Earthquake-induced slope displacement prediction method, device, equipment, medium and product

Abstract

The invention relates to the technical field of side slope slippage, in particular to an earthquake-induced side slope displacement prediction method, device, equipment, medium and product, and the method comprises the steps: setting different side slope models, and determining a target earthquake intensity parameter according to an earthquake record; performing simulation based on a material point method to obtain a slope permanent displacement result of each slope model under seismic oscillation, and performing fitting according to the slope permanent displacement results to obtain a linear regression equation of slopes with the same slope angle; and generating a slope permanent displacement prediction chart according to the linear regression equation of the slopes with the same slope angle, and predicting the earthquake-induced slope displacement based on the slope permanent displacement prediction chart. Therefore, the problems that in the prior art, a solving method is simplified, precision is limited, numerical simulation is complex, dependency is high, and unified standards are lacked are solved.

Description

Technical Field

[0001] The present application relates to the technical field of slope sliding, and in particular to a method, device, equipment, medium and product for predicting earthquake-induced slope displacement. Background Art

[0002] Earthquake landslides are a common geological disaster that often cause huge casualties and economic losses. In order to effectively prevent and control earthquake landslide disasters and reduce their impact, it is particularly important to conduct stability analysis of slopes under earthquake action. Among them, the permanent displacement of the slope under earthquake action is a key indicator for evaluating its stability, which can intuitively reflect the performance and damage degree of the slope in an earthquake.

[0003] At present, the commonly used solution methods are mainly Newmark slider method and numerical simulation method. The Newmark slider method is simple in concept and easy to calculate, and has been widely used in the seismic design of slope engineering, but it contains simplified assumptions and may not fully reflect the true response of the slope. The numerical simulation method can consider more influencing factors and provide more accurate displacement prediction, but the calculation process is complicated and highly dependent on the model. Summary of the invention

[0004] The present application provides a method, device, equipment, medium and product for predicting earthquake-induced slope displacement to solve the problems in the prior art such as simplified solution method, limited accuracy, complex numerical simulation, strong dependence, and lack of unified standards.

[0005] The first aspect of the present application provides a method for predicting earthquake-induced slope displacement, comprising the following steps: setting different slope models, and determining target seismic intensity parameters according to seismic motion records; simulating the permanent displacement results of each slope model under seismic motion based on the material point method, and fitting the linear regression equation of the slopes with the same slope angle according to the permanent displacement results; generating a slope permanent displacement prediction chart according to the linear regression equation of the slopes with the same slope angle, and predicting the earthquake-induced slope displacement based on the slope permanent displacement prediction chart.

[0006] Optionally, the linear regression equation is:

[0007] ln(D)=aln(PGV)+b,

[0008] Where D is the permanent displacement of the slope, PGV is the peak ground velocity, and a and b are regression parameters determined by the geometric parameters of the slope itself and the soil strength parameters.

[0009] Optionally, generating a slope permanent displacement prediction chart based on the linear regression equation of the slope with the same slope angle includes: analyzing the relationship between the regression coefficient of the linear regression equation and the slope soil strength parameter; constructing a dimensionless parameter for determining the performance of the slope itself, and generating the slope permanent displacement prediction chart based on the relationship between the dimensionless parameter and the regression coefficient and the slope soil strength parameter.

[0010] Optionally, the relationship between the regression coefficient and the slope soil strength parameter includes: soil cohesion and soil internal friction angle are negatively correlated with the slope permanent displacement, and soil weight and slope height are positively correlated with the slope permanent displacement.

[0011] Optionally, predicting the earthquake-induced slope displacement based on the slope permanent displacement prediction chart includes: calculating dimensionless parameters according to geometric parameters and strength parameters of the example slope; obtaining slope displacement regression equation coefficients of the example slope by linear interpolation; and solving the earthquake-induced slope displacement under different earthquake motions based on the calculated dimensionless parameters, slope displacement regression equation coefficients and the slope permanent displacement prediction chart.

[0012] Optionally, before determining the target seismic intensity parameters according to the seismic motion records, the method further includes: acquiring a seismic motion database; determining a seismic hazard curve of the site where the slope is located based on a probabilistic seismic hazard analysis; and selecting seismic motion records from the seismic motion database according to the seismic hazard curve.

