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

Abstract

The application relates to the technical field of slope sliding, in particular to a method and device for predicting earthquake-induced slope displacement, equipment, medium and products, wherein the method comprises the following steps: setting different slope models, determining target seismic intensity parameters according to seismic records; obtaining the permanent displacement results of each slope model under seismic motion based on the material point method; fitting a linear regression equation of the slope with the same slope angle according to the permanent displacement results of the slope; generating a permanent displacement prediction chart of the slope according to the linear regression equation of the slope with the same slope angle; and predicting the earthquake-induced slope displacement based on the permanent displacement prediction chart of the slope. Thus, the problems of the prior art, such as the simplified solving method, the limited precision, the complex numerical simulation, the strong dependence and the lack of unified standards, are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of slope sliding, and in particular relates to a method and device for predicting slope displacement induced by an earthquake, equipment, media and products. BACKGROUND

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

[0003] At present, the commonly used solving methods mainly include Newmark sliding block method and numerical simulation method. The Newmark sliding block method is simple in concept and easy to calculate, and has been widely used in the seismic design of slope engineering, but contains simplified assumptions, which may not fully reflect the real response of the slope. The numerical simulation method can consider more influencing factors and provide higher precision displacement prediction, but the calculation process is complex and has high dependence on the model. SUMMARY

[0004] The present application provides a method and device for predicting slope displacement induced by an earthquake, equipment, media and products to solve the problems of simplified solving method, limited precision, complex numerical simulation, strong dependence and lack of unified standard in the prior art.

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

[0006] Optionally, the linear regression equation is:

[0007] ,

[0008] wherein 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 and soil strength parameters of the slope.

[0009] Optionally, the generating the slope permanent displacement prediction chart according to the linear regression equation of the slopes with the same slope angle comprises: 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, and generating the slope permanent displacement prediction chart according to 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 comprises: the soil cohesion and the soil internal friction angle are negatively correlated with the slope permanent displacement, and the soil bulk density and the slope height are positively correlated with the slope permanent displacement.

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

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

[0013] The second aspect embodiment of the present application provides a slope displacement prediction device for predicting earthquake-induced slope displacement, comprising: a setting module configured to set different slope models and determine a target ground motion intensity parameter according to a ground motion record; a fitting module configured to simulate the permanent displacement of each slope model under ground motion based on a material point method, and fit a linear regression equation of slopes with the same slope angle according to the permanent displacement of the slope; and a prediction module configured 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.

[0014] The third aspect embodiment 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 method for predicting earthquake-induced slope displacement as described in the above embodiments.

[0015] The fourth aspect embodiment of the present application provides a computer readable storage medium having a computer program stored thereon, wherein the program is executable by a processor to implement the method for predicting earthquake-induced slope displacement as described in the above embodiments.

[0016] The fifth aspect embodiment of the present application provides a computer program product comprising computer programs or instructions, which, when executed, implement the method for predicting the displacement of a slope induced by an earthquake as described above.

[0017] Thus, the present application includes the following beneficial effects:

[0018] The embodiments of the present application set up diversified slope models, and determine target seismic intensity parameters in combination with actual seismic records, thereby significantly improving the prediction accuracy of the permanent displacement of the slope. 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 according to the data, 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 conveniently performed without complex numerical simulation calculation. Thus, the technical problems such as simplified solution method, limited accuracy, complex numerical simulation, strong dependence, and lack of unified standard in the prior art are solved.

[0019] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0020] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings, wherein:

[0021] Figure 1 A flowchart of a method for predicting the displacement of a slope induced by an earthquake according to an embodiment of the present application is provided.

[0022] Figure 2 A flowchart of a method for predicting the displacement of a slope induced by an earthquake according to an embodiment of the present application is provided.

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

[0024] Figure 4 A schematic diagram of the matrix level of seismic motion according to an embodiment of the present application is provided.

[0025] Figure 5 A schematic diagram of the established slope model according to an embodiment of the present application is provided.

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

[0027] Figure 7 A schematic diagram of the permanent displacement result of the slope according to an embodiment of the present application is provided.

