A building structure vulnerability assessment method based on ground motion parameter zoning map

Abstract

The application discloses a building structure vulnerability evaluation method based on a ground motion parameter zoning map, which comprises two parts of random artificial earthquake generation based on the ground motion parameter zoning map and building structure earthquake vulnerability analysis based on a recurrence period. Target response spectra of five types of sites and four recurrence periods of each street are obtained; random artificial ground motion is generated based on a spectral representation method, and an optimization algorithm is adopted to match the mean response spectrum and the target response spectrum of the random artificial ground motion; a multi-degree-of-freedom shear type layer model based on a BWBN model is established. The parameter values of the multi-degree-of-freedom shear type layer model and the maximum inter-story drift angle threshold and loss ratio of different types of building structures in different damage states are determined. The earthquake vulnerability curves of different types of building structures in different streets in different sites are established. According to the application, the earthquake vulnerability unified evaluation method is suitable for different regions and different types of building structures in China, and the applicability of the evaluation method, the accuracy of the evaluation results and the structure calculation efficiency are improved.

Description

Technical Field

[0001] This invention relates to the technical field of earthquake resistance and disaster prevention of building structures, and in particular to a method for assessing the vulnerability of building structures based on seismic ground motion parameter zoning maps. Background Technology

[0002] Current methods for assessing the seismic vulnerability of building structures have the following main problems:

[0003] (1) When designing seismic resistance for building structures in different regions of the country, the seismic performance under major earthquakes is only verified according to the requirements of the Code for Seismic Design of Buildings (GB50011), without comprehensively evaluating the seismic performance of different types of building structures under different earthquake recurrence periods.

[0004] (2) Current seismic vulnerability assessment of building structures mainly targets individual buildings. When determining the seismic input, it only targets the scenario of a major earthquake. The generated artificial seismic time history cannot reflect the randomness of the seismic motion and is incompatible with the local probabilistic seismic hazard analysis results.

[0005] (3) Current seismic vulnerability assessment methods for building structures mainly use peak ground acceleration (PGA) or spectral acceleration (Sa) as seismic intensity indicators. However, due to the presence of numerous different types of building structures within the same street, different seismic intensity indicators are applicable to different types of structures. For example, PGA is more suitable for assessing the seismic vulnerability of low-rise masonry structures, while Sa is more suitable for assessing the seismic vulnerability of high-rise reinforced concrete structures. Therefore, current methods for assessing the seismic vulnerability of building structures are difficult to compare the seismic performance of different types of building structures within the same street.

[0006] (4) Current assessments of seismic vulnerability of building structures are mainly based on detailed finite element simulations to generate seismic vulnerability curves for several typical and representative building structures. This method not only suffers from a lack of standards in selecting typical and representative buildings, but also generates identical seismic vulnerability curves for the same type of building structure when located in different areas, which does not match the actual earthquake damage scenario. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method for assessing the vulnerability of building structures based on seismic ground motion parameter zoning maps. Considering the varying degrees of seismic hazard in cities across my country and the existence of different types of building structures within cities, this invention proposes a unified seismic vulnerability assessment method applicable to different regions and building types in my country, improving the applicability, accuracy of assessment results, and efficiency of structural calculations. To achieve the above-mentioned objectives and other advantages of this invention, a method for assessing the vulnerability of building structures based on seismic ground motion parameter zoning maps is provided, comprising:

[0008] Random artificial ground motion generation based on ground motion parameter zoning map and seismic vulnerability analysis of building structures based on return period, wherein the vulnerability analysis of building structures based on return period includes the following steps:

[0009] 2-1. Obtain the building structure database for each street and classify it according to basic attributes;

[0010] 2-2. For each building structure, establish a multi-degree-of-freedom shear-type layer model;

[0011] 2-3. Based on the basic attribute parameters in the building structure database, determine the parameter values ​​for the multi-degree-of-freedom shear layer model;

[0012] 2-4. Input the time-frequency non-stationary random artificial ground motions for each street under five site types and four return periods, and calculate the maximum inter-story drift angle of different types of buildings located on that street;

[0013] 2-5. Calculate the mean and standard deviation of the maximum inter-story drift angle for each building in the street under five site types and four return periods, and use the log-normal distribution function to describe its probability density distribution;

[0014] 2-6. Based on the basic attribute parameters in the building structure database, determine the maximum inter-story drift angle threshold for each building under different damage states, and calculate the probability of each building exceeding different damage states under five site types and four return periods.

[0015] 2-7. Based on the basic attribute parameters in the building structure database, determine the seismic loss ratio of each building under different damage states, and calculate the total loss ratio of each building under five site categories and four return periods.

