Building group seismic loss probability assessment method based on seismic oscillation intensity random field simulation

Abstract

The invention provides a building group seismic loss probability assessment method based on seismic oscillation intensity random field simulation, and belongs to the technical field of seismic loss assessment. The method provided by the invention comprises the following steps: firstly simulating seismic oscillation of a region by adopting a seismic oscillation intensity random field simulation technology to obtain seismic oscillation intensity spatial distribution of different sites, and then estimating loss probability distribution of each building by utilizing a building anti-seismic performance model and a building vulnerability database. According to the method, the occurrence probability of extreme earthquake loss of a large-scale building group can be evaluated more quickly and accurately, and important support is provided for earthquake risk evaluation and post-disaster emergency decision, so that the disaster resistance and recovery capability of a city are enhanced, and the overall toughness of the city is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of earthquake loss assessment, and in particular relates to a method for assessing the probability of earthquake losses of a building complex based on random field simulation of earthquake motion intensity. Background Art

[0002] Earthquakes, as a major natural disaster, cause serious damage to high-density buildings and bring huge challenges to urban development. Therefore, how to accurately assess the losses of buildings under earthquakes, especially extreme earthquake losses, and provide a basis for urban earthquake resistance planning has become an urgent problem to be solved.

[0003] In the probability assessment of earthquake loss of building complexes, it is necessary to first predict the seismic intensity. However, in the existing technology, the influence of terrain and geological conditions on seismic intensity is usually ignored, which makes the prediction of seismic intensity lack a certain accuracy, affecting the final assessment of the probability distribution of earthquake loss of building complexes.

[0004] Therefore, it is necessary to provide a probability assessment method for earthquake loss of building complexes based on random field simulation of earthquake motion intensity to solve the above problems. Summary of the invention

[0005] The present invention provides a method for assessing the probability of earthquake loss of a building complex based on random field simulation of seismic intensity. The method takes into account the influence of terrain and geological conditions, uses random field simulation technology of seismic intensity, utilizes building seismic performance models and vulnerability curves to assess the loss probability of each building, and calculates the total loss probability of the entire building complex in combination with basic building information. The method can more quickly and accurately calculate the probability of earthquake loss of a building complex, provide important support for earthquake risk assessment and post-disaster emergency decision-making, and can effectively solve at least one of the problems mentioned in the background technology.

[0006] In order to solve the above-mentioned technical problems, the present invention is achieved as follows:

[0007] A method for assessing the probability of earthquake loss of a building complex based on random field simulation of earthquake intensity comprises the following steps:

[0008] Step S1, collecting basic information of all buildings in the area to be evaluated, establishing a simplified multi-degree-of-freedom mechanical model of each building, and aggregating the simplified multi-degree-of-freedom mechanical models of all buildings to form a building complex structure model database; collecting terrain and geological condition data of the area to be evaluated, and establishing a geological terrain grid data model;

[0009] Step S2, based on historical earthquake data, cluster analysis is performed on the seismic responses and maintenance costs of different types of buildings under the action of seismic waves, and a building vulnerability database is constructed based on the seismic responses of buildings in a certain damage state under different seismic design levels and different structural type combinations; a building loss proportion database is constructed based on the percentage of different maintenance costs of buildings in a certain damage state under different building maintenance cost categories and different usage category combinations to the replacement cost of the building;

[0010] Step S3, inputting the amplitude modulated historical seismic waves into the building complex structure model database, performing vulnerability analysis on the building based on the incremental dynamic analysis method, obtaining the distribution of engineering demand parameters, and constructing a building seismic performance evaluation model;

[0011] Step S4, considering the topography and geological conditions of the area to be evaluated, introducing terrain condition related terms into the Campbell 2014 earthquake prediction equation, and correcting the geological condition related terms based on the topography and geological conditions to obtain a corrected Campbell 2014 earthquake prediction equation; after the earthquake occurs, using the building complex structure model database and the regional geological and topographic grid data model through pre-earthquake analysis, based on the Monte Carlo simulation method, using the corrected Campbell 2014 earthquake prediction equation to predict the earthquake intensity;

[0012] Step S5, input the predicted earthquake motion intensity into the building seismic performance assessment model, obtain the corresponding earthquake response through numerical simulation, and then input it into the building vulnerability database to obtain the probability that the building is in or exceeds a certain damage state; finally, based on the building loss ratio database, the building complex earthquake loss probability assessment method is adopted to calculate the maintenance cost and time consumption cost of the building complex.

[0013] As a preferred improvement, the process of establishing a simplified multi-degree-of-freedom mechanical model of each building includes the following steps:

[0014] A simplified finite element model is established using the basic information of the building. The concentrated mass method is used to model each floor in the building as a concentrated mass block. Each mass block has only mass but no elastic stiffness. The mass blocks are connected by shear springs. Each shear spring has only elastic stiffness but no mass. The dynamic response of the shear spring is specified by the bearing capacity curve and hysteresis rule of the building.

