A method for matching urban earthquake disaster scenarios

Abstract

The present application discloses a method for matching urban earthquake disaster scenarios, which includes a seismic motion library, an urban earthquake disaster scenario library, and a fast matching algorithm. The fast matching algorithm includes a single wave method, a multi-wave splicing method, and a multi-wave superposition method. The method of the present invention establishes a seismic motion library in advance, uses all seismic motions in the seismic motion library in advance to calculate the seismic response of the urban model, and stores it in the earthquake disaster scenario library. When it is necessary to construct an urban earthquake disaster scenario of a target seismic motion, by comparing the acceleration response spectrum of the target seismic motion with the seismic motion in the seismic motion library, the optimal earthquake disaster scenario is directly matched from the urban earthquake disaster scenario library as the earthquake disaster scenario of the target seismic motion, providing a fast and feasible method for constructing urban earthquake disaster scenarios.

Description

Technical Field

[0001] The present invention belongs to the technical field of rapid urban earthquake disaster assessment, and in particular relates to an urban earthquake disaster scenario matching method. Background Art

[0002] Regional earthquake damage simulation technology has emerged to mitigate urban seismic risks by studying potential urban earthquake risks before an earthquake strikes and rapidly assessing damage after an earthquake occurs. This type of simulation system typically uses the finite element method to model all building structures within a region and analyze their seismic response, resulting in a detailed understanding of the seismic response of the regional building complex.

[0003] However, urban areas often contain a huge number of buildings, and the computational complexity of using nonlinear finite element methods is very large. Therefore, it takes a long time and occupies a lot of computing resources when constructing urban earthquake disaster scenarios. Especially in emergency situations where an earthquake occurs, computer hardware and power equipment may be affected by the earthquake at any time. At this time, a large amount of computing work may be interrupted or errors may occur for various reasons. Therefore, methods with simple calculations and less computational complexity are more advantageous. Summary of the Invention

[0004] In view of this, an urban earthquake disaster scenario matching method is provided to meet the current demand for rapid urban earthquake damage assessment and the shortcomings of existing regional earthquake damage simulation systems.

[0005] In order to solve the above technical problems, the present application discloses a method for matching urban earthquake disaster scenarios, which is characterized by including establishing a seismic motion library and an urban earthquake disaster scenario library, wherein the seismic motion library includes seismic waves and corresponding response spectra, and the seismic motion library is calculated by an urban earthquake disaster simulator to obtain an urban earthquake disaster scenario library, and the earthquake disaster scenario of the target seismic motion is quickly constructed by directly matching the earthquake disaster scenarios in the earthquake disaster scenario library from the urban earthquake disaster scenario library through a fast matching algorithm according to the acceleration response spectrum characteristics of the target seismic motion.

[0006] Furthermore, the earthquake motion library includes natural earthquake acceleration time history records, and the acceleration time history records include peak value, duration, and spectrum characteristics.

[0007] Furthermore, the urban earthquake disaster scenario library is a collection of urban earthquake disaster scenarios of all earthquake motions in the earthquake motion library. The urban earthquake disaster scenario consists of damage index and maximum inter-story displacement angle of all building structures in the urban model, and the damage index and maximum inter-story displacement angle are calculated by nonlinear time history analysis.

[0008] Furthermore, the fast matching algorithm includes a single-wave method, a multi-wave splicing method, and a multi-wave superposition method.

[0009] Furthermore, the single-wave method directly matches the urban earthquake disaster scenario of the same pair of ground motions from the urban earthquake disaster scenario library as the urban earthquake disaster scenario construction result of the target ground motion.

[0010] Furthermore, the multi-wave splicing method groups urban buildings according to basic periods, matches urban earthquake disaster scenario fragments with different seismic motions from the urban earthquake disaster scenario library for each group of buildings according to the basic period of the building structure of this group, and finally splices them as the urban earthquake disaster scenario construction result of the target seismic motion.

[0011] Furthermore, the multi-wave superposition method is a construction result of an urban earthquake disaster scenario using a linear combination of a group of urban earthquake disaster scenarios of earthquake motions in an urban earthquake disaster scenario library as the target earthquake disaster scenario.

