Earthquake vulnerability analysis method and system for loss evaluation

Abstract

The invention relates to a loss assessment-oriented earthquake vulnerability analysis method and system, and particularly relates to the following generation steps of earthquake vulnerability curve data for a huge disaster model: obtaining a damage state loss rate matrix, the data elements of the damage state loss rate matrix comprising a damage state and a loss rate corresponding to the damage state; obtaining a damage state damage probability matrix, wherein data elements of the damage state damage probability matrix comprise the damage state and a damage probability corresponding to the damage state; multiplying the loss rate and the damage probability corresponding to the same damage state to obtain an average loss rate; and storing the damage state and the average loss rate corresponding to the damage state to obtain earthquake vulnerability curve data for the huge disaster model. The method has the advantages that the method can be directly used for calculating the average vulnerability curve data of the earthquake loss, and directly available data is provided for a huge disaster model.

Description

Technical Field

[0001] The present invention belongs to the technical field of catastrophe model data processing, and specifically relates to a seismic vulnerability analysis method and system for loss assessment, and also relates to a method for generating seismic vulnerability curve data for catastrophe models. Background Art

[0002] The destructive earthquake database refers to the accumulation of a large number of earthquake damage matrices of building structures based on intensity, that is, the damage ratio or damage probability of building structures under different intensities. However, the intensity is obtained based on four types of macroscopic phenomena such as human perception, instrument response, damage of engineering structures mainly composed of houses, and surface damage. Therefore, there is a certain causal coupling relationship between intensity and earthquake damage, and due to the relatively small amount of earthquake damage data at high intensities (such as IX and X), the earthquake damage matrix based on intensity has great uncertainty. Currently, mainstream earthquake risk assessment software (such as HAZUS-EQ, GEM, and TELES) and commercial catastrophe models (such as RiskLink of RMS and Touchstone of AIR) mostly use earthquake motion parameters such as PGA or Sa for loss calculation. Therefore, it is necessary to convert the earthquake damage matrix based on intensity into a more general vulnerability curve based on earthquake motion parameters to provide directly available data for catastrophe models and achieve rapid earthquake loss assessment and catastrophe insurance risk assessment. Summary of the Invention

[0003] In view of the technical problems existing in the prior art, the first aspect of the present invention provides a method for generating seismic vulnerability curve data for catastrophe models, including the following steps:

[0004] Obtain a damage state loss rate matrix, where the data elements of the damage state loss rate matrix include damage states and loss rates corresponding to the damage states;

[0005] Obtain a damage state damage probability matrix, where the data elements of the damage state damage probability matrix include the damage states and damage probabilities corresponding to the damage states;

[0006] Multiply the loss rate and the damage probability corresponding to the same damage state to obtain an average loss rate;

[0007] Save the damage state and the average loss rate corresponding to the damage state to obtain seismic vulnerability curve data for catastrophe models.

[0008] The second aspect of the present invention provides a method for presenting vulnerability curve data for catastrophe models, including the following steps:

[0009] Input the seismic vulnerability curve data into the catastrophe model;

[0010] Present the seismic vulnerability curve on a display based on the seismic vulnerability curve data.

[0011] The third aspect of the present invention provides a seismic vulnerability analysis method for loss assessment, including the following steps:

[0012] Input the seismic vulnerability curve data into the catastrophe model;

[0013] Input the damage state and the replacement value of the insured object into the catastrophe model;

[0014] Output the expected damage loss of the insured object based on the current damage state.

[0015] The fourth aspect of the present invention provides a seismic vulnerability analysis system for loss assessment, the system includes at least one processor; and a memory that stores instructions, when the instructions are executed by at least one processor, implement the steps of the method described in any one of the foregoing.

[0016] The beneficial effects of the present invention are as follows: A method for average vulnerability curve data that can be directly used to calculate seismic losses is proposed, providing directly available data for the catastrophe model so that it can be applied to rapid seismic loss assessment and catastrophe insurance risk assessment. Description of the Drawings

[0017] Figure 1 Flowchart of the generation method of seismic vulnerability curve data for the catastrophe model;

[0018] Figure 2 Damage exceedance probability curve based on intensity;

[0019] Figure 3 Average loss rate curve based on intensity;

[0020] Figure 4 Damage exceedance probability curve based on PGA;

[0021] Figure 5 Average loss rate curve based on PGA;

[0022] Figure 6 Example diagrams of excellent, medium, and poor seismic vulnerability;

[0023] Figure 7 Schematic diagram of the seismic vulnerability analysis system for loss assessment. Detailed Embodiments

[0024] The following embodiments further illustrate the content of the present invention, but should not be construed as a limitation of the present invention. Without departing from the spirit and essence of the present invention, modifications or substitutions made to the methods, steps or conditions of the present invention all belong to the scope of the present invention.