[0015] As a preferred improvement, the structural parameters of each building model include the mass m of the mass block and the elastic stiffness k of the shear spring. Assuming that the mass of each mass block is equal, the elastic stiffness of each shear spring is also equal. The elastic stiffness k of the shear spring is derived from the mass m of the mass block and the basic period T of the building through modal calculation. The derivation process is expressed as:

[0016]

[0017] The basic period T of the building is calculated based on the typical period T0 and typical number of floors N0 of this type of building. The calculation process is expressed as:

[0018]

[0019] As a preferred improvement, the building bearing capacity curve is generated based on the Hazus database. The generation process is as follows:

[0020] The bearing capacity curve of the tth floor of the building is given by the yield shear force V y，t , yield displacement D y , Ultimate shear force V u，t 、Limit displacement D u , Complete damage displacement D c is defined as follows: y and complete damage displacement D c Provided by Hazus database;

[0021] Yield shear stress V y，t It is expressed as:

[0022] V y，t =γC s mgNΓ t ;

[0023] Ultimate shear force V y，t It is expressed as:

[0024] V u，t =βV y，t ;

[0025] Limit displacement D u It is expressed as:

[0026] D u =μD y ;

[0027] Γ i The calculation process is:

[0028]

[0029] In the formula, γ represents the ratio of yield strength to design strength; C s represents the design strength coefficient; mgN represents the total weight of the target building; Γ t Indicates V y，t and V y，1 ratio; β represents the super strength coefficient related to the ultimate strength and yield strength; μ represents the ductility coefficient; N represents the total number of floors of the building; γ, C s, β, μ are provided by the Hazus database, and their values ​​depend on the structural type and seismic design level of the building;

[0030] The hysteresis rules for buildings are set as follows:

[0031] The moment-resisting steel frame S1 and the light steel frame S3 have good energy dissipation capacity and adopt the elastic perfect plastic model; other structural types are modeled using hysteretic materials in Opensees.

[0032] As a preferred improvement, the seismic design levels are divided into four types, namely high standard, medium standard, low standard and pre-standard seismic design levels; the damage states are divided into slight damage state, moderate damage state, extensive damage state and complete damage state; the building use categories include residential, commercial, public facilities and industrial; the engineering demand parameters include maximum inter-story displacement angle, peak floor acceleration and residual inter-story displacement.

[0033] As a preferred improvement, the modified Campbell 2014 earthquake prediction equation is used to estimate the median value μ of the earthquake intensity. lnIM and standard deviation σ, where:

[0034] lnIM=μ lnIM +δB+δW;

[0035]

[0036] Where, lnIM represents the logarithm of the ground motion intensity; δB and δW are the inter-event residual and intra-event residual, respectively. Both are independent and identically distributed and obey the normal distribution with mean 0 and variance β and ω, respectively.

[0037] μ lnIM =f mag +f dis +f flt +f hng +f hyp +f dip +f atn +f topo +f site ;

[0038] In the formula, f mag represents the magnitude-related term; f dis represents the geometric attenuation related term; f flt represents the fault type related item; f hng represents the hanging plate effect related term; f hyp represents the focal depth related term; f dip represents the fault dip related term; f atn represents the rupture distance related term; f toporepresents the terrain condition related item; f site Indicates items related to geological conditions;

[0039]

[0040]

[0041] f site =f site，G +S C f site，C ;

[0042]

[0043]

[0044] In the formula, c 21 , c 22 , c 23 , c 24 represents the coefficient, and its values ​​are -0.0048, 0.0056, 0.0063, and 0.0049 respectively; e represents the absolute elevation of the station; z represents the source distance elevation of the station; f site，G represents the shallow soil response term; S C represents the regional site effect index; f site，C represents the deep soil response term; θ1, θ2 represent coefficients, with values ​​of 1.03 and 1.05 respectively; k1 represents the coefficient with V S30 Related thresholds are used to distinguish different soil types; V s30 represents the average shear wave velocity within the 30-meter depth range of the site; k2 represents the model coefficient related to the structural period; n represents the model coefficient unrelated to the structural period, which is taken as 1.18; c 11 represents the model coefficient related to the structural period; c represents the model coefficient independent of the structural period, which is 1.88; A 1100 Indicates V S30 is the median estimate of the peak ground acceleration on a rock formation of 1100 m / s.

[0045] As a preferred improvement, the probability of a building being in or exceeding a certain damage state is expressed as:

[0046]

[0047] Where Φ represents the standard normal distribution function; P[ds|S d ] represents the probability of being in or exceeding a certain damage state; ds represents the building damage state; S d Represents the structural seismic response value; It represents the median value of the structural seismic response when the building reaches a certain damage state threshold; β dsIt represents the standard deviation of the natural logarithm of the seismic response of the structure under a certain damage state.

[0048] As a preferred improvement, the maintenance cost includes structural maintenance cost, acceleration-sensitive non-structural maintenance cost and displacement-sensitive non-structural maintenance cost; the time consumption cost is divided into maintenance time cost, recovery time cost and function loss time cost.