[0013] The second aspect of the present application provides an earthquake-induced slope displacement prediction device, including: a setting module, used to set different slope models, and determine the target seismic motion intensity parameters according to the seismic motion record; a fitting module, used to simulate the permanent displacement result of each slope model under seismic motion based on the material point method, and obtain the linear regression equation of the slope with the same slope angle according to the slope permanent displacement result; a prediction module, used to generate a slope permanent displacement prediction chart according to the linear regression equation of the slope with the same slope angle, and predict the earthquake-induced slope displacement based on the slope permanent displacement prediction chart.

[0014] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the earthquake-induced slope displacement prediction method as described in the above embodiment.

[0015] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the earthquake-induced slope displacement prediction method as described in the above embodiment.

[0016] The fifth aspect of the present application provides a computer program product, including a computer program or instructions, which, when executed, are used to implement the earthquake-induced slope displacement prediction method as described in the above embodiment.

[0017] Therefore, this application includes the following beneficial effects:

[0018] The embodiment of the present application significantly improves the prediction accuracy of the permanent displacement of the slope by setting up a variety of slope models and combining the actual seismic records to determine the target seismic intensity parameters. The advanced material point method is used for numerical simulation to obtain the permanent displacement data of each slope model under the action of an earthquake, and a linear regression equation suitable for slopes with the same slope angle is fitted based on this, so that the prediction results are closer to the actual situation. In addition, by generating a slope permanent displacement prediction chart, the prediction process is simplified, and the slope displacement prediction can be carried out conveniently without the need for complex numerical simulation calculations. As a result, the technical problems in the prior art such as simplified solution methods, limited accuracy, complex numerical simulation, strong dependence, and lack of unified standards are solved.

[0019] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0021] Figure 1 A flowchart of a method for predicting earthquake-induced slope displacement according to an embodiment of the present application;

[0022] Figure 2 A flowchart of a method for predicting earthquake-induced slope displacement according to an embodiment of the present application;

[0023] Figure 3 A schematic diagram of the acceleration of the response spectrum of the earthquake motion provided according to an embodiment of the present application;

[0024] Figure 4 A schematic diagram of a matrix level of earthquake motion provided according to an embodiment of the present application;

[0025] Figure 5 A schematic diagram of a slope model established according to an embodiment of the present application;

[0026] Figure 6 A schematic diagram of gravity linear loading provided according to an embodiment of the present application;

[0027] Figure 7 A schematic diagram of the permanent displacement results of a slope provided according to an embodiment of the present application;

[0028] Figure 8 is the regression coefficient a and the dimensionless parameter provided according to the embodiment of the present application The relationship diagram between

[0029] Fig. 9 is the regression coefficient b and dimensionless parameter provided according to the embodiment of the present application The relationship diagram between

[0030] Fig.10 A schematic diagram of solving the displacement of a slope with a slope of 25° provided according to an embodiment of the present application;

[0031] Fig.11 A schematic diagram of solving the displacement of a slope with a slope of 35° provided according to an embodiment of the present application;

[0032] Fig.12 A schematic diagram of solving the displacement of a slope with a slope of 45° provided according to an embodiment of the present application;

[0033] Fig.13 A comparison chart showing the results obtained by interpolation using the chart method provided in the embodiment of the present application and the results obtained by fitting the displacement data;

[0034] Fig.14 This is an example diagram of a device for predicting earthquake-induced slope displacement according to an embodiment of the present application;

[0035] Fig.15 Schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0037] Earthquake landslides are a common geological disaster that often cause huge casualties and economic losses. In order to effectively prevent and control earthquake landslide disasters and reduce their impact, it is particularly important to conduct stability analysis of slopes under earthquake action. Among them, the permanent displacement of the slope under earthquake action is a key indicator for evaluating its stability, which can intuitively reflect the performance and damage degree of the slope in an earthquake.