[0025] As Figure 1 shown, in some embodiments of the present invention, a method for generating seismic vulnerability curve data for a catastrophe model includes the following steps:

[0026] S1: Obtain a damage state loss rate matrix, where the data elements of the damage state loss rate matrix include a damage state and a loss rate corresponding to the damage state;

[0027] S2: Obtain a damage state failure probability matrix, where the data elements of the damage state failure probability matrix include the damage state and a failure probability corresponding to the damage state;

[0028] S3: Multiply the loss rate and the failure probability corresponding to the same damage state to obtain an average loss rate;

[0029] S4: Save the damage state and the average loss rate corresponding to the damage state to obtain seismic vulnerability curve data for a catastrophe model.

[0030] The term "damage state loss rate matrix" refers to a data set having at least a damage state and a loss rate as data elements.

[0031] The term "damage state failure probability matrix" refers to a data set having at least a damage state and a failure probability as data elements.

[0032] The term "seismic vulnerability curve data" refers to a data set having at least a damage state and an average loss rate as data elements.

[0033] In an embodiment of the present invention, according to the failure probability matrix (i.e., the damage state failure probability matrix), as shown in Equation 1, the average loss rate of a certain ground motion intensity index is calculated:

[0034]

[0035] Where MLR is the average loss rate under a given ground motion intensity index, DS is the damage state (damage state) or damage level (1, 2, 3, 4, 5 respectively represent the five damage levels of basically intact, slightly damaged, moderately damaged, severely damaged, and destroyed), P DS is the failure probability (or failure ratio) of a given damage state under a certain ground motion intensity index, CDF DS is the loss rate (or loss ratio) under a given damage state, and the CDF DS includes a minimum value, a mean value, and a maximum value. The ground motion intensity index includes but is not limited to seismic intensity (I) or peak ground acceleration (PGA).

[0036] The CDF DSAccording to the seismic performance difference grade value DSPF of the same building type in different damage states DS DS for value taking. The DSPF DS includes three levels: excellent, medium, and poor. The value-taking rule is that when DSPF DS is "excellent", CDF DS takes the minimum value; when DSPF DS is "medium", CDF DS takes the average value; when DSPF DS is "poor", CDF DS takes the maximum value. In these embodiments, the seismic performance difference grade value DSPF of the same building type in different damage states DS DS is added for judgment to select the corresponding vulnerability curve, so as to more accurately evaluate the losses under earthquake disasters for housing buildings. For examples, please refer to Figure 6 , Examples 1 to 3.

[0037] Example 1, a certain housing type is "reinforced concrete". The system judges that its DSPF DS is "excellent", and CDF DS should take the minimum value, that is, query Table 1, and the value-taking result of CDF DS is: basically intact 0%, slightly damaged 6%, moderately damaged 16%, severely damaged 46%, destroyed 81%. That is, the vulnerability calculated at this value-taking level is for reinforced concrete with excellent seismic performance, and the losses in actual earthquake disasters will be smaller.

[0038] Example 2, a certain housing type is "industrial factory building". The system judges that its DSPF DS is "medium", and CDF DS should take the average value, that is, query Table 1, and the value-taking result of CDF DS is: basically intact 2%, slightly damaged 11%, moderately damaged 31%, severely damaged 73%, destroyed 91%. That is, the vulnerability calculated at this value-taking level is for industrial factory buildings with moderate seismic performance, and the losses in actual earthquake disasters will be in the middle.

[0039] Example 3, a certain housing type is "masonry building". The system judges that its DSPF DS is "poor", and CDF DS should take the maximum value, that is, query Table 1, and the value-taking result of CDF DS is: basically intact 5%, slightly damaged 15%, moderately damaged 45%, severely damaged 100%, destroyed 100%. That is, the vulnerability calculated at this value-taking level is for reinforced concrete with excellent seismic performance, and the losses in actual earthquake disasters will be larger.