[0049] As a preferred improvement, the structural repair cost CS i It is expressed as:

[0050]

[0051]

[0052]

[0053] Acceleration-sensitive non-structural repair costs CNSA i It is expressed as:

[0054]

[0055] CNSA ds，i =BRC i *PONSA ds，i *λ (N) RCA ds，i ;

[0056] Displacement-sensitive non-structural repair costs (CNSD) i It is expressed as:

[0057]

[0058] CNSD ds，i =BRC i *PONSD ds，i *λ (N) RCD ds，i ;

[0059] In the formula, CS ds，i It represents the structural repair cost of a building with use category i in the damaged state ds, BRC i represents the replacement cost of a building with use category i; PMBTSTR ds，i represents the probability that a building with usage category i is in a structural damage state ds; λ (N) Indicates the correction factor related to the number of floors N; RCS ds，i It represents the percentage of the structural repair cost of a building with use category i in the damaged state ds to the replacement cost of the building; CNSA ds，iPONSA represents the acceleration-sensitive non-structural repair cost of a building with utilization category i in damage state ds; ds，i RCA represents the probability that a building with utilization category i is in an acceleration-sensitive non-structural damage state ds; ds，i CNSD is the percentage of the acceleration-sensitive non-structural repair cost of a building in use category i in damage state ds to the replacement cost of the building; ds，i PONSD is the displacement-sensitive non-structural repair cost of a building with usage category i in damage state ds; ds，i RCD represents the probability that a building with utilization category i is in a displacement-sensitive non-structural damage state ds; ds，i represents the percentage of displacement-sensitive non-structural repair costs of a building in use category i in damaged state ds to the replacement cost of the building;

[0060] The non-structural maintenance cost CNS i Expressed as: CNSi=CNSA i +CNSD i ;

[0061] Building maintenance cost CBD for category i i Expressed as: CBD i =μ j (CS i +CNS i );

[0062] In the formula, μ j represents the correction coefficient related to the city classification j, j = 1, 2, 3, 4, 5, when the city classification is level 1, level 2, level 3, level 4 and level 5, μ j The values ​​are 1.2, 1.1, 1.0, 0.95, and 0.9;

[0063] The total maintenance cost CBD is expressed as:

[0064] As a preferred improvement, the maintenance time cost is expressed as:

[0065]

[0066]

[0067] The recovery time cost is expressed as:

[0068]

[0069]

[0070] The time cost of loss of function is expressed as:

[0071]

[0072] Where M represents the number of standard maintenance teams; N ds，i represents the number of buildings with use category i and in damage state ds; RPT ds，i TRP represents the repair time cost of a building with usage category i in the damaged state ds; ds，i represents the repair time cost of a single building with usage category i in the damaged state ds; RCT ds，i TRC represents the time cost of restoration of a building with usage category i in damaged state ds; ds，i FLT represents the recovery time cost of a single building with usage category i in damaged state ds; ds，i FLT represents the repair time cost of a building with usage category i in the damaged state ds; i TFL represents the time cost of loss of building function for use category i; ds，i It represents the recovery time cost of a building with usage category i in the damaged state ds.

[0073] The beneficial effects of the present invention are:

[0074] (1) The present invention uses the Monte Carlo method to simulate the random field of seismic intensity, which can more accurately reflect the spatial correlation and uncertainty of seismic motion. Compared with a single average value or simple interpolation method, it is closer to reality and takes into account the influence of terrain and geological conditions on seismic wave propagation, thereby improving the accuracy of the random field simulation of seismic intensity and laying a good foundation for subsequent building loss assessment.

[0075] (2) For areas with complex terrain such as a large number of mountains and hills, the present invention introduces terrain condition-related terms into the ground motion prediction equation and corrects it. Compared with the ground motion prediction equation that does not consider terrain conditions, the prediction accuracy can be greatly improved;

[0076] (3) Compared with on-site exploration, satellite / UAV, Internet of Things and image recognition, the random field simulation technology of seismic intensity is used to predict the earthquake loss of building complexes through seismic performance model, building vulnerability database and building loss ratio database. It has the advantages of low technical cost, fast calculation speed, strong timeliness and wide coverage. It can realize the rapid prediction of earthquake loss of building complexes after the earthquake, and timely understand the actual disaster situation in various regions after the earthquake, providing first-hand data for accurate assessment of earthquake risks. It helps to timely discover potential high-risk areas and provide decision-making basis for subsequent disaster prevention and mitigation work. It provides guidance for the repair and reinforcement of fragile buildings and infrastructure. It guides the rational deployment of rescue forces and improves the efficiency of emergency response. It optimizes the utilization of rescue resources and improves the scientificity and effectiveness of emergency decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 A flowchart showing a method for assessing the probability of earthquake losses of a building complex based on random field simulation of earthquake motion intensity;

[0078] Figure 2 A schematic diagram showing a database of a building complex structure model;

[0079] Figure 3 Schematic diagram of the multi-degree-of-freedom mechanical model of the building;

[0080] Figure 4 A schematic diagram showing a geological and topographic raster data model;

[0081] Figure 5 It represents the schematic diagram of the seismic performance evaluation model;

[0082] Figure 6 A schematic diagram showing the distribution of seismic intensity in the area to be assessed;

[0083] Figure 7 A schematic diagram showing a building vulnerability database;

[0084] Figure 8 A schematic diagram showing the probability distribution of the maintenance cost of a building complex;

[0085] Fig. 9 Schematic diagram showing the probability distribution of time consumption cost of a building complex. DETAILED DESCRIPTION

[0086] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] Please refer to Figure 1-Figure 9 The present invention provides a method for assessing the probability of earthquake loss of a building complex based on random field simulation of earthquake intensity, comprising the following steps:

[0088] Step S1, collect basic information of all buildings in the area to be evaluated, establish a simplified multi-degree-of-freedom mechanical model of each building, and aggregate the simplified multi-degree-of-freedom mechanical models of all buildings to form a building complex structural model database; collect terrain and geological condition data of the area to be evaluated, and establish a geological terrain grid data model.