[0038] At present, there are two main methods for solving the permanent displacement of earthquake slopes: the Newmark slider method and the numerical simulation method. The Newmark slider method estimates the permanent displacement by quadratically integrating the part of the earthquake acceleration-time history that exceeds the landslide initiation threshold. Its solution has been proven to be able to better reflect the seismic performance of the slope, so it has been widely used. However, this method is based on a series of simplified assumptions and may not fully reflect the true response of the slope. In order to solve the permanent displacement more accurately, numerical simulation methods can be tried. For example, Fotopoulou and Pitilakis used FLAC2D software to calculate the impact of 40 earthquake motions on 12 slope models, and established an empirical prediction model for permanent displacement based on displacement data. In recent years, other numerical simulation methods, such as finite element method and finite difference method, can also be used to establish a prediction model for the permanent displacement of slopes. However, the accuracy of these models is limited by the number of slope models and earthquake motions used, and the model form is relatively complex, which is not convenient for direct application.

[0039] The earthquake-induced slope displacement prediction method, device, equipment, medium and product of the embodiment of the present application are described below with reference to the accompanying drawings. In view of the problem of inaccurate prediction results mentioned in the above background technology, the present application provides an earthquake-induced slope displacement prediction method, in which a variety of slope models are set, and the target seismic intensity parameters are determined in combination with actual seismic records, thereby significantly improving the prediction accuracy of the permanent displacement of the slope. By using the advanced material point method for numerical simulation, the permanent displacement data of each slope model under the action of the earthquake are obtained, and the linear regression equation applicable to the slope with the same slope angle is fitted based on this, so that the prediction results are closer to the actual situation. In addition, by generating a slope permanent displacement prediction chart, the prediction process is simplified, and the slope displacement prediction can be carried out conveniently without the need for complex numerical simulation calculations. As a result, the problems of simplified solution methods, limited accuracy, complex numerical simulation, strong dependence, and lack of unified standards in the prior art are solved.

[0040] Specifically, Figure 1 A schematic flow chart of a method for predicting earthquake-induced slope displacement provided in an embodiment of the present application.

[0041] like Figure 1 As shown, the earthquake-induced slope displacement prediction method includes the following steps:

[0042] In step S101, different slope models are set, and target ground motion intensity parameters are determined according to ground motion records.

[0043] Among them, the slope model refers to a mathematical model or physical model established to study and analyze the behavior of the slope under specific conditions. The seismic motion record refers to the ground motion data recorded by monitoring equipment such as seismographs when an earthquake occurs. The target seismic motion intensity parameters may include the magnitude, intensity, and peak acceleration of the earthquake.

[0044] It can be understood that the embodiments of the present application, by setting up a variety of slope models and combining actual seismic records to determine the target seismic intensity parameters, help to timely discover the risk of slope instability, improve project safety, and provide strong support for scientific research on slope stability.

[0045] It should be noted that the slope model parameters may include slope height, slope angle, soil weight, soil cohesion, soil internal friction angle, Poisson's ratio and elastic modulus. Among them, the Poisson's ratio and elastic model of the homogeneous soil slope do not significantly affect the stability of the slope itself. Therefore, when setting the slope model, the Poisson's ratio and elastic modulus are kept constant.

[0046] In an embodiment of the present application, before determining the target seismic motion intensity parameters based on the seismic motion records, it also includes: acquiring a seismic motion database; determining the seismic hazard curve of the site where the slope is located based on a probabilistic seismic hazard analysis; and selecting seismic motion records from the seismic motion database based on the seismic hazard curve.

[0047] The earthquake motion database may be a data set storing a large number of earthquake motion records.

[0048] It can be understood that the seismic motion database obtained in the embodiment of the present application provides a rich data source for slope stability analysis. The seismic hazard curve of the site where the slope is located is determined based on the probabilistic seismic hazard analysis, which can scientifically evaluate the earthquake disasters that the site may suffer in the future and their probability distribution, and provide a quantitative basis for seismic design and earthquake risk assessment. Selecting seismic motion records from the seismic motion database according to the seismic hazard curve can ensure that the selected records match the seismic hazard of the site where the slope is located, thereby improving the accuracy and reliability of simulation and prediction.

[0049] Specifically, the peak ground velocity in the seismic intensity parameter is selected because it has a good correlation with the permanent displacement of the slope under the action of the earthquake. Therefore, the seismic intensity parameter selected is PGV, and its calculation formula is as follows:

[0050] PGV=max|v(t)|,

[0051] Where v(t) is the ground velocity time history.