[0040] In some embodiments of the present invention, it relates to a method for generating vulnerability curve data for a catastrophe model. The data elements of the damage state loss rate matrix further include the type of building.

[0041] The acquisition method of the damage state loss rate matrix of the present invention is not limited. Any known damage state loss rate matrix is within the selection scope of the present invention. For example, according to the loss ratio values given in "GB / T 18208.4-2011 Earthquake Field Work - Part 4: Assessment of Direct Disaster Losses" (Table 1), the data elements of the damage state loss rate matrix that can be obtained from this table include the damage state (damage level), loss rate (building loss ratio), and type of building.

[0042] Table 1 Reference values of building loss ratio CDF (%)

[0043]

[0044] In some embodiments of the present invention, it relates to a method for generating vulnerability curve data for a catastrophe model. The failure probability corresponding to the damage state is generated based on the ultimate damage state of the damage state and the exceedance probability of the ultimate damage state.

[0045] In some embodiments of the present invention, the failure probability P under the damage state DS is obtained by using the earthquake damage matrix curve fitting method of Formula 2, Formula 3, and Formula 4.

[0046] P DS0 = 1 - (EP LS1 ) (2)

[0047] p DSk = (EP LS(k+1) ) - (EP LSk ) (k = 1, 2, 3) (3)

[0048] P DS4 = (EP LS4 ) (4)

[0049] In the formula, P DS0 is the occurrence probability of the damage level DS0; EP LS1 is the exceedance probability of the ultimate damage state LS1; P DSk is the occurrence probability at each damage level, where DSk is the damage level (k = 0, 1, 2, 3, 4 respectively represent the five damage levels of basically intact, slightly damaged, moderately damaged, severely damaged, and destroyed); EP LSk is the exceedance probability under a certain ultimate damage state LSk, where LSk is the ultimate damage state (k = 1, 2, 3, 4 respectively represent the four ultimate states of slightly damaged, moderately damaged, severely damaged, and destroyed); EP LS(k+1)is the exceedance probability of the ultimate failure state being LS(k+1); P DS4 is the occurrence probability of the damage level being DS4; EP LS4 is the exceedance probability of the ultimate failure state being LS4.

[0050] In some embodiments of the present invention, it relates to a method for generating vulnerability curve data for a catastrophe model, and the exceedance probability of the ultimate failure state is generated through cumulative calculation based on the failure probability of the ultimate failure state.

[0051] In some embodiments of the present invention, it relates to a method for generating vulnerability curve data for a catastrophe model, and the cumulative calculation method is: performing least squares fitting on the ultimate failure state using a lognormal distribution function.

[0052] In some embodiments of the present invention, it relates to a method for generating vulnerability curve data for a catastrophe model, and the failure states include the failure state based on PGA and the failure state based on intensity.

[0053] In some embodiments of the present invention, considering that seismic peak acceleration is generally used as the input parameter of ground motion intensity in a seismic catastrophe model, referring to the corresponding relationship between macro intensity and acceleration PGA given in "GB / T 17742-2008 China Seismic Intensity Scale" (Table 2), similar to the above calculation method of the average loss rate curve based on intensity, the exceedance probability curves of each ultimate failure state under PGA can also be fitted to obtain the average loss rate curve based on PGA.

[0054] Table 2 Corresponding relationship between seismic intensity and peak acceleration PGA

[0055] Seismic intensity VI VII VIII IX X Median PGA 0.63 1.25 2.50 5.00 10.00 PGA (m / s2) (0.45,0.89) (0.90,1.77) (1.78,3.53) (3.54,7.07) (7.08,14.14)

[0056] In some embodiments of the present invention, it relates to a method for generating vulnerability curve data for a catastrophe model, and further includes a step of generating the expected damage loss of the insured object caused by an earthquake disaster, and the expected damage loss is generated based on the seismic vulnerability curve data.

[0057] In the embodiments of the present invention, for calculating the insurance loss of an earthquake disaster, a more intuitive mathematical form of loss ratio (loss rate) is used instead of directly using the earthquake damage matrix or exceedance probability curve under each failure state. At a given ground motion intensity IM (Intensity Measure), such as macro intensity I (or peak acceleration PGA, response spectrum value Sa), the expected damage loss amount of the insured object can be calculated by the following formula 5:

[0058] Expected damage loss = replacement value * average loss rate (5)

[0059] In some other embodiments of the present invention, a method for presenting vulnerability curve data for a catastrophe model includes the following steps:

[0060] Inputting the earthquake vulnerability curve data into a catastrophe model;

[0061] Based on the earthquake vulnerability curve data, the earthquake vulnerability curve is displayed on the display (see Figure 6 ) presents, such as Figure 3 and Figure 5 shown.