[0016] 2-8. The total earthquake loss ratio and return period were fitted using the cumulative normal distribution function to obtain the seismic vulnerability curves for each building when it is located in the five types of sites.

[0017] Preferably, the generation of random artificial ground motions based on the ground motion parameter zoning map includes the following steps:

[0018] 1-1. Based on the current seismic ground motion parameter zoning map of my country and corresponding to the administrative division code of my country based on streets, extract the basic peak ground acceleration and response spectrum characteristic period of Class II sites for each street.

[0019] 1-2. Adjust the parameters in 1-1 to obtain the target response spectrum for each street under five types of sites and four return periods;

[0020] 1-3. Based on the evolutionary power spectrum model, the spectral representation method is used to generate time-frequency non-stationary random artificial ground motions and calculate the mean response spectrum of the random artificial ground motions.

[0021] 1-4. Using the nine independent parameters of the evolved power spectrum model as target variables, an optimization algorithm is used to match the mean response spectrum of random artificial ground motion with the target response spectrum.

[0022] 1-5. Based on the optimized evolution power spectrum model parameters, the spectral representation method is used to generate time-frequency non-stationary random artificial ground motions for each street under five site types and four return periods.

[0023] Preferably, the objective function for spectral matching in steps 1-4 is the sum of the relative errors obtained by weighting the mean response spectrum of random artificial ground motion at each frequency point with the target response spectrum according to the target spectral value for each return period.

[0024] Preferably, the parameter calibration rule for the multi-degree-of-freedom bending-shear type layer model in steps 2-3 is as follows: determine the equivalent layer mass based on the floor area, number of structural layers, and mass density. m 0; Determine the basic period of the structure based on the structure type and building height. T 0; Based on equivalent layer quality m 0 and the basic period of the structure T 0 Determine the equivalent interlayer elastic stiffness k 0; The values ​​of the 12 parameters of the BWBN hysteresis model are determined based on the structural type and building age.

[0025] Preferably, steps 2-8 use the return period as a measure of seismic intensity to generate seismic vulnerability curves for each building in different site categories, and fit them using a cumulative normal distribution function.

[0026] Compared with the prior art, the beneficial effects of this invention are:

[0027] (1) This invention combines my country’s current seismic ground motion parameter zoning map with the seismic vulnerability analysis method of building structure. Based on the evolution power spectrum model and spectrum representation method, it uses an optimization algorithm to match the mean response spectrum of random artificial ground motion with the target response spectrum provided by the seismic ground motion parameter zoning map, and generates random artificial ground motion under five types of sites and four return periods in different streets. This solves the current problems of wave selection difficulty and lack of standards in the seismic vulnerability assessment of building structure, and makes the seismic vulnerability assessment of building structure more accurate.

[0028] (2) This invention simplifies different types of building structures into a multi-degree-of-freedom shear layer model based on the BWBN model, and proposes a rule for calibrating 15 model parameters based on the basic property parameters of building structures. This solves the problem that current building structure seismic vulnerability assessment models not only have many parameters and are difficult to calibrate, but also have difficulty describing the complex hysteretic characteristics of different types of building structures under seismic action, such as strength degradation, stiffness degradation and pinching effect, making the seismic vulnerability assessment of building structures more efficient.

[0029] (3) This invention uses the earthquake return period index to measure the ground motion intensity in the seismic vulnerability assessment of building structures, which is consistent with the results of the classic probabilistic seismic hazard analysis. It solves the problem that the current seismic vulnerability assessment of building structures generally uses ground peak acceleration (PGA) and spectral acceleration (Sa) and other ground motion intensity indices, which are not applicable to the seismic vulnerability assessment of different regions and different types of building structures in my country, thus making the seismic vulnerability assessment method of building structures more widely applicable. Attached Figure Description

[0030] Figure 1 A flowchart of the structural vulnerability assessment method based on seismic motion parameter zoning map according to the present invention;

[0031] Figure 2 This is a target response spectrum diagram of a target street under five site types and four return periods, according to an embodiment of the building structure vulnerability assessment method based on seismic motion parameter zoning map of the present invention.

[0032] Figure 3 This is a comparison chart of the mean response spectrum of random artificial ground motions with the target response spectrum under four return periods for a Class II site on a target street according to an embodiment of the building structure vulnerability assessment method based on ground motion parameter zoning map of the present invention.

[0033] Figure 4 This is a multi-degree-of-freedom shear-type layer model diagram of different types of building structures in the target street, according to an embodiment of the building structure vulnerability assessment method based on seismic motion parameter zoning map of the present invention.