[0052] In step S102, the permanent displacement result of each slope model under earthquake motion is simulated based on the material point method, and the linear regression equation of the slope with the same slope angle is fitted according to the permanent displacement result of the slope.

[0053] Among them, the material point method can simulate the dynamic response and permanent displacement of the slope under the action of earthquake. The permanent displacement of the slope can be the irreversible displacement of the slope under the action of earthquake.

[0054] It is understandable that the embodiment of the present application adopts an advanced material point method to effectively simulate the dynamic response and permanent displacement of the slope under earthquake, providing a powerful tool for slope stability analysis. By simulating different slope models and quantifying the permanent displacement of the slope, it is crucial to evaluate the stability and repair needs of the slope after an earthquake. At the same time, the analysis of the simulation results reveals the relationship between the slope response and the seismic parameters, providing a theoretical basis for the seismic design of the slope. Finally, the linear regression equation is fitted based on the permanent displacement results to simplify the prediction process and improve the prediction efficiency.

[0055] Specifically, the material point open source code MPM3D-f90 is used for slope modeling and displacement solution under earthquake action. The material point method uses a dual description of Lagrangian particles and Euler grids to discretize the continuum into particles that carry regional material information. No information is stored on the grid nodes, which are only used for solution calculations. At the end of each time step, the deformed grid is discarded and the new grid system is used to solve the next time step. Based on the updated Lagrangian format, the governing equations for the conservation of mass, conservation of momentum, and solution equations of the continuum are in the following form:

[0056]

[0057]

[0058]

[0059] Where ρ is the medium density, v is the velocity, σ ij is the Cauchy stress, b is the force per unit mass acting on the object, is the acceleration.

[0060] Compared with other traditional numerical simulation methods, the material point method can effectively avoid the problem of mesh distortion. In addition, in order to simulate the deformation process of the slope under earthquake, the original material point open source code was improved by adding free field boundaries on both sides of the model and adding seismic input boundaries and absorbing boundaries at the bottom of the model.

[0061] In the embodiment of the present application, the linear regression equation is:

[0062] ln(D)=aln(PGV)+b,

[0063] Where D is the permanent displacement of the slope, PGV is the peak ground velocity, and a and b are regression parameters determined by the geometric parameters of the slope itself and the soil strength parameters.

[0064] Specifically, for each determined slope model, the least squares method is used to fit the solved slope permanent displacement results to obtain a linear regression equation, which is expressed in the following form:

[0065] ln(D)=aln(IM)+b,

[0066] Among them, D is the permanent displacement of the slope, IM is the ground motion intensity parameter, a and b are regression parameters, which are determined by the geometric parameters of the slope itself and the soil strength parameters;

[0067] Since the earthquake intensity parameter selected in the embodiment of the present application is the ground peak velocity, the linear regression equation is:

[0068] ln(D)=aln(PGV)+b.

[0069] In step S103, a slope permanent displacement prediction chart is generated according to a linear regression equation of slopes with the same slope angle, and the earthquake-induced slope displacement is predicted based on the slope permanent displacement prediction chart.

[0070] It can be understood that the embodiment of the present application utilizes the previously established linear regression equation of the slopes with the same slope angle to generate a slope permanent displacement prediction chart, which provides an intuitive and efficient tool for predicting earthquake-induced slope displacement, helps to accurately evaluate the stability of the slope under earthquake action, and can quickly understand the permanent displacement of the slope under different earthquake motion intensities.

[0071] In an embodiment of the present application, a slope permanent displacement prediction chart is generated based on a linear regression equation of a slope with the same slope angle, including: analyzing the relationship between the regression coefficient of the linear regression equation and the slope soil strength parameter; constructing a dimensionless parameter for determining the performance of the slope itself, and generating a slope permanent displacement prediction chart based on the relationship between the dimensionless parameter and the regression coefficient and the slope soil strength parameter.

[0072] Among them, the slope soil strength parameters can be parameters of mechanical properties such as shear resistance and compression resistance of the soil, and the dimensionless parameters can be parameters that do not depend on specific units and are used to make unified comparisons and analyses of the same object under different conditions.

