Method and device for establishing a loss estimation model considering slope instability caused by earthquake

Abstract

The present invention relates to a method for establishing a loss estimation model considering slope instability caused by earthquakes, comprising the following steps: obtaining the sliding direction of each source point according to the slope aspect data of each dangerous source point in the source point matrix of the earthquake influence field, wherein the source point matrix includes dangerous source points and stable surface points; performing a stacking volume assignment once for each dangerous source point in the source point matrix and the stable surface points in its sliding direction to obtain a stacking volume matrix; summarizing the stacking volume matrix to a kilometer grid, and assigning its value as the proportion of the stacking volume of 1 in the kilometer grid to obtain a landslide rate matrix; and finding the minimum circumscribed matrix of the effective range of the landslide rate matrix to obtain an effective landslide rate matrix. The beneficial effect of the present invention is that the algorithm model proposed by the present invention fully considers the terrain amplification effect, the uncertainty of landslide occurrence, and the influence of the sliding direction and sliding termination conditions of the landslide on the sliding area and stacking volume, and has a wider application range.

Description

Technical Field

[0001] The present invention belongs to the technical field of regional building loss assessment methods based on post-earthquake slope instability analysis, and in particular relates to a method and device for establishing a loss estimation model taking into account slope instability caused by earthquakes. Background Art

[0002] In view of the fact that secondary landslide disasters greatly increase the damage caused by earthquake disasters, the development of earthquake catastrophe insurance models requires the study of key technologies for rapid assessment of regional earthquake landslide risks based on earthquake event sets and considering the landslide movement process. Earthquake landslide risk models for insurance applications need to solve two problems: 1) conform to and reflect the physical mechanism of earthquake landslides as much as possible; 2) simplify the process simulation of landslide instability and movement, and use parameterized methods to achieve rapid calculation of large amounts of data and event sets as much as possible. Therefore, in the process of earthquake landslide risk assessment, the parameterized earthquake landslide hazard model and the parameterized landslide movement risk model can be coupled, and statistical methods can be used to realize the analysis of changes in geotechnical stress and the analysis of geotechnical movement and accumulation, so as to effectively face and integrate the application of the insurance industry.

[0003] In regional earthquake landslide risk assessment, how to comprehensively consider the landslide hazard process and the landslide movement process, and quickly and quantitatively assess the risk of landslide movement processes in large areas and large scales, and promote earthquake landslide risk simulation for large batch event sets are technical problems to be solved by the present invention. Summary of the invention

[0004] The present invention considers the example of the method for establishing the loss estimation model caused by earthquake-induced slope instability, and includes the following steps:

[0005] Acquire the sliding direction of each dangerous material source point according to the slope aspect data of each dangerous material source point in the material source point matrix of the earthquake impact field, wherein the material source point matrix includes dangerous material source points and stable surface points;

[0006] Assigning a deposition amount to each dangerous material source point in the material source point matrix and a stable surface point before the stop sliding point in the sliding direction thereof, to obtain a deposition amount matrix;

[0007] Summarize each point in the accumulation amount matrix into a landslide rate point, calculate the proportion of points with accumulation amount assignment in each landslide rate point to the total number of points, and use this as the landslide rate assignment for each landslide rate point to obtain a landslide rate matrix;

[0008] The minimum outer matrix of the effective range formed by the points whose landslide rates are not zero in the landslide rate matrix is ​​obtained to obtain the effective landslide rate matrix.

[0009] In an example of establishing a loss estimation model considering slope instability caused by an earthquake, the device includes at least one processor; and a memory that stores instructions which, when executed by the at least one processor, implement the steps of the method according to any example of the present invention.

[0010] The beneficial effect of the present invention is that the algorithm model proposed by the present invention fully considers the terrain amplification effect, the uncertainty of landslide occurrence, the sliding direction of the landslide, and the influence of the sliding termination condition on the sliding area and accumulation volume, and has a wider application range. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 . Schematic diagram of the dangerous source point;

[0012] Figure 2 . Calculation method of landslide disaster-causing factors for the earthquake random event set; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] In some embodiments, a method for establishing a loss estimation model considering slope instability caused by an earthquake includes the following steps:

[0014] Obtain the sliding direction of each dangerous source point according to the slope aspect data of each dangerous source point in the source point matrix of the earthquake influence field, where the source point matrix includes dangerous source points and stable ground surface points;

[0015] Assign an accumulation volume to each dangerous source point of the source point matrix and the stable ground surface points before the stop sliding point in its sliding direction once to obtain an accumulation volume matrix;

[0016] Summarize each point in the accumulation volume matrix to the landslide rate point, calculate the proportion of the points with assigned accumulation volume in each landslide rate point to the total number of points, and assign the landslide rate to each landslide rate point to obtain a landslide rate matrix.