[0089] Basic building information includes building age, structure type, usage category, building height, number of floors, building area, longitude and latitude of the building location, and construction cost.

[0090] The process of establishing a simplified multi-degree-of-freedom mechanical model for each building includes the following steps:

[0091] A simplified finite element model is established using the basic information of the building. The concentrated mass method is used to model each floor in the building as a concentrated mass block. Each mass block has only mass but no elastic stiffness. The mass blocks are connected by shear springs. Each shear spring has only elasticity but no mass. The dynamic response of the shear spring is specified by the bearing capacity curve and hysteresis rule of the building. The structural parameters of each building model include the mass m of the mass block and the elastic stiffness k of the shear spring.

[0092] The complex structure of the building is simplified into a number of mass blocks with only mass but no elastic stiffness and some shear springs with only elasticity but no mass through the concentrated mass method. This constitutes a discrete, intuitive and simple finite degree of freedom system. In this system, only partial damping needs to be considered, which can greatly simplify the amount of calculation, making the calculation easier to solve.

[0093] Assuming that the mass of each mass block is equal and the elastic stiffness of each shear spring is also equal, the elastic stiffness k of the shear spring can be easily derived from the mass m of the mass block and the fundamental period T of the structure through modal calculation. The derivation process is expressed as:

[0094]

[0095] The basic period T of the building is calculated based on the typical period T0 and typical number of floors N0 of this type of building. The calculation process is expressed as:

[0096]

[0097] According to Hazus (multi-hazard loss assessment software), the period T of the corresponding target building is calculated based on the typical period T0 and typical number of floors N0 of a certain structural type of building:

[0098]

[0099] The building's bearing capacity curve is generated based on the Hazus database. The generation process is as follows:

[0100] The bearing capacity curve of the tth floor of the building is given by the yield shear force V y，t , yield displacement D y , Ultimate shear force V u，t 、Limit displacement D u , Complete damage displacement D c is defined as follows: y and the complete damage displacement D c Provided by Hazus database;

[0101] Yield shear stress V y，i It is expressed as:

[0102] V y，t =γC s mgNΓ t ;

[0103] Ultimate shear force V u，i It is expressed as:

[0104] V u，t =βV y，t ;

[0105] Limit displacement D u It is expressed as:

[0106] D u =μD y ;

[0107] Γ i The calculation process is:

[0108]

[0109] In the formula, γ represents the ratio of yield strength to design strength; C s represents the design strength coefficient; mgN represents the total weight of the target building; Γ t Indicates V y，t and V y，1 ratio; β represents the super strength coefficient related to the ultimate strength and yield strength; μ represents the ductility coefficient; N represents the total number of floors of the building; γ, C s The values ​​of β and μ are provided by Hazus, and their values ​​depend on the structural type and seismic design level of the building.

[0110] Yield shear stress V y，t , yield displacement D y , Ultimate shear force V u，t、Limit displacement D u and complete damage displacement D c Once determined, the bearing capacity curve of the building can be obtained.

[0111] After determining the bearing capacity curve, the hysteresis rules for different structural types should also be determined. The moment-resisting steel frame S1 and the light steel frame S3 have good energy dissipation capacity, so the elastic perfect plastic model is adopted. Other structural types are modeled using hysteresis materials in Opensees.

[0112] Step S2, based on historical earthquake data, cluster analysis is performed on the seismic responses and maintenance costs of different types of buildings under the action of seismic waves, and a building vulnerability database is constructed based on the seismic responses of buildings in a certain damage state under different seismic design levels and different structural type combinations; a building loss ratio database is constructed based on the percentage of different maintenance costs of buildings in a certain damage state under different building maintenance cost categories and different usage category combinations to the replacement cost of the building.

[0113] Specifically, the building vulnerability database contains the median and log-normal standard deviation of the seismic response of buildings in a certain damage state under different seismic design levels and different structural type combinations. Among them, the seismic design level is divided into four types, namely high-code, medium-code, low-code and pre-code seismic design levels. The damage state is divided into slight damage states, moderate damage states, extensive damage states and complete damage states.

[0114] The database of building loss ratio contains the percentage of different repair costs of buildings in a certain damage state under different building repair cost categories and different use category combinations as a percentage of the building replacement cost, that is, the structural repair cost of the building with use category i in the subsequent step under the damage state ds as a percentage of the building replacement cost (RCS) ds，i , the acceleration-sensitive non-structural repair cost of a building in use category i in damaged state ds as a percentage of the building replacement cost RCA ds，i and the displacement-sensitive non-structural repair cost of a building in use category i in damaged state ds as a percentage of the building replacement cost RCD ds，i .