[0034] Figure 5 This is a distribution map of the maximum inter-story drift angle of a three-story masonry structure in a target street of the present invention, located in a Class II site, under four return periods, according to the structural vulnerability assessment method based on seismic motion parameter zoning map of the present invention.

[0035] Figure 6 This is a seismic vulnerability curve of a three-story masonry structure in a target street located in a Class II site, according to an embodiment of the building structure vulnerability assessment method based on seismic motion parameter zoning map of the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Reference Figure 1 A method for assessing the vulnerability of building structures based on seismic ground motion parameter zoning maps includes: generating random artificial ground motions based on seismic ground motion parameter zoning maps and analyzing the seismic vulnerability of building structures based on return periods.

[0038] The generation of random artificial ground motions based on ground motion parameter zoning maps includes the following steps:

[0039] 1-1. Based on the current seismic ground motion parameter zoning map of my country and corresponding to the administrative division code of my country based on streets, extract the peak ground acceleration (PGA) and response spectrum characteristic period (Tg) of the basic seismic ground motion (50-year exceedance probability 10%) for Class II sites in each street.

[0040] 1-2. Adjust the above parameters to obtain the target response spectrum for each street under five site types (I0, I1, II, III, IV) and four return periods (50-year exceedance probabilities of 63%, 10%, 2%, and 1%, i.e., 50-year, 474-year, 1600-year, and 10000-year return periods);

[0041] 1-3. Based on the evolving power spectrum model, using the spectral representation method, time-frequency non-stationary random artificial ground motions are generated, and the mean response spectrum of these random artificial ground motions is calculated; Evolving power spectrum model:

[0042] ;

[0043] In the formula,

[0044] ;

[0045] in, It's frequency. For time, These are the nine model parameters for the evolution power spectrum model.

[0046] 1-4. Using the nine independent parameters of the evolved power spectrum model as objective variables, an optimization algorithm is employed to match the mean response spectrum and the target response spectrum of random artificial ground motions. The objective function for spectrum matching is the sum of the relative errors obtained by weighting the mean response spectrum and the target response spectrum of random artificial ground motions at each frequency point according to the target spectrum value for each return period. The calculation expression is as follows:

[0047] ;

[0048] In the formula, and The first k The mean response spectrum and the target response spectrum at each frequency point.

[0049] 1-5. Based on the optimized evolution power spectrum model parameters, the spectral representation method is used to generate time-frequency non-stationary random artificial ground motions for each street under five site types and four return periods.

[0050] The structural vulnerability analysis of buildings based on the return period includes the following steps:

[0051] 2-1. Obtain the building structure database for each street and classify it according to basic attributes. The basic attributes should include at least: building age, building height, structural type, usage type, number of floors, and floor area.

[0052] 2-2. For each building structure, the Bouc-Wen-Baber-Noori (BWBN) hysteresis model is used to describe the restoring force of each floor, establishing a multi-degree-of-freedom shear-type floor model; the restoring force vector F of the multi-degree-of-freedom shear-type floor model is... i Each component can be described by the BWBN hysteresis model:

[0053] ;

[0054] In the formula, For the first i The post-yield stiffness ratio of the layers; For the first i Inter-story displacement; For the first i The nonlinear hysteretic displacement of the layer is determined by the following formula:

[0055] ;

[0056] In the formula, for The first derivative with respect to time; and n i For the first i Shape parameters of the uniaxial BWBN model of the layer; and The first i Stiffness and strength degradation parameters of the layer; For the first i Layer in duration t c The cumulative hysteresis energy consumption within the range is determined by the following formula:

[0057] ;

[0058] To describe the first i The function of the layer pinching effect is determined by the following formula:

[0059] ;

[0060] In the formula, and To describe the first i Control parameters for layer pinching effect; For symbolic functions:

[0061] .

[0062] 2-3. Based on the basic attribute parameters in the building structure database, such as structural type, building height, and construction year, determine the parameter values ​​for the multi-degree-of-freedom shear-type layer model. The parameter calibration rule for the multi-degree-of-freedom bending-shear layer model is as follows: determine the equivalent layer mass based on the floor area, number of structural layers, and mass density. m 0; Determine the basic period of the structure based on the structure type and building height. T 0; Based on equivalent layer quality m 0 and the basic period of the structure T 0 Determine the equivalent interlayer elastic stiffness k 0; The values ​​of the 12 parameters of the BWBN hysteresis model are determined based on the structural type and building age.