[0017] Seismic influence field It can be a specific earthquake with known information such as the earthquake epicenter, magnitude, rupture direction, etc. For example, it can be calculated through an earthquake ground motion parameter attenuation relationship model, and describes that the earthquake influence field includes position information (longitude, latitude) and earthquake ground motion acceleration information (PGA). It should be noted that the present invention does not limit the specific earthquake ground motion parameter attenuation relationship model.

[0018] "Point" of the present invention Also known as a grid. For example, a dangerous source point can also be called a dangerous source grid, and its position is usually determined by longitude and latitude, and the data structure includes longitude and latitude.

[0019] Hazard source point and stable ground surface point , see Figure 1As shown, the dangerous source points represent the points with landslide risks (points marked as 1 in the grid), while the stable ground surface points represent the points without landslide risks (points marked as 0 in the grid).

[0020] Source point matrix refers to a dataset including n sets composed of dangerous source points and stable ground surface points, usually obtained by random sampling;

[0021] Slope aspect data Data characterizing the sliding direction of each dangerous source grid, usually digital elevation model data DEM.

[0022] Sliding direction Characterizes the sliding direction of the landslide, and is also the direction for sequentially determining whether the stable ground surface points are the stopping points of sliding starting from the dangerous source points.

[0023] Point where sliding stops Characterizes the stopping position of the landslide, and is also the stable ground surface point that satisfies the preset stopping conditions found along the sliding direction starting from the dangerous source points.

[0024] Accumulation volume and accumulation volume assignment The accumulation amount characterizes the accumulation situation at the positions passed by the landslide. The accumulation amount assignment is to perform an average accumulation amount assignment for the relevant dangerous source points and stable ground surface points of each sliding. Then, based on this assignment, the accumulation amounts of multiple slides of the relevant dangerous source points and stable ground surface points can be calculated.

[0025] Landslide rate point and landslide rate The resolution of the accumulation amount matrix can be greater than or equal to the resolution of the landslide rate matrix. For example, the resolution of the accumulation amount matrix is 100 m * 100 m, and the resolution of the landslide rate points is a kilometer grid of 1 km * 1 km or a kilometer grid of 25 km * 25 km., where the landslide rate is represented by R landslide is represented.

[0026] Landslide rate matrix Obtaining the landslide rate matrix means that the establishment of the loss estimation model considering the slope instability caused by the earthquake is completed. When a specific ground motion event occurs, the loss rate can be quickly calculated. Assuming that the building damage rate caused by the ground motion parameters is MDR, the final damage rate is R ultimate is: R landslide +(1 - R landslide ) * MDR.

[0027] In some embodiments, the accuracy of the source point matrix and the accumulation amount matrix is 100 m * 100 m, and the landslide rate points are kilometer grids of 1 km * 1 km.

[0028] In some embodiments, the steps for establishing the source point matrix are as follows:

[0029] Calculate the slip probability \(p_f\) of each point in the seismic influence field according to Formula 1 to obtain the slip probability \(p_f\) matrix;

[0030]

[0031] Among them, \(D_n\) represents the permanent displacement matrix obtained according to the permanent displacement of each point in the seismic influence field;

[0032] For each point in the slip probability \(p_f\) matrix, determine whether it landslides through random sampling according to the \(p_f\) value. The points that landslide are the dangerous source points, and the points that do not landslide are the stable ground surface points, that is, the source point matrix is obtained.

[0033] In some embodiments, the steps for establishing the permanent displacement matrix \(D_n\) are as follows:

[0034] Calculate the seismic influence field of a specific earthquake through the ground motion parameter attenuation relationship model to obtain the bedrock PGA matrix of the seismic influence field;

[0035] Multiply each point of the bedrock PGA matrix by the terrain amplification factor \(\alpha\) to obtain \(a\) considering the terrain effect max , and obtain the bedrock PGA matrix considering the terrain effect;

[0036] For each point of the bedrock PGA matrix considering the terrain effect, calculate \(d_n\) according to Formula (2) to obtain the permanent displacement matrix \(d_n\);

[0037]

[0038] Among them, \(a\) c represents the critical acceleration.