[0028] Figure 8 a relationship diagram between regression coefficient a and dimensionless parameter ctan φ / γH provided according to an embodiment of the present application;

[0029] Figure 9 a relationship diagram between regression coefficient b and dimensionless parameter ctan φ / γH provided according to an embodiment of the present application;

[0030] Figure 10 a schematic diagram for solving slope displacement of a slope with a gradient of 25° provided according to an embodiment of the present application;

[0031] Figure 11 a schematic diagram for solving slope displacement of a slope with a gradient of 35° provided according to an embodiment of the present application;

[0032] Figure 12 a schematic diagram for solving slope displacement of a slope with a gradient of 45° provided according to an embodiment of the present application;

[0033] Figure 13 a comparison diagram between a result obtained by interpolation according to a chart method and a result obtained by fitting displacement data provided according to an embodiment of the present application;

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

[0035] Figure 15 a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

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

[0038] Currently, there are two main methods for solving the permanent displacement of a seismic slope: the Newmark sliding block method and the numerical simulation method. The Newmark sliding block method estimates the permanent displacement by twice integrating the part of the seismic acceleration-time history that exceeds the landslide threshold. The results of this method have been proven to be able to better reflect the seismic performance of the slope, and therefore it has been widely applied. However, this method is based on a series of simplifying assumptions, which may not fully reflect the true response of the slope. In order to more accurately solve the permanent displacement, numerical simulation methods can be tried. For example, Fotopoulou and Pitilakis used FLAC2D software to calculate the effects of 40 seismic 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 the finite element method and the finite difference method can also be used to establish a prediction model for the permanent displacement of a slope. However, the accuracy of these models is limited by the number of slope models and seismic motions used, and the model form is relatively complex, which is not convenient for direct application.

[0039] The seismic-induced slope displacement prediction method, device, equipment, medium and product provided by the embodiments of the present application are described below with reference to the accompanying drawings. In view of the inaccurate prediction results mentioned in the background art, the present application provides a seismic-induced slope displacement prediction method, in which a variety of slope models are set up, and the target seismic intensity parameters are determined in combination with actual seismic records, which significantly improves the prediction accuracy of the permanent displacement of the slope. Advanced material point method is used for numerical simulation to obtain the permanent displacement data of each slope model under the action of earthquakes, and a linear regression equation suitable for slopes with the same slope angle is fitted accordingly, 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 conveniently performed without complex numerical simulation calculations. Thus, the problems of simplified solution method, limited precision, complex numerical simulation, strong dependence, lack of unified standard, etc. in the prior art are solved.

[0040] Specifically, Figure 1 The flowchart of the seismic-induced slope displacement prediction method provided by the embodiments of the present application is shown in the following figure.

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

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

[0043] The slope model refers to a mathematical model or a physical model established for studying and analyzing behaviors of a slope under specific conditions, and the seismic motion record refers to ground motion data recorded by a seismograph or the like when an earthquake occurs. The target seismic intensity parameter can include a magnitude, an intensity, a peak acceleration, and the like of an earthquake.

[0044] It can be understood that, by setting diversified slope models and combining with actual seismic motion records to determine the target seismic intensity parameter, the embodiments of the present application can help to discover slope instability risks in a timely manner, improve engineering safety, and provide strong support for scientific research on slope stability.

[0045] It should be noted that the slope model parameters can include a slope height, a slope angle, a soil bulk density, a soil cohesion, a soil internal friction angle, a Poisson's ratio, and an elastic modulus. The Poisson's ratio and the elastic modulus of a homogeneous soil slope have little effect on the stability of the slope itself. Therefore, the Poisson's ratio and the elastic modulus are kept constant when the slope model is set.

[0046] In the embodiments of the present application, before the target seismic intensity parameter is determined according to the seismic motion record, the method further includes: obtaining a seismic motion database; determining a seismic hazard curve of a site where the slope is located based on a probabilistic seismic hazard analysis; and selecting the seismic motion record from the seismic motion database according to the seismic hazard curve.

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

[0048] It can be understood that, by obtaining the seismic motion database, the embodiments of the present application provide rich data sources 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 can suffer in the future and the probability distribution thereof, and provide a quantitative basis for seismic design and seismic risk assessment. The seismic motion record is selected from the seismic motion database according to the seismic hazard curve, which can ensure that the selected record matches the seismic hazard of the site where the slope is located, and improve the accuracy and reliability of simulation and prediction.

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

[0050]

[0051] The v(t) is a seismic motion velocity time history.