[0063] 2-4. Input the time-frequency non-stationary random artificial ground motions for each street under five site types and four return periods, and use the Newmark-β method to calculate the maximum inter-story drift angle of different types of buildings in the street;

[0064] 2-5. Calculate the mean and standard deviation of the maximum inter-story drift angle for each building in the street under five site types and four return periods, and use the log-normal distribution function to describe its probability density distribution;

[0065] 2-6. Based on the basic attribute parameters in the building structure database, such as structure type, building height and construction year, determine the maximum inter-story drift angle threshold for each building under different damage states (minor damage, moderate damage, severe damage, collapse damage), and calculate the probability of each building exceeding different damage states under five site types and four return periods.

[0066] 2-7. Based on the basic attribute parameters in the building structure database, such as structure type and construction year, determine the seismic loss ratio of each building under different damage states, and calculate the total loss ratio of each building under five site types and four return periods.

[0067] 2-8. The total earthquake loss ratio and return period are fitted using the cumulative normal distribution function to obtain the seismic vulnerability curves for each building located in five site categories. Using the return period as a measure of ground motion intensity, seismic vulnerability curves are generated for each building in different site categories, and fitted using the cumulative normal distribution function. The calculation expression is as follows:

[0068] ;

[0069] in, T It is the recurrence period. L It is the total earthquake loss ratio, and μ and σ are two fitting parameters.

[0070] Example: Generating random artificial ground motions based on ground motion parameter zoning maps includes the following steps:

[0071] 1-1. Based on the current seismic ground motion parameter zoning map of my country and corresponding to the administrative division code of my country based on streets, extract the peak ground acceleration (PGA) and response spectrum characteristic period (Tg) of the basic seismic ground motion (50-year exceedance probability 10%) for Class II sites in each street.

[0072] 1-2. Adjust the above parameters to obtain the target response spectrum for each street under five site types (I0, I1, II, III, IV) and four return periods (50-year exceedance probabilities of 63%, 10%, 2%, and 1%, i.e., 50-year, 474-year, 1600-year, and 10000-year return periods). The expression for the target response spectrum is:

[0073] ;

[0074] In the formula, a m The peak ground acceleration of the ground motion can be determined and adjusted based on the current seismic ground motion parameter zoning map of my country; β m This is the seismic amplification factor, typically taken as 2.5; T 0 represents the period value of the first inflection point of the target reaction spectrum, which is usually taken as 0.1 s; T g The second inflection point period of the target response spectrum can be determined and adjusted based on my country's current seismic ground motion parameter zoning map; T m The maximum period range is usually taken as 6 s; α is the speed control parameter for the descent phase, usually taken as 1.0.

[0075] Target response spectra under other site types and return periods, characteristic period of response spectra ( T gThe adjustment method is as follows: First, determine the zoning based on the characteristic period Tg of the acceleration response spectrum of the basic ground motion (50-year exceedance probability 10%) for Class II sites; then, determine the corresponding characteristic period according to the site category of the building structure by referring to the table below; finally, consider the influence of the return period. If it is a frequent ground motion (50-year exceedance probability 63.2%), the characteristic period is not adjusted; if it is a rare ground motion (50-year exceedance probability 2%) or an extremely rare ground motion (50-year exceedance probability 1%), the characteristic period needs to be increased by 0.05 s.

[0076]

[0077] Target response spectrum under other types of sites and return periods, peak ground acceleration ( a m The adjustment method is as follows: First, determine the zoning based on the peak ground acceleration (PGA) value of the basic ground motion (50-year exceedance probability 10%) for Class II sites; then, calculate the corresponding PGA based on the site category of the building structure using the following formula; finally, consider the impact of the return period. This applies to frequent ground motions (50-year exceedance probability 63.2%), rare ground motions (50-year exceedance probability 2%), and extremely rare ground motions (50-year exceedance probability 1%). a m The values ​​were taken as 1 / 3, 1.9 times, and 2.9 times the basic ground motion (10% probability of exceedance in 50 years), respectively.

[0078] ;

[0079] In the formula, Peak ground acceleration under basic ground motion (10% probability of exceedance in 50 years) for Class II sites; F The peak acceleration adjustment factor should be taken from the following table:

[0080]

[0081] 1-3. Based on the evolutionary power spectrum model, time-frequency non-stationary random artificial ground motions are generated using the spectral representation method, and the mean response spectrum of these random artificial ground motions is calculated. The evolutionary power spectrum model used is as follows:

[0082] ;

[0083] In the formula:

[0084] ;

[0085] in, Indicates frequency; Indicates time; These are the nine independent parameters of the evolving power spectrum model.

[0086] 1-4. Using the nine independent parameters of the evolved power spectrum model as target variables, an optimization algorithm is employed to match the mean response spectrum of random artificial ground motion with the target response spectrum. The spectrum matching process is as follows:

[0087] (1) The sum of the relative errors obtained by weighting the mean response spectrum and the target response spectrum of random artificial ground motion at each frequency point according to the target spectrum value under each return period is defined as the objective function, and the calculation expression is as follows:

[0088] ;

[0089] In the formula, and The first k The mean response spectrum and the target response spectrum at each frequency point.