[0115] Usage categories include residential, commercial, public facilities, industrial, etc.

[0116] Step S3, inputting the amplitude modulated historical seismic waves into the building complex structure model database, performing vulnerability analysis on the building based on the incremental dynamic analysis method, obtaining the distribution of engineering demand parameters, and constructing a building seismic performance evaluation model;

[0117] Engineering requirement parameters include maximum inter-story drift angle (IDR), peak floor acceleration (PFA), residual inter-story drift, etc.

[0118] During the input of historical seismic waves, at least 7 seismic wave data are selected and amplitude modulation is performed at least 8 times to ensure the reliability of the evaluation model.

[0119] Step S4, considering the topography and geological conditions of the area to be evaluated, introducing terrain condition related terms into the Campbell 2014 earthquake motion prediction equation, and correcting the geological condition related terms based on the topography and geological conditions to obtain a corrected Campbell 2014 earthquake motion prediction equation; after the earthquake occurs, through pre-earthquake analysis using the building complex structure model database and the regional geological and topographic raster data model, based on the Monte Carlo simulation method, using the corrected Campbell 2014 earthquake motion prediction equation to predict the earthquake intensity.

[0120] Geological condition data include the average shear wave velocity Vs within 30 meters of the site 30 , the depth Z where the horizontal shear wave velocity is 1.0 km / s 1.0 and the depth Z at which the horizontal shear wave velocity is 2.5 km / s 2.5 ; Topographic data include the absolute elevation of the station (based on sea level) and the source distance elevation (based on the horizontal plane where the earthquake source is located).

[0121] The inter-event residual δB indicates that for a given period building in a single simulation, it is constant in space, but the residuals of the seismic intensity of buildings with different periods are correlated; the intra-event residual δW indicates that the seismic intensity of different stations is correlated under a given simulation. Therefore, the correlation between events and within events needs to be considered.

[0122] The modified Campbell2014 ground motion prediction equation is used to estimate the median value μ of the ground motion intensity. lnIM and standard deviation σ, where:

[0123] lnIM=μl n I M +6B+δW;

[0124]

[0125] Where, lnIM represents the logarithm of the ground motion intensity; δB and δW are the inter-event residual and intra-event residual, respectively. Both are independent and identically distributed and obey the normal distribution with mean 0 and variance β and ω, respectively.

[0126] μ lnIM =f mag +f dis +f flt +f hng +f hyp +f dip +f atn +f topo +f site ;

[0127] In the formula, f mag represents the magnitude-related term; f dis represents the geometric attenuation related term; f flt represents the fault type related item; f hng represents the hanging plate effect related term; f hyp represents the focal depth related term; f dip represents the fault dip related term; f atn represents the rupture distance related term; f topo represents the terrain condition related item; f site Indicates items related to geological conditions;

[0128]

[0129]

[0130] f site =f site，G +S C f site，C ;

[0131]

[0132]

[0133] In the formula, c 21 , c 22 , c 23 , c 24 represents the coefficient, and its values ​​are -0.0048, 0.0056, 0.0063, and 0.0049 respectively; e represents the absolute elevation of the station; z represents the source distance elevation of the station; f site，G represents the shallow soil response term; S C represents the regional site effect index; f site，C represents the deep soil response term; θ1, θ2 represent coefficients, with values ​​of 1.03 and 1.05 respectively; k1 represents the coefficient with V S30Related thresholds are used to distinguish different soil types; V s30 represents the average shear wave velocity within the 30-meter depth range of the site; k2 represents the model coefficient related to the structural period; n represents the model coefficient unrelated to the structural period, which is taken as 1.18; c 11 represents the model coefficient related to the structural period; c represents the model coefficient independent of the structural period, which is 1.88; A 1100 Indicates V S30 is the median estimate of the peak ground acceleration on a rock formation of 1100 m / s.

[0134] Step S5, input the predicted earthquake motion intensity into the building seismic performance assessment model, obtain the corresponding earthquake response through numerical simulation, and then input it into the building vulnerability database to obtain the probability that the building is in or exceeds a certain damage state; finally, based on the building loss ratio database, the building complex earthquake loss probability assessment method is adopted to calculate the maintenance cost and time consumption cost of the building complex.

[0135] The probability that a building is in or exceeds a certain damage state:

[0136]

[0137] Where Φ represents the standard normal distribution function; P[ds|S d ] represents the probability of being in or exceeding a certain damage state; ds represents the building damage state; S d Represents the structural seismic response value; It represents the median value of the structural seismic response when the building reaches a certain damage state threshold; β ds It represents the standard deviation of the natural logarithm of the seismic response of the structure under a certain damage state.

[0138] According to the probability P[ds|S d ] calculates the probability of being in a specific damage state, that is, the subsequent PMBTSTR ds，i ,PONSA ds，i , PONSD ds，i The probability calculation formula for being in a specific damage state is:

[0139] P(PMBTSTR ds，i ,PONSA ds，i , PONSD ds，i )=P[ds2|S d ]-P[ds1|S d ].