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

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

[0054] It can be understood that the embodiments of the present application use the advanced material point method to effectively simulate the dynamic response and permanent displacement of the slope under the earthquake, and provide 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 slope stability and repair needs after the earthquake. At the same time, the analysis of the simulation results reveals the relationship between the slope response and the seismic motion parameters, which provides a theoretical basis for the seismic design of the slope. Finally, based on the permanent displacement results, a linear regression equation is fitted 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 solving under the action of the earthquake. The material point method uses Lagrangian particles and Eulerian grid double description, which discretizes the continuum into particles carrying regional material information, and the grid nodes do not store any information, and are only used for solving calculation. At the end of each time step, the deformed grid is discarded, and a new grid system is used to solve the next time step. Based on the updated Lagrangian format, the control equation form of the continuum mass conservation, momentum conservation and solving equation is as follows:

[0056]

[0057] wherein, is the medium density, is the velocity, is the Cauchy stress, is the unit mass force acting on the object, is the acceleration.

[0058] Compared with other traditional numerical simulation methods, the material point method can effectively avoid the grid distortion problem. In addition, in order to simulate the deformation process of the slope under the action of the earthquake, the original material point open source code is improved, and free field boundaries are added on both sides of the model, and seismic motion input boundaries and absorption boundaries are added at the bottom of the model.

[0059] In the embodiments of the present application, the linear regression equation is:

[0060] ,

[0061] Wherein, D is the permanent displacement of the slope, PGV is the peak ground velocity, a and b are regression parameters determined by the geometric parameters and the strength parameters of the soil of the slope.

[0062] Specifically, for each determined slope model, the least square method is used to fit the obtained permanent displacement of the slope to obtain a linear regression equation, which is specifically shown as follows:

[0063] ,

[0064] Wherein, D is the permanent displacement of the slope, IM is the ground motion intensity parameter, a and b are regression parameters determined by the geometric parameters and the strength parameters of the soil of the slope;

[0065] Since the ground motion intensity parameter selected in the embodiment of the present application is the peak ground velocity, the linear regression equation is:

[0066] .

[0067] In step S103, a slope permanent displacement prediction chart is generated according to the linear regression equations of the slopes with the same slope angle, and the earthquake-induced slope displacement is predicted based on the slope permanent displacement prediction chart.

[0068] It can be understood that the embodiment of the present application uses the linear regression equations of the slopes with the same slope angle previously established to generate the slope permanent displacement prediction chart, which provides an intuitive and efficient tool for predicting the earthquake-induced slope displacement, helps to accurately evaluate the stability of the slope under the action of the earthquake, and can quickly understand the permanent displacement of the slope under different ground motion intensities.

[0069] In the embodiment of the present application, the slope permanent displacement prediction chart is generated according to the linear regression equations of the slopes with the same slope angle, which includes: analyzing the relationship between the regression coefficients of the linear regression equations and the strength parameters of the soil of the slope; constructing a dimensionless parameter for determining the performance of the slope, and generating the slope permanent displacement prediction chart according to the relationship between the dimensionless parameter and the regression coefficients and the strength parameters of the soil of the slope.

[0070] Wherein, the strength parameters of the soil of the slope can be the shear resistance, compressive resistance and other mechanical properties of the soil, and the dimensionless parameter can be a parameter independent of specific units, which is used for unified comparison and analysis of the same object under different conditions.

[0071] It can be understood that the embodiment of the present application constructs the dimensionless parameter for determining the performance of the slope by deeply analyzing the internal relationship between the regression coefficients of the linear regression equations and the strength parameters of the soil of the slope, and generates the slope permanent displacement prediction chart based on these key parameters, which can deeply understand the response behavior of the slope under the action of external loads such as earthquakes, and improves the prediction accuracy of the permanent displacement of the slope.

[0072] Specifically, a dimensionless constant is constructed ctan φ / γH to characterize the performance of the slope itself, ctan φ / γH The greater the value, the stronger the stability of the slope itself. For this dimensionless parameter, there are two requirements: one is to include the geometric parameters and strength parameters of the slope, and the other is to have good correlation with the regression equation coefficients a and b, so as to solve the regression coefficients of the general slope through the parameter.

[0073] It should be noted that the above dimensionless parameter ctan φ / γH does not involve the slope angle, and the slope angle has a significant impact on the calculation of the permanent displacement of the slope under earthquake.