[0073] It can be understood that the embodiment of the present application constructs dimensionless parameters for determining the performance of the slope itself by deeply analyzing the intrinsic relationship between the regression coefficient of the linear regression equation and the slope soil strength parameters, and generates a slope permanent displacement prediction chart based on these key parameters, which can deeply understand the response behavior of the slope under external loads such as earthquakes and improve the prediction accuracy of the slope permanent displacement.

[0074] Specifically, construct the dimensionless constant To characterize the performance of the slope itself, The larger the value, the stronger the stability of the slope itself. There are two requirements for this dimensionless parameter: one is that it contains the geometric parameters and strength parameters of the slope itself, and the other is that it has a good correlation with the regression equation coefficients a and b, so that the regression coefficient of the general slope can be solved by this parameter.

[0075] It should be noted that the above dimensionless parameters The slope angle is not considered, which has a significant impact on the calculation of the permanent displacement of the slope due to earthquakes.

[0076] In the embodiment of the present application, the relationship between the regression coefficient and the slope soil strength parameters includes: soil cohesion and soil internal friction angle are negatively correlated with the permanent displacement of the slope, and soil weight and slope height are positively correlated with the permanent displacement of the slope.

[0077] In an embodiment of the present application, an earthquake-induced slope displacement is predicted based on a slope permanent displacement prediction chart, including: calculating dimensionless parameters according to geometric parameters and strength parameters of an example slope; obtaining slope displacement regression equation coefficients of the example slope by linear interpolation; and solving the earthquake-induced slope displacement under different earthquake motions based on the calculated dimensionless parameters, slope displacement regression equation coefficients and the slope permanent displacement prediction chart.

[0078] It can be understood that the embodiment of the present application calculates dimensionless parameters to standardize slope characteristics, uses linear interpolation technology to estimate slope displacement regression equation coefficients based on historical or experimental data, and combines these parameters, coefficients and slope permanent displacement prediction charts to solve and predict the possible displacement of the slope under different earthquake motions. This can eliminate the differences between different slopes, improve prediction accuracy, and thus scientifically evaluate the stability of the slope.

[0079] According to the earthquake-induced slope displacement prediction method proposed in the embodiment of the present application, by setting a variety of slope models and combining the actual seismic records to determine the target seismic intensity parameters, the prediction accuracy of the permanent displacement of the slope is significantly improved. By using the advanced material point method for numerical simulation, the permanent displacement data of each slope model under the action of the earthquake is obtained, and the linear regression equation applicable to the slope with the same slope angle is fitted accordingly, so that the prediction result is closer to the actual situation. In addition, by generating a slope permanent displacement prediction chart, the prediction process is simplified, and the slope displacement prediction can be carried out conveniently without complex numerical simulation calculations. As a result, the problems of simplified solution methods, limited accuracy, complex numerical simulation, strong dependence, and lack of unified standards in the prior art are solved.

[0080] The following will be combined Figure 2 The prediction method of earthquake-induced slope displacement is specifically described as follows:

[0081] S1. Set up the slope model, select appropriate earthquake motion, establish the slope model in the material point method, simulate the deformation process of the slope under earthquake action, and calculate the permanent displacement.

[0082] Specifically, 18 groups of slope models are set, the slope angles of the slope models are set to 25°, 35° and 45°, the slope heights are set to 15m and 25m, the elastic modulus is 100MPa, the Poisson's ratio is 0.4, and 6 slope models are set for slopes with different slope angles, and their dimensionless constants are 0.05, 0.1, 0.2, 0.4, 0.6 and 0.8 respectively. Among them, the weight, cohesion and internal friction angle of the slope soil are shown in Table 1 below.

[0083] Table 1 Slope model parameters

[0084]

[0085] A probabilistic earthquake hazard analysis is conducted on a certain site. Based on the analysis results, 100 earthquake motion data are selected from the global earthquake motion database NGA-West2. The earthquake motion response spectrum acceleration is as follows: Figure 3 As shown, the matrix level is Figure 4 shown.