[0140] Maintenance costs include structural maintenance costs, acceleration-sensitive non-structural maintenance costs, and displacement-sensitive non-structural maintenance costs; time consumption costs include maintenance time costs, recovery time costs, and function loss time costs.

[0141] Structural repair costs CS i It is expressed as:

[0142]

[0143]

[0144]

[0145] Acceleration-sensitive non-structural repair costs CNSA i It is expressed as:

[0146]

[0147] CNSA ds，i =BRC i *PONSA ds，i *λ (N) RCA ds，i ;

[0148] Displacement-sensitive non-structural repair costs (CNSD) i It is expressed as:

[0149]

[0150] CNSD ds，i =BRC i *PONSD ds，i *λ (N) RCD ds，i ;

[0151] In the formula, CS ds，i It represents the structural repair cost of a building with use category i in the damaged state ds, BRC i represents the replacement cost of a building with use category i; PMBTSTR ds，i represents the probability that a building with usage category i is in a structural damage state ds; λ (N) Indicates the correction factor related to the number of floors N; RCS ds，i It represents the percentage of the structural repair cost of a building with use category i in the damaged state ds to the replacement cost of the building; CNSA ds，i PONSA represents the acceleration-sensitive non-structural repair cost of a building with utilization category i in damage state ds; ds，iRCA represents the probability that a building with utilization category i is in an acceleration-sensitive non-structural damage state ds; ds，i CNSD is the percentage of the acceleration-sensitive non-structural repair cost of a building in use category i in damage state ds to the replacement cost of the building; ds，i PONSD is the displacement-sensitive non-structural repair cost of a building with usage category i in damage state ds; ds，i RCD represents the probability that a building with utilization category i is in a displacement-sensitive non-structural damage state ds; ds，i It represents the percentage of displacement-sensitive non-structural repair cost of a building with utilization category i in damaged state ds to the replacement cost of the building.

[0152] The non-structural maintenance cost CNS i Expressed as: CNS i =CNSA i +CNSD i ;

[0153] Building maintenance cost CBD for category i i Expressed as: CBD i =μ j (CS i +CNS i );

[0154] In the formula, μ j represents the correction coefficient related to the city classification j, j = 1, 2, 3, 4, 5, when the city classification is level 1, level 2, level 3, level 4 and level 5, μ j The values ​​are 1.2, 1.1, 1.0, 0.95, and 0.9 respectively.

[0155] It is understandable that the corresponding material costs, labor costs, management costs, etc. are different for different city levels. The higher the city level (the smaller the value of j), the higher the corresponding maintenance cost. Correction coefficient μ j The introduction of fully considers the differences between cities of different levels, making the calculation of maintenance costs closer to the actual situation.

[0156] The total maintenance cost CBD is expressed as:

[0157] The maintenance time cost is expressed as:

[0158]

[0159]

[0160] The recovery time cost is expressed as:

[0161]

[0162]

[0163] The time cost of loss of function is expressed as:

[0164]

[0165] Where M represents the number of standard maintenance teams; N ds，i represents the number of buildings with use category i and in damage state ds; RPT ds，i TRP represents the repair time cost of a building with usage category i in the damaged state ds; ds，i represents the repair time cost of a single building with usage category i in the damaged state ds; RCT ds，i TRC represents the time cost of restoration of a building with usage category i in damaged state ds; ds，i FLT represents the recovery time cost of a single building with usage category i in the damaged state ds; ds，i FLT represents the repair time cost of a building with usage category i in the damaged state ds; i TFL represents the time cost of loss of building function for use category i; ds，i It represents the recovery time cost of a building with usage category i in the damaged state ds.

[0166] The maintenance cost of a single building includes structural maintenance cost, acceleration-sensitive non-structural maintenance cost, and displacement-sensitive non-structural maintenance cost. The time consumption cost is divided into maintenance time cost, recovery time cost, and function loss time cost. After an earthquake occurs, the spatial distribution of the earthquake intensity of the building complex and the probability distribution of earthquake losses can be quickly and intuitively displayed.

[0167] The solution provided by the present invention can quickly and intuitively display the spatial distribution of earthquake motion intensity and the probability distribution of earthquake losses in building complexes, providing important support for earthquake risk assessment and post-disaster emergency decision-making, thereby enhancing the city's disaster resistance and recovery capabilities.