[0039] In some embodiments, for the sliding starting from each dangerous source point of the source point matrix, the stable ground surface points that meet the following sliding stop conditions are the sliding stop points:

[0040] 1) \(L\geq L_{Max}\);

[0041] Among them, \(L_{max}\) is the maximum slip distance of the source point. Calculate the maximum slip distance of each source point according to Formulas 3 and 4 to obtain the maximum slip distance matrix;

[0042] \(v = 96.256\times(d_n\) 1.9581 ) Formula 3

[0043] \(L_{max}=3.2148\times(v\) 0.4018 ) Formula 4.

[0044] In some embodiments, for the sliding starting from each dangerous source point of the source point matrix, the stable ground surface point that meets any of the following sliding stop conditions is the sliding stop point:

[0045] 1) L≥LMax;

[0046] 2) ΔDEM<0, and ΔH / L<0.2;

[0047] 3) ΔDEM>0, and ΔH / L<0.6.

[0048] In some embodiments, a landslide rate matrix set storage and indexing is established.

[0049] For each earthquake in the random earthquake event set, its effective landslide rate matrix can be calculated according to the method of the foregoing embodiments, and the landslide effective landslide rate matrix of the random earthquake event set (hereinafter referred to as the landslide rate matrix set) is obtained.

[0050] The storage format of the effective landslide rate matrix includes a data header and a data body;

[0051] The data header is designed as follows:

[0052] Byte position Data type Description Bytes 1 - 8 Double Longitude of the center point of the upper left grid Bytes 9 - 16 Double Latitude of the center point of the upper left grid Bytes 17 - 24 Double Grid accuracy (such as 0.001) Bytes 24 - 28 Int Number of rows of the matrix (rn) Bytes 29 - 32 Int Number of columns of the matrix (cn)

[0053] Data body design: The effective landslide rate matrix data is stored from byte 33 to byte 33 + rn*cn*1; the data type is byte (for example, 70 represents 70%); the storage order is stored row by row from left to right in sequence;

[0054] The space occupied by the storage of the effective landslide rate matrix is 32 + rn*cn bytes, that is, the storage space;

[0055] The storage step is performed on each matrix in the landslide rate matrix set;

[0056] The storage address of the first matrix in the landslide rate matrix set is 0, and the storage address of the nth matrix is the storage address of the n - 1th matrix plus the storage space of the n - 1th matrix;

[0057] A hash index is established between the event ID and the matrix storage address to obtain the landslide rate matrix set index.

[0058] In some embodiments, a landslide rate matrix set retrieval method is provided

[0059] When the earthquake event ID is known, the matrix storage address is obtained from the landslide rate matrix set index;

[0060] 32 bytes of the data header at the specified position of the data file are read according to the matrix storage address, and the data body is read according to the number of rows and columns of the matrix;

[0061] In some embodiments, a method for constructing a landslide vulnerability module is provided.

[0062] For buildings with known locations (or other risk exposures, the same below), earthquake events with potential impact are quickly screened from the earthquake event set according to their locations (refer to CN113204547A, a method and device for rapid earthquake event retrieval).

[0063] For each earthquake event, read its data header and data body.

[0064] Calculate the row number r and column number c of the building according to the building location (longitude lon, latitude lat), the longitude of the upper left grid center point (leftTopLon), the latitude of the upper left grid center point (leftTopLat) and the grid precision (prc s);

[0065]

[0066]

[0067] Read the r*cn+cth byte, which is the landslide rate R of the building location. landslide , assuming that the building damage rate caused by the earthquake parameters is MDR, the final damage rate is R ultimate For: R landslide +(1-R landslide )*MDR.

[0068] In some embodiments, see Figure 2 , provides a method for calculating the landslide hazard factor of the earthquake random event set, specifically:

[0069] 1. Get the number of processing units n (server threads or distributed processing server processing logic units);

[0070] 2. Slice the random earthquake event set into multiple subsets;

[0071] 3. Start a landslide hazard factor calculation module for each subset;

[0072] 4. Summarize the results of the landslide hazard factor calculation module and compile a retrieval index.

[0073] Embodiments and functional operations of the subject matter described in this specification can be implemented in digital electronic circuitry, tangibly embodied computer software or firmware, computer hardware, including the structures disclosed in this specification and their structural equivalents, or in a combination 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.

[0074] As an alternative or in addition, the program instructions can be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, that is generated to encode information for transmission to the appropriate receiver apparatus for execution by a data processing apparatus. A computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of the foregoing devices.

[0075] The term “data processing apparatus” encompasses all kinds of apparatus, devices, and machines for processing data, including, by way of example, a programmable processor, a computer, or multiple processors or 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, in addition to hardware.