[0012] Compared with the existing technology, this application can achieve the following technical effects:

[0013] The urban earthquake disaster scenario matching method provided by the present invention can significantly reduce the computing time and computing resource usage in emergency situations, ensuring that reliable urban earthquake disaster scenario construction results are obtained quickly and stably. The urban earthquake disaster scenario matching method completes the computationally intensive work, namely, the work of establishing an urban earthquake disaster scenario library, in advance. When constructing an urban earthquake damage scenario for a target ground motion, it is only necessary to match the optimal earthquake damage scenario from the urban earthquake disaster scenario library. The computational complexity and computing time required by the matching algorithm are far less than those of nonlinear time-history analysis, and the computational complexity is low and the stability is high. Therefore, the urban earthquake disaster scenario matching method can quickly, stably and reliably establish urban earthquake disaster scenarios, has good economy and practicality, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0015] Figure 1 It is a flow chart of the urban earthquake disaster scenario matching method;

[0016] Figure 2 It is the algorithm flow chart of the multi-wave splicing method;

[0017] Figure 3 It is the algorithm flow chart of the multi-wave superposition method. DETAILED DESCRIPTION

[0018] The following will describe the implementation methods of the present application in detail with reference to the accompanying drawings and examples, so that the implementation process of how the present application applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0019] Rapid matching method for urban earthquake disaster scenarios Figure 1 As shown, the following steps are included: establishing a seismic motion database, establishing an urban earthquake disaster scenario database, and a fast matching algorithm. The fast matching algorithm includes but is not limited to the following three methods: single wave method, multi-wave splicing method, and multi-wave superposition method.

[0020] like Figure 1 As shown, the seismic motion library is established according to the following principles: the selected seismic motions are natural seismic motions; there are no more than two pairs of seismic motions from one earthquake; the magnitude distribution of the selected earthquakes is wide and uniform; the epicenter distance, peak acceleration, duration, and site soil type of the selected seismic motions are wide and uniform.

[0021] like Figure 1 As shown in Figure 1, the earthquake disaster scenario library of the city is established using the urban earthquake disaster simulator YouSimulator platform, specifically as follows: (1) YouSimulator is used to automatically establish an urban area building complex model based on the city GIS data and relevant building attribute data; (2) All seismic motions in the seismic motion library are used as input to start the nonlinear time history analysis of seismic motions in YouSimulator; (3) The analysis results, such as the maximum inter-story displacement angle and damage index of each building structure corresponding to each pair of seismic motions, are stored to establish the earthquake disaster scenario library of the city.

[0022] The concept of the single-wave method. The steps include selecting a seismic motion 1 that best matches the target seismic motion from the seismic motion library, and selecting a corresponding urban earthquake disaster scenario 2 from the urban earthquake disaster scenario library as the matching earthquake damage scenario for the target seismic motion.

[0023] The degree of matching between the seismic motions in step 1 is determined based on the similarity between the seismic motion response spectra. Referring to the design response spectrum in "GB50011-2010 (2016 Edition) Code for Seismic Design of Buildings", the response spectrum period range is taken as 0.00s to 6.00s, and 300 period segments can be obtained by dividing a period segment by 0.02s. Each seismic motion can be represented by the acceleration response spectrum value corresponding to 300 period points. Therefore, each seismic motion can be regarded as a vector with a dimension of 300. The problem of finding the similarity between two seismic motion response spectra is transformed into the problem of finding the distance between two vectors. The distance between two vectors is calculated using the Euclidean distance formula, as follows:

[0024]

[0025] Where n is the dimension of the vector, xi and y i are the i-th elements of the two vectors respectively.

[0026] The algorithm flow chart of the multi-wave splicing method is as follows Figure 2 The main steps include grouping buildings in an urban area according to their structural fundamental periods and calculating the sensitive period segments for each group of buildings; selecting the earthquake motion that best matches the target earthquake motion within each sensitive period segment from the earthquake motion library; selecting an urban earthquake damage scenario segment corresponding to each group of buildings from the urban earthquake damage scenario library; and splicing and combining earthquake damage scenario segments for multiple groups of buildings to construct an urban earthquake disaster scenario for the target earthquake motion. Figure 2 Middle array N t The number of structures whose basic period falls within each period segment of 0.02s; array T n is the seismic motion number matched by the target seismic acceleration response spectrum in each period segment; the array d is the maximum inter-story displacement angle or damage index of each structure in the matched earthquake damage scenario; n is the number of structures; the matrix D is the maximum inter-story displacement angle or damage index of each structure corresponding to each seismic motion in the seismic motion library.

[0027] The principle of this matching algorithm is to reduce the difficulty and efficiency of seismic motion matching by reducing the dimensionality of the matching vector. The algorithm still uses the similarity between seismic acceleration response spectra as the basis for matching. Although the period range of seismic acceleration response spectra spans a wide range, specifically from 0.00s to 6.00s, the fundamental period of a given structure is fixed, and the frequency band in which seismic motion affects it is limited to the fundamental period and a period range nearby. Therefore, regional building clusters can be grouped according to their fundamental period. For each group of structures, seismic motions similar to the target seismic motion within the corresponding period segment can be selected to obtain a set of similar seismic motions. Then, a set of urban seismic damage scenario segments corresponding to each group of structures is selected from the urban seismic damage scenario library. The seismic damage scenario segments of multiple groups of structures are combined to obtain the final, complete matching seismic damage scenario.