[0168] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A method for assessing the probability of earthquake losses of a building complex based on random field simulation of earthquake intensity, characterized in that: The steps include: Step S1, collecting basic information of all buildings in the area to be evaluated, establishing a simplified multi-degree-of-freedom mechanical model of each building, and aggregating the simplified multi-degree-of-freedom mechanical models of all buildings to form a building complex structural model database; Collect terrain and geological condition data of the area to be evaluated and establish a geological and topographic raster data model; Step S2, based on historical earthquake data, cluster analysis is performed on the seismic responses and maintenance costs of different types of buildings under the action of seismic waves, and a building vulnerability database is constructed based on the seismic responses of buildings in a certain damage state under different seismic design levels and different structural type combinations; a building loss proportion database is constructed based on the percentage of different maintenance costs of buildings in a certain damage state under different building maintenance cost categories and different usage category combinations to the replacement cost of the building; Step S3, inputting the amplitude modulated historical seismic waves into the building complex structure model database, performing vulnerability analysis on the building based on the incremental dynamic analysis method, obtaining the distribution of engineering demand parameters, and constructing a building seismic performance evaluation model; Step S4, considering the topography and geological conditions of the area to be evaluated, introducing the terrain condition related terms into the Campbell2014 earthquake motion prediction equation, and correcting the geological condition related terms based on the topography and geological conditions to obtain a corrected Campbell2014 earthquake motion prediction equation; After an earthquake occurs, the building complex structure model database and the regional geological terrain grid data model are used for pre-earthquake analysis, and the seismic intensity is predicted using the modified Campbell 2014 seismic motion prediction equation based on the Monte Carlo simulation method; Step S5, input the predicted earthquake motion intensity into the building seismic performance assessment model, obtain the corresponding earthquake response through numerical simulation, and then input it into the building vulnerability database to obtain the probability that the building is in or exceeds a certain damage state; finally, based on the building loss ratio database, the building complex earthquake loss probability assessment method is adopted to calculate the maintenance cost and time consumption cost of the building complex.

2. The method for assessing the probability of earthquake loss of a building complex by simulating a random field of earthquake intensity according to claim 1 is characterized in that: The process of establishing a simplified multi-degree-of-freedom mechanical model for each building includes the following steps: A simplified finite element model is established using the basic information of the building. The concentrated mass method is used to model each floor in the building as a concentrated mass block. Each mass block has only mass but no elastic stiffness. The mass blocks are connected by shear springs. Each shear spring has only elastic stiffness but no mass. The dynamic response of the shear spring is specified by the bearing capacity curve and hysteresis rule of the building.

3. The method for assessing the probability of earthquake loss of a building complex by simulating a random field of earthquake intensity according to claim 2, characterized in that: The structural parameters of each building model include the mass m of the mass block and the elastic stiffness k of the shear spring. Assuming that the mass of each mass block is equal, the elastic stiffness of each shear spring is also equal. The elastic stiffness k of the shear spring is derived from the mass m of the mass block and the basic period T of the building through modal calculation. The derivation process is expressed as: The basic period T of the building is calculated based on the typical period T0 and typical number of floors N0 of this type of building. The calculation process is expressed as:

4. The method for assessing the probability of earthquake loss of a building complex by simulating a random field of earthquake intensity according to claim 2, characterized in that: The building's bearing capacity curve is generated based on the Hazus database. The generation process is as follows: The bearing capacity curve of the tth floor of the building is given by the yield shear force V y，t , yield displacement D y , Ultimate shear force V u，t 、Limit displacement D u , Complete damage displacement D c is defined as follows: y and complete damage displacement D c Provided by Hazus database; Yield shear stress V y，t It is expressed as: V y，t =γC s mgNΓ t ; Ultimate shear force V y，t It is expressed as: V u，t =βV y，t ; Limit displacement D u It is expressed as: D u =μD y ; Γ i The calculation process is: In the formula, γ represents the ratio of yield strength to design strength; C s represents the design strength coefficient; mgN represents the total weight of the target building; Γ t Indicates V y，t and V y，1 ratio; β represents the super strength coefficient related to the ultimate strength and yield strength; μ represents the ductility coefficient; N represents the total number of floors of the building; γ, C s , β, μ are provided by the Hazus database, and their values ​​depend on the structural type and seismic design level of the building; The hysteresis rules for buildings are set as follows: The moment-resisting steel frame S1 and the light steel frame S3 have good energy dissipation capacity and adopt the elastic perfect plastic model; other structural types are modeled using hysteretic materials in Opensees.

5. The method for assessing the probability of earthquake loss of a building complex by simulating a random field of earthquake intensity according to claim 1, characterized in that: There are four types of seismic design levels, namely high standard, medium standard, low standard and pre-standard seismic design levels; the damage states are divided into slight damage state, moderate damage state, extensive damage state and complete damage state; the building use categories include residential, commercial, public facilities and industrial; the engineering demand parameters include maximum inter-story displacement angle, peak floor acceleration and residual inter-story displacement.