[0086] The slope model established in the material point method is as follows: Figure 5 As shown in the figure, the distance between the toe of the slope and the left boundary of the model is L1 = 100m, and the distance between the toe of the slope and the right boundary of the model is L2 = 50m. At the same time, the height of the bottom of the slope is twice the height of the slope, which can reduce the reflection of seismic waves from the slope boundary. The slope is divided into two layers, and the bottom bedrock is set as elastic material with a specific gravity of γ = 25kN / m3, cohesion c = 15000kPa, and internal friction angle

[0087] The model is meshed to 1m×1m, and each mesh contains 4 material points in the initial state. The slope is initially in a static state, and the initial stress state of each particle is generated by linear loading gravity to make the calculation more stable. The loading method is as follows Figure 6 At T = 15s, the above 100 earthquake motions are input at the bottom of each slope model, and then the material point method is used to solve the permanent displacement of the slope under the action of local earthquakes, as shown in Figure 7 shown.

[0088] S2. Through the numerical simulation of the material point method, 100 (PGV, D) data pairs can be obtained for each slope model. The least squares method is used to perform linear fitting on the data, and the regression equation is as follows:

[0089] ln(D)=aln(PGV)+b,

[0090] Where D is the permanent displacement of the slope, PGV is the peak ground velocity, and a and b are regression parameters determined by the geometric parameters of the slope itself and the soil strength parameters.

[0091] The regression coefficients a and b corresponding to different slope models and their standard deviations and the correlation coefficient R of the regression equation are shown in Table 2. The range of R is 0.87 to 0.93, indicating that the permanent displacement of the slope has a good linear correlation with the seismic intensity parameter PGV.

[0092] Table 2 Regression equation parameters and standard deviations

[0093]

[0094] Analyzed dimensionless parameters The relationship between the regression coefficients a and b is as follows: Figure 8 and Fig. 9 As shown. With the dimensionless parameter As the value of There is an obvious negative correlation. The linear fitting equation is as follows:

[0095]

[0096]

[0097] Among them, the correlation coefficient of the fitting equation of coefficient a is R = 0.835, and the correlation coefficient of the fitting equation of coefficient b is R = 0.769. Both coefficients are related to the dimensionless parameter There is a strong linear correlation. Therefore, the regression coefficients a and b of the general slope can be solved by linear interpolation.

[0098] S3. Combining the permanent displacement regression equations of the slopes with the same slope angle obtained in S2 to obtain a displacement prediction chart.

[0099] When the slope angle is determined, as the dimensionless parameter As the value of increases, the regression equation curve moves toward the bottom of the chart, such as Fig.10 Therefore, for a general slope, its dimensionless parameters can be calculated by To predict the regression equation parameters a and b, and then obtain the permanent displacement prediction formula and solve the permanent displacement of the slope. In addition, as the slope angle increases, the stability of the slope gradually decreases, and the permanent displacement under the action of the earthquake will gradually increase. Therefore, for slopes with different slope angles, the regression coefficient of the slope with a specific slope angle can also be solved to interpolate and obtain the regression equation coefficient of the general slope.

[0100] like Fig.10 , Fig.11 , Fig.12 As shown, the slopes have three slope angles of 25°, 35° and 45°. For other slopes with slope angles between 25° and 45°, the regression equation coefficients can also be solved by interpolation.

[0101] S4. Solve the permanent displacement of general slopes.

[0102] Specifically, when the slope height is 15m, the slope angle is 45°, and the soil weight γ = 20kN / m 3 , when the soil cohesion is 10 kPa and the internal friction angle is 20°, the dimensionless parameters of the slope are calculated as follows: The range of the slope regression equation parameter a is 0.87-0.96, and the range of b is 0.39-0.69. The regression coefficients a=0.942 and b=0.63 are determined by linear interpolation. The displacement regression equation can be expressed as:

[0103] ln(D)=0.942ln(PGV)+0.63;

[0104] When the slope height is 15m, the slope angle is 34°, the soil weight γ=20.7kN / m3, the soil cohesion is 13.99kPa, and the soil internal friction angle is 25°, calculate the dimensionless parameters of the slope: The linear interpolation method is also used to solve the problem. When , the regression equation of the slope is:

[0105] Slope angle 25°: ln(D)=0.81ln(PGV)+0.28,

[0106] Slope angle 35°: ln(D)=0.85ln(PGV)+0.34,

[0107] The slope angle is 34°. Using linear interpolation, the regression equation is:

[0108] ln(D)=0.844ln(PGV)+0.334,

[0109] For the displacement regression equation obtained by solving it, the permanent displacement of the slope can be directly predicted by inputting the ground motion intensity parameter PGV. It can also be used for slope vulnerability analysis under earthquake action.