[0028] like Figure 2 As shown in the figure, the structural sensitive period is defined as 0.2T0 to 1.5T0, where T0 is the fundamental period of the building structure. The upper limit of 1.5T0 takes into account that the fundamental period of the structure will increase with the increase of seismic response, while the lower limit of 0.2T0 takes into account that the higher-order vibration modes of the structure will also participate in the seismic response.

[0029] The concept of the multi-wave superposition method: The steps include selecting a set of seismic motions from the seismic motion library 1, calculating a set of combination coefficients 2, selecting a set of urban earthquake disaster scenarios corresponding to step 1 from the urban earthquake disaster scenario library and performing linear combination 3.

[0030] like Figure 3As shown, the screening principle for a group of ground motions in step 1 is that the peak acceleration values of the ground motions in the group are substantially the same as the target ground motions, and the frequency spectrum characteristics of the ground motions in the group are greatly different.

[0031] like Figure 3 As shown, the linear programming method is used to calculate the combination coefficient in step 2, with the principle of minimizing the sum of the squares of the differences between the linear combination of the square values of the acceleration response spectra of each earthquake and the corresponding values of the square values of the acceleration response spectrum of the target earthquake at each period point.

[0032] This matching algorithm uses the concept of superimposed ground motions to improve matching efficiency. The principle is as follows: ground motion is a random process, and the structural responses caused by several unrelated ground motions can be treated as independent events. Based on the probabilistic statistical laws of random independent events, the maximum structural responses to multiple unrelated ground motions can be superimposed using the square root of the sum of squares (SRSS). Therefore, the maximum acceleration response and the squared maximum displacement response of the structure under linearly superimposed ground motions can be obtained by linearly combining the squared values of the maximum acceleration response and the squared maximum displacement response of the structure under each of the superimposed ground motions.

[0033] Assume that vector A(a1, a2, ...a 300 ) represents the acceleration response spectrum of the target ground motion and specifies the vector Assume that the vector E1(e11, e12, ...e1 300 ), E2(e21, e22, …e2 300 )…En(en1,en2,…en 300 ) represents a set of acceleration response spectra of earthquake motions in the earthquake motion library, and specifies the vector The elements of the above specified vectors are the square values of the elements of the assumed vector. A set of combination coefficients x1, x2…x can be optimized by linear programming. n , so that the vector AA≈x1EE1+x2EE2+…+x n EEn. At this time, the maximum seismic response of the structure under the target ground motion can be approximately calculated using the following formula:

[0034]

[0035] Where d1, d2…d n are the maximum seismic responses of the structure under the action of each seismic motion in the seismic motion library.

Claims

1. A method for matching urban earthquake disaster scenarios, characterized in that: The method includes establishing a seismic motion library and an urban earthquake disaster scenario library, wherein the seismic motion library includes seismic waves and corresponding response spectra, and the seismic motion library calculates the urban earthquake disaster scenario library through an urban earthquake disaster simulator. According to the acceleration response spectrum characteristics of the target seismic motion, the earthquake disaster scenario in the earthquake disaster scenario library is directly matched from the urban earthquake disaster scenario library through a fast matching algorithm to quickly construct the earthquake disaster scenario of the target seismic motion. The fast matching algorithm is a multi-wave splicing method, and the multi-wave splicing method is to group urban buildings according to basic periods, match urban earthquake disaster scenario fragments of different seismic motions from the urban earthquake disaster scenario library according to the basic period of the building structure of each group of buildings, and finally splice them as the urban earthquake disaster scenario construction result of the target seismic motion.

2. The urban earthquake disaster scenario matching method according to claim 1, characterized in that: The earthquake motion library includes natural earthquake acceleration time history records, and the acceleration time history records include peak value, duration, and spectrum characteristics.

3. The urban earthquake disaster scenario matching method according to claim 1, characterized in that: The urban earthquake disaster scenario library is a collection of urban earthquake disaster scenarios of all earthquake motions in the earthquake motion library. The urban earthquake disaster scenario consists of damage indexes and maximum inter-story displacement angles of all building structures in the urban model. The damage indexes and maximum inter-story displacement angles are calculated by nonlinear time history analysis.

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