[0076] A computer program (which may also be referred to as 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, a component, a subroutine, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. The program can be stored in a portion of a file that holds other programs or data, e.g., in one or more scripts stored in a markup language document; in a single file dedicated to the relevant program; or in multiple coordinated files, e.g., files that store one or more modules, subroutines, or portions of code. The computer program can 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.

[0077] The processes and logical flows described in this specification can be performed by one or more programmable computers that execute one or more computer programs by operating on input data and generating output to perform a function. The processes and logical flows can also be performed by special purpose logic circuitry, such as, for example, an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit), and the apparatus can also be implemented as special purpose logic circuitry.

[0078] Computers suitable for carrying out computer programs include, by way of example, and can be based on general purpose microprocessors or special purpose microprocessors or both of the foregoing, or any other kind of central processing unit. Generally, the central processing unit will receive instructions and data from a read only memory or a random access memory or both. The primary elements of a computer are a central processing unit for executing or running instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to, receive data from and transfer data to one or more mass storage devices for storing data, such as, for example, magnetic disks, magneto-optical disks, or optical disks. However, a computer need not have such devices. In addition, a computer can be embedded in another device, such as, for example, a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a removable storage device, such as, for example, a Universal Serial Bus (USB) flash drive, etc.

[0079] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, by way of example, including: semiconductor memory devices, such as, for example, EPROM, EEPROM, and flash memory devices; magnetic disks, such as, internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0080] To send interactions with a user, implementations of the subject matter described in this specification can be implemented on a computer having: a display device, such as 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 can also be used to send interactions with the user; for example, the feedback provided to the user can be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic input, voice input, or tactile input. Additionally, a computer can interact with a user by sending documents to and receiving documents from the device used by the user; for example, by sending a web page to a web browser on a user's client device in response to a request received from the web browser.

[0081] Implementations of the subject matter described in this specification can be implemented in a computing system that includes backend components such as, for example, a data server, or includes middleware components such as, for example, an application server, or includes frontend components such as, for example, a client computer having a graphical user interface or a web browser through which a user can interact with an implementation of the subject matter described in this specification, or the computer system can include any combination of one or more such backend components, middleware components, or frontend components. Components in the system can be interconnected by any form or medium of digital data communication such as, for example, a communication network. Examples of communication networks include local area networks (“LANs”) and wide area networks (“WANs”), such as, for example, the Internet. A computing system can include clients and servers. Clients and servers are typically remote from each other and typically interact through a communication network. The relationship between a client and a server is created by computer programs that run on respective computers and have a client-server relationship with each other.

[0082] Although this specification contains many specific implementation details, these should not be construed as limitations on the scope of any invention or of what can be claimed, but rather as descriptions of features that may be specific to particular implementations of particular inventions. The particular features described in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, the various features described in the context of a single implementation can also be implemented independently in multiple implementations or in any suitable sub-combination. Moreover, although the features may be described above as acting in combination and even initially claimed as such, one or more features from a claimed combination can in some cases be excluded from the combination, and the claimed combination can be directed to a sub-combination or variation of a sub-combination.

[0083] Similarly, although operations are depicted in the drawings in a particular order, it should not be understood that such operations are required to be performed in the particular order shown or in sequential order to achieve the desired results, or that all illustrated operations must be performed. In certain circumstances, multitasking and parallel processing may be advantageous. Additionally, the separation of various system modules and components in the above-described embodiments should not be understood as required in all embodiments, and it should be understood that program components and systems may generally be integrated in a single software product or packaged into multiple software products.

[0084] Particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. For example, the acts recited in the claims may be performed in a different order and still achieve the desired results. As one example, the processes depicted in the figures are not necessarily required to be in the particular order shown or in sequential order to achieve the desired results. In certain implementations, multitasking and parallel processing may be advantageous.

