified ductility coefficient μ. i If the error is less than the limit of 0.05, the iterative calculation stops when the error is less than the limit requirement, thus obtaining the wind resistance strength reduction factor R corresponding to the specified ductility coefficient μ. W .

4. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 3, characterized in that, In step 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, and calculate multiple R values. W The data samples are then used to perform fitting analysis according to different probability distribution functions to find the goodness of fit R. 2 The highest, that is, the one that best fits R W Probability distribution formula of data samples Probability distribution functions include the Gumbel distribution, Lognormal distribution, Gamma distribution, Weibull distribution, and Normal distribution. These are frequently used in statistics and engineering to model different types of data, and the R² value for fitting data is... 2 The closer the value is to 1, the better the fit.

5. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 1, characterized in that, Step S3 is as follows: S31. Based on step S1, set the target reliability β according to the specifications or owner's requirements. m R is determined by back-calculation using the limit state equations corrected in equations (4) and (5) of step S2. W The representative value R Wk Used for wind-resistant design of structures; S32. By changing the ductility coefficient μ and the structural period T, an R-value that is easy to use in engineering design is established. Wk -μ-T relationship curve; By changing the ductility coefficient μ and the structural period T, and repeating steps S12, S13, S2, and S31, R is established. Wk -μ-T relationship curve; R Wk The magnitude of R is affected by wind load parameters and structural parameters, among which the duration t of the wind load and the post-yield stiffness ratio α of the structure have a significant impact on R. Wk The size has the most significant impact; S33. Verify the wind resistance capacity according to the revised design expression; （6） R is clearly defined W Representative value R Wk After determining the rapid method, a wind resistance improvement design method for building structures based on target reliability is established and applied to the wind resistance design of structures.

6. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 5, characterized in that, In step S31, the target reliability β m The reliability is determined based on the target reliability given in existing specifications, and this reliability level is the minimum limit of the target reliability. If the owner proposes a higher wind resistance reliability requirement, it is determined based on the owner's expected reliability. On this basis, R is determined according to the method in step S31. W The representative value R Wk .

7. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 5, characterized in that, In step S32, by changing the values ​​of damping ratio, turbulence intensity, stiffness ratio, and duration parameters, an R-value is established covering the range of common parameters in engineering design and under different parameter conditions. Wk -μ-T relationship curve, which facilitates rapid determination of R in engineering design. W The representative value.

8. The wind-resistant design improvement method based on inelastic performance and target reliability as described in claim 5, characterized in that, In step S32, the structural information required for wind resistance verification is obtained, the natural vibration period T of the structure is acquired, and the ductility coefficient μ of the structure is determined by consulting literature databases or standard databases; based on this, R... Wk Rapid determination of R from μ-T relationship curve Wk value.

9. The application of the wind-resistant design improvement method based on inelastic performance and target reliability as described in any one of claims 1 to 8, characterized in that, This wind-resistant design improvement method based on inelastic performance and target reliability is applicable to the wind-resistant design improvement of building structures with equivalent single-degree-of-freedom systems, such as high-rise building structures or flat roof structures.

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