[0110] To verify the accuracy and feasibility, the material point method is used to solve the permanent displacement of the example slope 1 under the action of 100 earthquake motions in S1, and 100 sets of (PGV, D) data are obtained. The displacement data are fitted according to S2 to obtain the regression equation:

[0111] ln(D)=0.995ln(PGV)+0.51.

[0112] The regression equation correlation coefficient R obtained by linear fitting 2 =0.8853, the residual sum of squares is 2.26, and the residual sum of squares of the equation obtained by using the graphical method of difference and the displacement data is 2.46.

[0113] like Fig.13 As shown in the figure, the results obtained by interpolation using the graphical method and the results obtained by fitting the displacement data are very similar, and the permanent displacement of the slope under earthquake action can be predicted quickly and accurately.

[0114] It should be noted that in the above embodiment, 18 groups of slopes and 100 earthquake motions are used to construct the earthquake slope permanent displacement prediction chart. If different slope models and earthquake motions are used, the regression equations obtained will also be different. However, only the slopes with three slope angles of 25°, 35° and 45° are calculated and solved, and the resulting displacement chart can only be used to solve the earthquake slope displacement within this slope angle range. The main reason is that for soil slopes, most of their slope angles are within this range, so the results of the embodiment of this application are applicable to most actual engineering situations.

[0115] In summary, the embodiment of the present application applies the graphical method to the dynamic analysis of earthquake landslides, combines easily accessible dimensionless parameters and material point method simulation, and quickly and easily predicts the permanent displacement of the slope under the action of an earthquake, thereby improving the accuracy and practicality of the analysis and providing efficient technical support for slope engineering.

[0116] Next, the earthquake-induced slope displacement prediction device proposed in accordance with the embodiment of the present application is described with reference to the accompanying drawings.

[0117] Fig.14 It is a block diagram of the earthquake-induced slope displacement prediction device of an embodiment of the present application.

[0118] like Fig.14 As shown, the earthquake-induced slope displacement prediction device 10 includes: a setting module 100, a fitting module 200 and a prediction module 300.

[0119] Among them, the setting module 100 is used to set different slope models and determine the target seismic intensity parameters according to the seismic motion records; the fitting module 200 is used to simulate the permanent displacement results of each slope model under seismic motion based on the material point method, and fit the linear regression equation of the slope with the same slope angle according to the slope permanent displacement results; the prediction module 300 is used to generate a slope permanent displacement prediction chart according to the linear regression equation of the slope with the same slope angle, and predict the earthquake-induced slope displacement based on the slope permanent displacement prediction chart.

[0120] It should be noted that the above explanations of the embodiment of the earthquake-induced slope displacement prediction method are also applicable to the earthquake-induced slope displacement prediction device of this embodiment, which will not be repeated here.

[0121] According to the earthquake-induced slope displacement prediction device proposed in the embodiment of the present application, by setting a variety of slope models and combining the actual seismic records to determine the target seismic intensity parameters, the prediction accuracy of the permanent displacement of the slope is significantly improved. By using the advanced material point method for numerical simulation, the permanent displacement data of each slope model under the action of the earthquake is obtained, and the linear regression equation applicable to the slope with the same slope angle is fitted accordingly, so that the prediction result is closer to the actual situation. In addition, by generating a slope permanent displacement prediction chart, the prediction process is simplified, and the slope displacement prediction can be carried out conveniently without complex numerical simulation calculations. As a result, the problems of simplified solution methods, limited accuracy, complex numerical simulation, strong dependence, and lack of unified standards in the prior art are solved.

[0122] Fig.15 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0123] A memory 1501 , a processor 1502 , and a computer program stored in the memory 1501 and executable on the processor 1502 .