6. The method for assessing the probability of earthquake losses of buildings using random field simulation of earthquake intensity according to claim 1 is characterized in that: The modified Campbell 2014 ground motion prediction equation is used to estimate the median value μ of the ground motion intensity. lnIM and standard deviation σ, where: lnIM=μ lnIM +δB+δW; Where, lnIM represents the logarithm of the ground motion intensity; δB and δW are the inter-event residual and intra-event residual, respectively. Both are independent and identically distributed and obey the normal distribution with mean 0 and variance β and ω, respectively. μ lnIM =f mag +f dis +f flt +f hng +f hyp +f dip +f atn +f topo +f site ; In the formula, f mag represents the magnitude-related term; f dis represents the geometric attenuation related term; f flt represents the fault type related item; f hng represents the hanging plate effect related term; f hyp represents the focal depth related term; f dip represents the fault dip related term; f atn represents the rupture distance related term; f topo represents the terrain condition related item; f site Indicates items related to geological conditions; f site =f site，G +S C f site，C ; In the formula, c 21 , c 22 , c 23 , c 24 represents the coefficient, and its values ​​are -0.0048, 0.0056, 0.0063, and 0.0049 respectively; e represents the absolute elevation of the station; z represents the source distance elevation of the station; f site，G represents the shallow soil response term; S C represents the regional site effect index; f site，C represents the deep soil response term; θ1, θ2 represent coefficients, with values ​​of 1.03 and 1.05 respectively; k1 represents the coefficient with V S30 Related thresholds are used to distinguish different soil types; V s30 represents the average shear wave velocity within the 30-meter depth range of the site; k2 represents the model coefficient related to the structural period; n represents the model coefficient unrelated to the structural period, which is taken as 1.18; c 11 represents the model coefficient related to the structural period; c represents the model coefficient independent of the structural period, which is 1.88; A 1100 Indicates V S30 is the median estimate of the peak ground acceleration on a rock formation of 1100 m / s.

7. The method for assessing the probability of earthquake losses of buildings using random field simulation of earthquake intensity according to claim 1 is characterized in that: The probability that a building is in or exceeds a certain damage state is expressed as: Where Φ represents the standard normal distribution function; P[ds|S d ] represents the probability of being in or exceeding a certain damage state; ds represents the building damage state; S d Represents the structural seismic response value; It represents the median value of the structural seismic response when the building reaches a certain damage state threshold; β ds It represents the standard deviation of the natural logarithm of the seismic response of the structure under a certain damage state.

8. The method for assessing the probability of earthquake losses of buildings using random field simulation of earthquake intensity according to claim 1 is characterized in that: Maintenance costs include structural maintenance costs, acceleration-sensitive non-structural maintenance costs and displacement-sensitive non-structural maintenance costs; time consumption costs are divided into maintenance time costs, recovery time costs and function loss time costs.

9. The method for assessing the probability of earthquake losses of buildings using random field simulation of earthquake intensity according to claim 8 is characterized in that: Structural repair costs CS i It is expressed as: Acceleration-sensitive non-structural repair costs CNSA i It is expressed as: CNSA ds，i =BRC i *PONSA ds，i *λ (N) RCA ds，i ; Displacement-sensitive non-structural repair costs (CNSD) i It is expressed as: CNSD ds，i =BRC i *PONSD ds，i *l (N) RCD ds，i ; In the formula, CS ds，i It represents the structural repair cost of a building with use category i in the damaged state ds, BRC i represents the replacement cost of a building with use category i; PMBTSTR ds，i represents the probability that a building with usage category i is in a structural damage state ds; λ (N) Indicates the correction factor related to the number of floors N; RCS ds，i It represents the percentage of the structural repair cost of a building with use category i in the damaged state ds to the replacement cost of the building; CNSA ds，i PONSA represents the acceleration-sensitive non-structural repair cost of a building with utilization category i in damage state ds; ds，i RCA represents the probability that a building with utilization category i is in an acceleration-sensitive non-structural damage state ds; ds，i CNSD is the percentage of the acceleration-sensitive non-structural repair cost of a building in use category i in damage state ds to the replacement cost of the building; ds，i PONSD is the displacement-sensitive non-structural repair cost of a building with usage category i in damage state ds; ds，i RCD represents the probability that a building with utilization category i is in a displacement-sensitive non-structural damage state ds; ds，i represents the percentage of displacement-sensitive non-structural repair costs of a building in use category i in damage state ds to the replacement cost of the building; The non-structural maintenance cost CNS i Expressed as: CNS i =CNSA i +CNSD i ; Building maintenance cost CBD for category i i Expressed as: CBD i =μ j (CS i +CNS i ); In the formula, μ j represents the correction coefficient related to the city classification j, j = 1, 2, 3, 4, 5, when the city classification is level 1, level 2, level 3, level 4 and level 5, μ j The values ​​are 1.2, 1.1, 1.0, 0.95, and 0.9; The total maintenance cost CBD is expressed as:

10. The method for assessing the probability of earthquake losses of buildings using random field simulation of earthquake intensity according to claim 8, characterized in that: The maintenance time cost is expressed as: The recovery time cost is expressed as: The time cost of loss of function is expressed as: Where M represents the number of standard maintenance teams; N ds，i represents the number of buildings with use category i and in damage state ds; RPT ds，i TRP represents the repair time cost of a building with usage category i in the damaged state ds; ds，i represents the repair time cost of a single building with usage category i in the damaged state ds; RCT ds，i TRC represents the time cost of restoration of a building with usage category i in damaged state ds; ds，i FLT represents the recovery time cost of a single building with usage category i in damaged state ds; ds，i FLT represents the repair time cost of a building with usage category i in the damaged state ds; i TFL represents the time cost of loss of building function for use category i; ds，i It represents the recovery time cost of a building with usage category i in the damaged state ds.

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