Claims

1. A method for establishing a loss estimation model considering slope instability caused by earthquakes, characterized in that, It includes the following steps: Obtain the sliding direction of each source point according to the slope direction data of each dangerous source point in the source point matrix of the earthquake influence field, where the source point matrix includes dangerous source points and stable ground surface points; Perform a stacking volume assignment on each dangerous source point of the source point matrix and the stable ground surface points before the stop sliding point of its sliding direction once to obtain a stacking volume matrix; Summarize each point in the stacking volume matrix to a landslide rate point, calculate the proportion of the points with stacking volume assignment in the total number of points in each landslide rate point, and assign the landslide rate to each landslide rate point to obtain a landslide rate matrix; Find the minimum circumscribed matrix of the effective range composed of the points with non-zero landslide rate in the landslide rate matrix to obtain an effective landslide rate matrix; The accuracy of the source point matrix and the stacking volume matrix is 100 meters * 100 meters, and the landslide rate point is a 1-kilometer * 1-kilometer kilometer grid; The establishment steps of the source point matrix are as follows: Calculate the sliding probability pf of each point in the earthquake influence field according to Formula 1 to obtain a sliding probability pf matrix; Among them, Dn represents a permanent displacement matrix obtained according to the permanent displacement of each point in the earthquake influence field; For each point in the sliding probability pf matrix, determine whether a landslide occurs according to the pf value through random sampling. The points where landslides occur are the dangerous source points, and the points where no landslides occur are the stable ground surface points, that is, the source point matrix is obtained.

2. The method according to claim 1, wherein The establishment steps of the permanent displacement matrix Dn are as follows: Calculate the earthquake influence field of a specific earthquake through the ground motion parameter attenuation relationship model to obtain the bedrock PGA matrix of the earthquake influence field; Multiply each point of the bedrock PGA matrix by the topographic amplification factor α to obtain a considering the topographic effect max , and obtain the bedrock PGA matrix considering the topographic effect; For each point in the bedrock PGA matrix considering the terrain effect, calculate dn according to Formula (2) to obtain a permanent displacement matrix dn; Among them, a c represents the critical acceleration.

3. The method according to claim 1, characterized in that For each point in the source point matrix, for each point in its sliding direction, judge whether the landslide sliding stops according to the following steps: If one of the following conditions is met, the landslide sliding stops: 1) L≥LMax; Among them, Lmax is the maximum sliding distance of the source point. Calculate the maximum sliding distance of each source point according to Formula 3 and Formula 4 to obtain a maximum sliding distance matrix; v = 96.256 * (dn 1.9581 ) Formula 3 Lmax = 3.2148 * (v 0.4018 ) Formula 4.

4. The method according to claim 1, for each point in the source point matrix, for each point in its sliding direction, judge whether the landslide sliding stops according to the following steps: If one of the following conditions is met, the landslide sliding stops: 2) ΔDEM<0, and ΔH / L<0.2; 3) ΔDEM>0, and ΔH / L<0.

6.

5. A computer-readable storage medium having computer programs / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor according to the following steps, the storage and indexing of the landslide rate matrix set described in any one of claims 1-4 are realized: For each earthquake in the random earthquake event set, obtain a random earthquake event set landslide effective landslide rate matrix; The storage format of the effective landslide rate matrix includes a data header and a data body; The data header includes the longitude of the grid center point, the latitude of the grid center point, the grid accuracy, the number of matrix rows, and the number of matrix columns; The data body includes: storing the effective landslide rate matrix data from byte 33 to byte 33 + rn * cn * 1; the data type is byte; the storage order is row by row, from left to right in sequence; The space occupied by storing the effective landslide rate matrix is 32 + rn * cn bytes, which is the storage space; Perform the storage step for each matrix in the landslide rate matrix set; The storage address of the first matrix in the landslide rate matrix set is 0, and the storage address of the nth matrix is the storage address of the (n - 1)th matrix plus the storage space of the (n - 1)th matrix; Establish a hash index between the event ID and the matrix storage address in step 18 to obtain the landslide rate matrix set index.

6. A method for retrieving a landslide rate matrix set based on the computer-readable storage medium according to claim 5, characterized in that, When the earthquake event ID is known, obtain the matrix storage address from the landslide rate matrix set index; Read the 32-byte data header at the specified position of the data file according to the matrix storage address, and read the data body according to the number of rows and columns of the matrix.

7. A method for constructing a landslide vulnerability module based on the computer-readable storage medium according to claim 5, characterized in that It includes the following steps: For a building at a known location, quickly screen out potentially influential earthquake events from the earthquake event set according to its location; For each earthquake event, read its data header and data body; Calculate the row number r and column number c where the building is located according to the building location, the longitude of the center point of the upper left grid, the latitude of the center point of the upper left grid, and the grid accuracy; Read the r*cn + c-th byte, which is the landslide rate R where the building is located landslide , obtain the building damage rate MDR caused by ground motion parameters, and calculate the final damage rate as R ultimate is: R landslide +(1 - R landslide ) * MDR.

8. A system of a loss estimation model considering slope instability caused by earthquakes, characterized in that, The system includes at least one processor; and a memory that stores instructions, and when the instructions are executed by at least one processor, the steps of the method according to any one of claims 1 - 4 are implemented.

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