[0124] When the processor 1502 executes the program, the earthquake-induced slope displacement prediction method provided in the above embodiment is implemented.

[0125] Furthermore, the electronic device further comprises:

[0126] The communication interface 1503 is used for communication between the memory 1501 and the processor 1502 .

[0127] The memory 1501 is used to store computer programs that can be executed on the processor 1502 .

[0128] The memory 1501 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0129] If the memory 1501, the processor 1502 and the communication interface 1503 are implemented independently, the communication interface 1503, the memory 1501 and the processor 1502 can be connected to each other through a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.15 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0130] Optionally, in a specific implementation, if the memory 1501, the processor 1502 and the communication interface 1503 are integrated on a chip, the memory 1501, the processor 1502 and the communication interface 1503 can communicate with each other through an internal interface.

[0131] The processor 1502 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0132] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above earthquake-induced slope displacement prediction method.

[0133] The embodiment of the present application also provides a computer program product, including a computer program or instructions, which, when executed, are used to implement the above earthquake-induced slope displacement prediction method.

[0134] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0135] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0136] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0137] It should be understood that the various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, the steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0138] A person of ordinary skill in the art may understand that all or part of the steps carried by the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the above-mentioned program may be stored in a computer-readable storage medium, which, when executed, includes one of the steps of the method embodiment or a combination thereof.

[0139] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for predicting earthquake-induced slope displacement, characterized in that: The following steps are involved: Set different slope models and determine the target ground motion intensity parameters based on ground motion records; Based on the material point method, the permanent displacement results of each slope model under earthquake motion are simulated, and the linear regression equation of the slope with the same slope angle is fitted according to the permanent displacement results of the slope. A slope permanent displacement prediction chart is generated according to the linear regression equation of the slopes with the same slope angle, and the earthquake-induced slope displacement is predicted based on the slope permanent displacement prediction chart.

2. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that: The linear regression equation is: ln(D)=aln(PGV)+b, Where D is the permanent displacement of the slope, PGV is the peak ground velocity, and a and b are regression parameters.

3. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that: The method of generating a slope permanent displacement prediction chart according to the linear regression equation of the slopes having the same slope angle comprises: Analyze the relationship between the regression coefficient of the linear regression equation and the slope soil strength parameter; A dimensionless parameter for determining the performance of the slope itself is constructed, and a permanent displacement prediction chart of the slope is generated according to the relationship between the dimensionless parameter and the regression coefficient and the slope soil strength parameter.

4. The earthquake-induced slope displacement prediction method according to claim 3, characterized in that: The relationship between the regression coefficient and the slope soil strength parameters includes: soil cohesion and soil internal friction angle are negatively correlated with the slope permanent displacement, and soil weight and slope height are positively correlated with the slope permanent displacement.

5. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that: The method of predicting earthquake-induced slope displacement based on the slope permanent displacement prediction chart comprises: Calculate dimensionless parameters based on the geometric parameters and strength parameters of the example slope; The slope displacement regression equation coefficients of the example slope are obtained by linear interpolation; Based on the calculated dimensionless parameters, slope displacement regression equation coefficients and the slope permanent displacement prediction chart, the earthquake-induced slope displacement under different ground motions is solved.

6. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that: Before determining the target earthquake intensity parameter according to the earthquake record, it also includes: Obtaining earthquake motion database; Determine the seismic hazard curve of the slope site based on probabilistic seismic hazard analysis; A seismic record is selected from the seismic database according to the seismic hazard curve.

7. An earthquake-induced slope displacement prediction device, characterized in that: include: A setting module, used to set different slope models and determine target ground motion intensity parameters according to ground motion records; A fitting module is used to simulate the permanent displacement results of each slope model under earthquake motion based on the material point method, and to fit the linear regression equation of the slope with the same slope angle according to the permanent displacement results of the slope; The prediction module is used to generate a slope permanent displacement prediction chart according to the linear regression equation of the slopes with the same slope angle, and predict the earthquake-induced slope displacement based on the slope permanent displacement prediction chart.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the earthquake-induced slope displacement prediction method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed, the earthquake-induced slope displacement prediction method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed, the earthquake-induced slope displacement prediction method according to any one of claims 1 to 6 is implemented.

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