[0062] In some other embodiments of the present invention, a seismic vulnerability analysis method for loss assessment based on seismic vulnerability curve data is provided, comprising the following steps:

[0063] Inputting the earthquake vulnerability curve data into a catastrophe model;

[0064] Input the damage status and the replacement value of the subject matter of insurance into the catastrophe model;

[0065] The expected damage loss of the insured object is output based on the current damage status.

[0066] like Figure 7 As shown, in the last some embodiments of the present invention, it relates to an earthquake vulnerability analysis system for loss assessment, the system 1 includes at least one processor 2; and a memory 3 and a display 4, which store instructions, and when the instructions are executed by at least one processor 2, the steps of the aforementioned method are implemented.

[0067] The following takes the civil structures in the destructive earthquakes in Sichuan Province from 2001 to 2010 as an example to explain in detail the process of converting the earthquake damage matrix into the average loss rate curve (vulnerability curve) suitable for the earthquake catastrophe insurance model.

[0068] Table 3 is the civil structure intensity-building damage ratio vulnerability matrix in destructive earthquakes in Sichuan Province from 2001 to 2010. The cumulative probability of exceeding each extreme damage state is calculated from the cumulative damage probability of the five damage states, and the exceedance probability matrix of the corresponding civil structure is obtained, as shown in Table 4.

[0069] Table 3 Civil structure intensity-failure probability matrix in Sichuan Province (2001-2010) (%)

[0070] Damage state Ⅵ Ⅶ Ⅷ Basically intact 42.63 34.89 4.00 Slightly damaged 32.48 23.25 14.00 Moderately damaged 18.14 17.93 47.00 Severely damaged 6.76 16.44 20.00 Destroyed 0.00 7.50 15.00

[0071] Table 4 Civil structure intensity-exceedance probability matrix in Sichuan Province (2001-2010) (%)

[0072] Damage state Ⅵ Ⅶ Ⅷ Basically intact 100.00 100.00 100.00 Slightly damaged 57.38 65.12 96.00 Moderately damaged 24.90 41.87 82.00 Severely damaged 6.76 23.94 35.00 Destroyed 0.00 7.50 15.00

[0073] The least squares fitting is performed on the ultimate failure states in Table 3 using the lognormal distribution function to obtain the exceedance probability curve of the civil structure failure, and it is compared with the linear interpolation data in Table 3, as Figure 2 shown. Combining with the reference value of the housing loss ratio in Table 1, using the failure probability P DS (calculation formula 2-4), the average loss rate curve under continuous macro intensities can be obtained, as Figure 3 shown.

[0074] Similarly, according to the corresponding relationship between the macro intensity and the acceleration PGA (Table 2), by adopting the calculation method of the average loss rate curve based on the intensity, the exceedance probability curves of each ultimate failure state under PGA can also be fitted ( Figure 4 ), and the average loss rate curve based on PGA ( Figure 5 ) can be obtained.

[0075] Embodiments and functional operations of the subject matter described in this specification can be implemented in digital electronic circuitry, tangibly implemented computer software or firmware, computer hardware, including the structures disclosed in this specification and structural equivalents thereof, or combinations of one or more of the foregoing. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on one or more tangible non-transitory program carriers for execution by, or to control the operation of, a data processing apparatus. The term "data processing apparatus" encompasses all kinds of apparatus, devices, and machines for processing data, including, by way of example, programmable processors, computers, or multiprocessors or multi-computers. The apparatus may include special purpose logic circuitry, e.g., an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The apparatus may also include code that creates an execution environment for the relevant computer programs, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. A computer program (which may also be referred to or described as a program, software, a software application, a module, a software module, a script, or code) can be written in any form of programming language, including a compiled or interpreted language, or a declarative or procedural language, and the computer program can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program may or may not correspond to a file in a file system. The program may be stored in a portion of a file that holds other programs or data, e.g., in one or more scripts in a markup language document; in a single file dedicated to the relevant program; or in multiple co-related files, e.g., files that store one or more modules, subroutines, or portions of code. The computer program may be deployed to execute on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network. For purposes of sending an interaction with a user, embodiments of the subject matter described in this specification can be implemented on a computer having: a display device, e.g., a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display) monitor, for displaying information to the user; and a keyboard and a pointing device such as a mouse or a trackball by which the user can send input to the computer. Other kinds of devices may also be used to send an interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and the input received from the user may be received in any form, including acoustic input, voice input, or tactile input.In addition, a computer can interact with a user by sending a document to a device used by the user and receiving the document from the device; for example, by sending a web page to a web browser on the user's client device in response to a received request from the web browser. Although the present invention has been described in detail above with general descriptions, specific embodiments and experiments, some modifications or improvements can be made to it based on the present invention, which are obvious to those skilled in the art. Therefore, these modifications or improvements made without departing from the spirit of the present invention all fall within the scope of protection required by the present invention.