[0090] (2) The optimization algorithm can use the differential evolution algorithm to initialize the population, determine the population size, the maximum number of iterations, the scaling factor and the crossover probability, etc.; the iteration termination condition can be set to the objective function being less than or equal to 5%, or reaching the maximum number of iterations;

[0091] 1-5. Based on the optimized evolutionary power spectrum model parameters, time-frequency non-stationary random artificial ground motions for each street under five site types and four return periods are generated using a spectral representation method. The spectral representation method used is as follows:

[0092] ;

[0093] In the formula:

[0094] ;

[0095] in, Indicates the first k One frequency point; n represents the number of frequency intervals; Indicates the first k Each random phase follows a uniform distribution within the interval [0, 2π]. The corresponding period can be calculated using the following formula:

[0096] ;

[0097] The aforementioned structural vulnerability analysis based on the return period includes the following steps:

[0098] Step 2-1) Obtain the building structure database for each street and classify it according to basic attributes. The basic attributes should include at least: building age, building height, structural type, usage type, number of floors, and floor area. The classification rules for basic building attributes are as follows:

[0099] (1) Construction period

[0100] The building's construction date is a specific numerical value, and it can be divided into four categories: no fortification (before 1989), low fortification (1990-2000), medium fortification (2001-2010), and high fortification (after 2010).

[0101] (2) Building height

[0102] Building height is a specific numerical value and can be divided into three categories: low-rise (3 floors and below), mid-rise (4 to 7 floors), and high-rise (8 floors and above).

[0103] (3) Structural type

[0104] The structural types are divided into three categories: steel structures, masonry structures, and reinforced concrete structures.

[0105] (4) Usage type

[0106] The types of buildings can be divided into five categories: residential buildings, commercial buildings, industrial buildings, public utilities, and other types.

[0107] 2-2. For each building structure, the Bouc-Wen-Baber-Noori (BWBN) hysteresis model is used to describe the restoring force of each floor, establishing a multi-degree-of-freedom shear-type floor model. The motion control differential equations of the multi-degree-of-freedom bending-shear-type floor model are as follows:

[0108] ;

[0109] In the formula, C is the damping matrix of the structure. If Rayleigh damping is used, it can be determined based on the first two damping ratios of the structure, the structural mass matrix M, and the stiffness matrix K. U is the input time history of artificial ground motion. N ×1 displacement response vector, N The number of layers in the structure; for N ×1 inter-story displacement response vector; Z is N ×1 inter-story hysteretic displacement response vector; F is N ×1 restoring force vector, determined by the BWBN model; I is N ×1 unit vector; the mass matrix M is represented as:

[0110] ;

[0111] The stiffness matrix K is expressed as:

[0112] ;

[0113] In the formula,m 0 represents the equivalent layer quality; k 0 represents the equivalent interlayer elastic stiffness; and It is a matrix with constant coefficients. The first constant is the restoring force vector F. i Each component can be described by the BWBN hysteresis model:

[0114] ;

[0115] In the formula, For the first i The post-yield stiffness ratio of the layers; For the first i Inter-story displacement; For the first i The nonlinear hysteretic displacement of the layer is determined by the following formula:

[0116] ;

[0117] In the formula, for The first derivative with respect to time; and n i For the first i Shape parameters of the uniaxial BWBN model of the layer; and The first i Stiffness and strength degradation parameters of the layer; For the first i Layer in duration t c The cumulative hysteresis energy consumption within the range is determined by the following formula:

[0118] ;

[0119] To describe the first i The function of the layer pinching effect is determined by the following formula:

[0120] ;

[0121] In the formula, and To describe the first i Control parameters for layer pinching effect; For symbolic functions:

[0122] ;

[0123] There are a total of 15 parameters in the multi-degree-of-freedom shear-type layer model, namely: equivalent layer quality. m Equivalent inter-story elastic stiffness k0, fundamental period of the structure T0, first-order damping ratio of the structure Second-order damping ratio And 12 BWBN hysteresis model parameters.

[0124] 2-3. Based on the basic attribute parameters in the building structure database, such as structure type, building height, and construction year, determine the parameter values ​​for the multi-degree-of-freedom shear layer model. The parameter calibration rules are as follows:

[0125] Assuming the building structure's mass is uniformly distributed along the floor height, estimate the equivalent floor mass based on the floor area. m 0:

[0126] ;

[0127] In the formula, S It is the floor area. N It refers to the number of structural layers. ρ It is the mass density per unit area, which is related to the structure type and building height. The following values ​​can be used as the basis for estimation: (1) Masonry structure: 17 kN / m 2 (2) Reinforced concrete frame structure: 11 ~ 16 kN / m 2 (When the number of stories in a reinforced concrete frame structure is greater than 20, the upper limit value shall be used; when it is less than 5 stories, the lower limit value shall be used.) (3) Steel structure: 8 kN / m 2 .

[0128] (2) Equivalent inter-story stiffness

[0129] The Rayleigh method was used for calculation:

[0130] ;

[0131] In the formula, The first-order mode shape vector of the structure; This is the fundamental natural period of the structure, which is related to the structure type and building height. For reinforced concrete and steel structures, the following empirical formula can be used to estimate it:

[0132] ;

[0133] Among them, reinforced concrete structure: C 1 = 0.047, x = 0.9; Steel structure: C 1 = 0.072, x= 0.8. For masonry structures, the following empirical formula can be used for estimation:

[0134] ;

[0135] (3) BWBN hysteresis model parameters

[0136] The parameters of the BWBN hysteresis model are related to the structural type and the building age, and their values ​​are shown in the table below:

[0137]

[0138] 2-4. Input the time-frequency non-stationary random artificial ground motions for each street under five site types and four return periods. Use the Newmark-β method to calculate the maximum inter-story drift angle of different types of buildings located on that street. The time histories of the time-frequency non-stationary random artificial ground motions for a certain street under five site types and four return periods are determined based on steps 1-1) to 1-5).

[0139] 2-5. Calculate the mean and standard deviation of the maximum inter-story drift angle for each building in the street under five site types and four return periods, and use the log-normal distribution function to describe its probability density distribution.

[0140] 2-6. Based on the basic attribute parameters in the building structure database, such as structure type, building height and construction year, determine the maximum inter-story drift angle threshold for each building under different damage states (minor damage, moderate damage, severe damage, collapse damage), and calculate the probability of each building under different damage states in five types of sites and four return periods.

[0141] ;

[0142] In the formula, The cumulative log-normal distribution function; and The first j Logarithmic mean and logarithmic standard deviation of the maximum inter-story drift angle of a building structure under a given return period; For the first i The inter-story drift angle thresholds for each extreme state are determined as follows: for low-rise buildings, the threshold is 2 / 3 of that for mid-rise buildings; and for high-rise buildings, the threshold is 1 / 3 of that for low-rise buildings.

[0143]

[0144] 2-7. Based on the basic attribute parameters in the building structure database, such as structure type and construction year, determine the seismic loss ratio of each building under different damage states, and calculate the total loss ratio of each building under five site types and four return periods.

[0145] ;

[0146] In the formula, P ij For the first j The structure is in the first recurrence period. i The probability of a damage state; R i For the structure to be in the first i The loss ratio for each damage state is related to the structure type and is determined according to the table below.

[0147]

[0148] Section 2-8 uses the cumulative normal distribution function to fit the total earthquake loss ratio and return period to obtain the seismic vulnerability curves for each building located in five site categories:

[0149] ;

[0150] In the formula, T It is the recurrence period. L It is the ratio of total earthquake losses. μ and σ These are two fitting parameters.

[0151] This embodiment uses the above method to conduct a seismic vulnerability assessment of the building structure of a target street, for further detailed explanation.

[0152] The target street is located in Dongcheng District, Beijing, my country. Since the 1990s, the rapid urbanization and land-use planning of this street have resulted in a landscape where skyscrapers and old buildings coexist. Furthermore, the area is situated in the central eastern part of Beijing, a densely populated and affluent region, making it highly vulnerable to severe casualties and economic losses in the event of a destructive earthquake. Therefore, conducting a seismic vulnerability assessment of the street's building structures is crucial for developing and implementing disaster prevention, relief, and mitigation plans to reduce earthquake damage.

[0153] (I) Generation of random artificial ground motions based on ground motion parameter zoning maps

[0154] First, based on my country's current seismic ground motion parameter zoning map, the peak ground acceleration and characteristic period of the response spectrum for the basic ground motion (50-year exceedance probability 10%) of the target street in site II are obtained as follows: PGA = 0.20 g, Tg = 0.40 s. Then, using an adjustment method, the PGA and Tg are obtained for the street under five site types (I0, I1, II, III, IV) and four return periods (50-year exceedance probabilities of 63%, 10%, 2%, and 1%, i.e., 50-year, 474-year, 1600-year, and 10000-year return periods). Furthermore, using the target response spectrum model expression, the target response spectrum curves for the street under five site types and four return periods are obtained, as shown below. Figure 2 As shown, the plateau segment of the target response spectrum continuously lengthens as the site category changes from I0 to IV. The maximum acceleration response spectrum values ​​are the same for sites of categories II-IV, and are greater than those for categories I0-I1. When the return period increases from 50 years to 10,000 years, the acceleration response spectrum value increases significantly, indicating a positive correlation between spectral acceleration and seismic hazard analysis results.