Claims

1. A method for generating seismic vulnerability curve data for a catastrophe model, characterized in that It includes the following steps: Obtain a damage state loss rate matrix, where the data elements of the damage state loss rate matrix include damage states and the corresponding loss rates; Obtain a damage state failure probability matrix, where the data elements of the damage state failure probability matrix include the damage states and the corresponding failure probabilities; Multiply the loss rate and the failure probability corresponding to the same damage state to obtain an average loss rate; Save the damage states and the corresponding average loss rates to obtain the seismic vulnerability curve data for the catastrophe model.

2. The method for generating vulnerability curve data for a catastrophe model according to claim 1, wherein The data elements of the damage state loss rate matrix and the damage state failure probability matrix further include building types and seismic intensities.

3. The method for generating vulnerability curve data for a catastrophe model according to any one of claims 1 to 2, characterized in that The failure probability corresponding to the damage state is generated based on the ultimate failure state of the damage state and the exceedance probability of the ultimate failure state.

4. The method for generating vulnerability curve data for a catastrophe model according to any one of claims 1 to 3, characterized in that, The exceedance probability of the ultimate failure state is generated through cumulative calculation based on the failure probability of the ultimate failure state.

5. The method for generating vulnerability curve data for a catastrophe model according to any one of claims 1 to 4, characterized in that The cumulative calculation method is: using the lognormal distribution function to perform least squares fitting on the ultimate failure state.

6. The method for generating vulnerability curve data for a catastrophe model according to any one of claims 1 to 5, characterized in that The damage states include damage states based on PGA and damage states based on intensity; preferably, the method for generating the vulnerability curve data for the catastrophe model further includes a step of generating the expected damage loss of the insured subject caused by the earthquake disaster, and the expected damage loss is generated based on the seismic vulnerability curve data.

7. The method for generating vulnerability curve data for a catastrophe model according to any one of claims 1 to 6, characterized in that The average loss rate is calculated according to formula (1): Among them, MLR is the average loss rate under a given ground motion intensity index, DS is the damage state or damage level, and P DS is the probability of damage or damage ratio of a given damage state under a certain ground motion intensity index, and CDF DS is the loss rate or loss ratio under a given damage state; Preferably, the CDF DS takes values according to the seismic performance difference grade value DSPF of the same building type in different damage states DS DS ; Further preferably: the DSPF DS includes three levels of excellent, medium and poor, and the value-taking rule is that when the DSPF DS is "excellent", the CDF DS takes the minimum value; when the DSPF DS is "medium", the CDF DS takes the average value; when the DSPF DS is "poor", the CDF DS takes the maximum value.

8. The method for presenting vulnerability curve data for a catastrophe model according to any one of claims 1 to 7, characterized in that It includes the following steps: Input the seismic vulnerability curve data into the catastrophe model; Present the seismic vulnerability curve on the display based on the seismic vulnerability curve data.

9. A seismic vulnerability analysis method for loss assessment based on the seismic vulnerability curve data described in any one of claims 1 to 8, characterized in that, It includes the following steps: Input the seismic vulnerability curve data into the catastrophe model; Input the damage states and the replacement value of the insured subject into the catastrophe model; Output the expected damage loss of the insured subject based on the current damage state.

10. A seismic vulnerability analysis system for loss assessment, characterized in that, The system includes at least one processor; and a memory that stores instructions, which, when executed by at least one processor, implement the steps of the method according to any one of claims 1-9.

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