[0155] Assume a building structure in the target street is located in site type II. Therefore, using the target response spectrum of site type II under four return periods as the matching object, the nine independent parameters in the evolutionary power spectrum model are used as decision variables. As the objective function, a differential evolutionary algorithm is used to fit the mean response spectrum and target response spectrum of random artificial ground motions at each return period. The fitting process is as follows: First, the nine independent parameters in the evolutionary power spectrum model are initialized with a population of 50, a maximum number of iterations of 100, a scaling factor of 0.2~0.8, and a crossover probability of 0.2. Then, crossover and mutation operations are performed to refine the initialized population. Next, the generated population is used in the evolutionary power spectrum model, and 50 random artificial ground motions are generated using a spectral representation method, and the corresponding mean acceleration response spectra are calculated. Then, the objective function is calculated, and the relative error between the mean response spectrum and the target response spectrum is evaluated. If the relative error is less than 5%, the iteration stops, and the optimal population parameters are output. Otherwise, the iteration continues, generating new population parameters until the requirements are met. Finally, the optimal population parameters are used as the parameter values ​​for the evolutionary power spectrum model, generating 50 random artificial ground motions at each return period. The comparison results of their mean spectrum and target spectrum are shown below. Figure 3As shown, the mean response spectrum and the target response spectrum are in excellent agreement across the four return periods, with the relative error controlled to around 5%. It's important to note that the mean and target response spectra exhibit some deviation at certain "stubborn points" in the short period. This deviation cannot be reduced by increasing the number of iterations because the objective function searches for the global optimum, but the model parameters in the evolution power spectrum are less sensitive at these points. In fact, due to the randomness of seismic motion, achieving a perfect fit between the mean and target response spectra will introduce some distortion. Therefore, in practical engineering applications, setting the relative error between the mean and target response spectra to 5% is stable and feasible.

[0156] (II) Seismic Vulnerability Analysis of Building Structures Based on Return Period

[0157] Assume a residential building on this street, located on a Class II site, with a masonry structure, three stories high (approximately 3 meters per floor), a total building height of 9 meters, constructed in 1990, and a floor area of ​​300 square meters. Therefore, the equivalent floor mass can be estimated. m 0 = 5.204 × 10 6 kg; equivalent interlaminar elastic stiffness k 0 = 2.699 × 10 9 N / m; BWBN hysteresis model parameters are obtained by looking up the table: α =0.01, β =1.8, γ =0.5, δ v =0.04, δ η =0.25, ζs =0.6, q =0.25, p =2.5, ψ =0.15, δ ψ =0.008, λ =0.8, n =1. Additionally, the first and second order damping ratios of the structure can be set to 0.05. Meanwhile, the maximum inter-story drift angle thresholds for the building under slight damage, moderate damage, severe damage, and collapse conditions can be obtained from tables: 0.004, 0.006, 0.016, and 0.044, respectively. The seismic loss ratios for the building under basically intact, slight damage, moderate damage, severe damage, and collapse conditions are 5%, 15%, 45%, 90%, and 100%, respectively.

[0158] For this building, the mass of each floor is concentrated at the floor level. A BWBN hysteresis model is used to describe the inter-story restoring forces, and a multi-degree-of-freedom shear-type floor model is established, such as... Figure 4As shown. Input random artificial ground motions of the street where the building is located for four return periods, and use the Newmark-β method to calculate the maximum inter-story drift angle of the building. The probability density distribution of the maximum inter-story drift angle of the building for each return period is shown below. Figure 5 As shown, the maximum inter-story drift angle basically conforms to a log-normal distribution. The mean of the maximum inter-story drift angle increases continuously with the increase of the return period. If we calculate the probability of the building being in different damage states under four return periods, we can see that under a frequent earthquake (50-year exceedance probability 63.2%, corresponding to a 50-year return period), the probability of the building being in a basically intact state is 99%; under a design earthquake (50-year exceedance probability 10%, corresponding to a 475-year return period), the probabilities of the building being in a slightly damaged state and moderately damaged state are 37% and 52%, respectively; under a rare earthquake (50-year exceedance probability 2%, corresponding to a 2500-year return period), the probabilities of the building being in a moderately damaged state and severely damaged state are 73% and 25%, respectively. The analysis results show that the building meets the requirements of my country's seismic fortification code for buildings: "no damage in minor earthquakes, repairable in moderate earthquakes, and no collapse in major earthquakes."

[0159] The calculated seismic loss ratios for the building under return periods of 50 years, 475 years, 2500 years, and 10000 years are 5%, 30%, 56%, and 80%, respectively. A cumulative log-normal distribution function is used to fit the seismic loss ratio to the return period, generating a vulnerability curve for the building based on the seismic return period, as shown below. Figure 5 As shown, the building's earthquake damage ratio increases with the increase in the earthquake recurrence interval.

[0160] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, online cloud storage, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0161] The number of devices and processing scale described herein are for simplification of the invention. Applications, modifications, and variations of this invention will be readily apparent to those skilled in the art. Although embodiments of the invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. It can be applied to various fields suitable for this invention, and further modifications can be readily implemented by those skilled in the art. Therefore, without departing from the general concept defined by the claims and their equivalents, this invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A building structure vulnerability assessment method based on a seismic motion parameter zoning map, characterized by, The application relates to a random artificial earthquake generation based on a seismic motion parameter zoning map and a building structure seismic vulnerability analysis based on a recurrence period, and the building structure seismic vulnerability analysis based on the recurrence period comprises the following steps: 2-1, obtaining a building structure database of each street and performing basic attribute classification; 2-2, establishing a multi-degree-of-freedom shear type layer model for each building structure; 2-3, determining parameter values of the multi-degree-of-freedom shear type layer model according to basic attribute parameters in the building structure database; 2-4, inputting time-frequency non-stationary random artificial ground motions under five types of sites and four recurrence periods of each street, and calculating maximum interlayer displacement angles of different types of buildings located in each street; 2-5, statistically calculating mean values and standard deviations of the maximum interlayer displacement angles of each building under five types of sites and four recurrence periods in each street, and adopting a logarithmic normal distribution function to describe probability density distributions of the mean values and the standard deviations; 2-6, determining maximum interlayer displacement angle threshold values of each building under different damage states according to the basic attribute parameters in the building structure database, and calculating probabilities of each building exceeding different damage states under five types of sites and four recurrence periods; 2-7, determining seismic loss ratios of each building under different damage states according to the basic attribute parameters in the building structure database, and calculating total loss ratios of each building under five types of sites and four recurrence periods; 2-8, adopting a cumulative normal distribution function to fit the total seismic loss ratios and the recurrence periods, and obtaining a seismic vulnerability curve of each building located in five types of sites; The random artificial earthquake generation based on the seismic motion parameter zoning map comprises the following steps: 1-1, based on a current seismic motion parameter zoning map of China, corresponding to a street-based administrative zoning code of China, extracting basic ground motion peak acceleration and characteristic period of response spectrum of each street under II type site; 1-2, adjusting the parameters in 1-1 to obtain target response spectra of each street under five types of sites and four recurrence periods; 1-3, based on an evolutionary power spectrum model, adopting a spectral representation method to generate time-frequency non-stationary random artificial ground motions, and calculating mean response spectra of the random artificial ground motions; 1-4, taking nine independent parameters of the evolutionary power spectrum model as target variables, and adopting an optimization algorithm to match the mean response spectra of the random artificial ground motions with the target response spectra; 1-5, based on the optimized evolutionary power spectrum model parameters, adopting the spectral representation method to generate time-frequency non-stationary random artificial ground motions under five types of sites and four recurrence periods of each street. The spectral matching target function of the step 1-4 is that the relative errors obtained by weighting the mean response spectra of the random artificial ground motions with target spectrum values at each frequency point are summed.

2. The building structure vulnerability assessment method based on a seismic motion parameter zoning map according to claim 1, wherein The step 2-8 adopts the recurrence period as a ground motion intensity measurement index to generate seismic vulnerability curves of each building located in different site categories, and adopts a cumulative normal distribution function to fit the seismic vulnerability curves.

3. The building structure vulnerability assessment method based on a seismic motion parameter zoning map according to claim 1, characterized by, The step 2-3 multi-degree-of-freedom bending shear type layer model parameter calibration rule is: determining the equivalent layer mass according to the floor area, the number of structure layers and the mass density m 0; determining the basic period of the structure according to the structure type and the building height T 0; determining the equivalent layer mass based on the equivalent layer mass m 0 and the basic period of the structure T 0; determining the equivalent interlayer elastic stiffness based on the equivalent layer mass k 0; determining the values of 12 parameters of the BWBN hysteretic model based on the structure type and the building age.

4. The building structure vulnerability assessment method based on seismic motion parameter zoning map according to claim 1, wherein, ​

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