[0074] In the embodiments of the present application, the relationship between the regression coefficient and the strength parameter of the slope soil body includes that the cohesion of the soil body and the internal friction angle of the soil body are negatively correlated with the permanent displacement of the slope, and the specific gravity of the soil body and the slope height are positively correlated with the permanent displacement of the slope.

[0075] In the embodiments of the present application, the slope displacement induced by earthquake is predicted based on the slope permanent displacement prediction chart, including: calculating the dimensionless parameter according to the geometric parameters and strength parameters of the example slope; obtaining the slope displacement regression equation coefficient of the example slope by using linear interpolation; and solving the slope displacement induced by earthquake under different seismic motions based on the calculated dimensionless parameter, slope displacement regression equation coefficient and slope permanent displacement prediction chart.

[0076] It can be understood that the embodiments of the present application standardize the characteristics of the slope by calculating the dimensionless parameter, estimate the slope displacement regression equation coefficient based on historical or experimental data by using linear interpolation technology, and combine these parameters, coefficients and slope permanent displacement prediction chart to solve and predict the possible displacement of the slope under different seismic motions. The differences between different slopes can be eliminated, the prediction accuracy can be improved, and the stability of the slope can be scientifically evaluated.

[0077] According to the slope displacement prediction method induced by earthquake proposed in the embodiments of the present application, by setting diversified slope models and combining with actual seismic motion records to determine the target seismic intensity parameter, the prediction accuracy of the permanent displacement of the slope is significantly improved. Advanced material point method is used for numerical simulation to obtain the permanent displacement data of each slope model under the action of earthquake, and a linear regression equation suitable for slopes with the same slope angle is fitted according to the data, so that the prediction result is closer to the actual situation. In addition, by generating the slope permanent displacement prediction chart, the prediction process is simplified, and the slope displacement prediction can be conveniently performed without complex numerical simulation calculation. Thus, the problems of simplified solving method, limited precision, complex numerical simulation, strong dependence and lack of unified standard in the prior art are solved.

[0078] The specific implementation of the present application will be described below. Figure 2The method for predicting the displacement of a slope induced by an earthquake is described in detail as follows:

[0079] S1, setting a slope model, selecting appropriate ground motion, establishing a slope model in the material point method and simulating the deformation process of the slope under the action of an earthquake, and calculating the permanent displacement.

[0080] Specifically, 18 sets of slope models are set, the slope angle of the slope model is set to 25°, 35° and 45°, the slope height is set to 15m and 25m, the elastic modulus is 100MPa, and the Poisson's ratio is 0.4. For slopes with different slope angles, 6 slope models are set, and the dimensionless constant is 0.05, 0.1, 0.2, 0.4, 0.6 and 0.8, respectively. Among them, the specific gravity, cohesion and internal friction angle of the slope soil are shown in Table 1.

[0081] Table 1 Slope model parameters

[0082]

[0083] For a site, 100 ground motion data are selected from the global ground motion database NGA-West2 according to the results of the probabilistic seismic hazard analysis, the response spectrum acceleration of the ground motion is as shown in Figure 3 , and the matrix level is as shown in Figure 4 .

[0084] The slope model established in the material point method is as shown in Figure 5 . The toe of the slope is 100m away from the left boundary of the model, and 50m away from the right boundary of the model, and the height of the bottom of the slope is twice the slope height, which can reduce the reflection of seismic waves from the boundary of the slope. The slope is divided into two layers, the bottom rock is set as an elastic material, the specific gravity γ=25kN / m3, the cohesion c=15000kPa, and the internal friction angle φ=45°.

[0085] The model is meshed with a grid of 1m x 1m, and each grid contains 4 material points in the initial state. The slope is initially in a static state, and a linear loading gravity method is used to generate the initial stress state of each particle, which makes the calculation more stable, and the loading method is as shown in Figure 6 . At T=15s, the above 100 ground motions are input at the bottom of each slope model, and then the permanent displacement of the slope under the action of each ground motion is obtained by solving the material point method, as shown in Figure 7 .

[0086] S2, through numerical simulation by the material point method, 100 (PGV, D) data pairs can be obtained for each slope model, and the least squares method is used to linearly fit the data, and the regression equation is as follows:

[0087] ,

[0088] where D is the permanent displacement of slope, PGV is the peak ground velocity, and a and b are regression parameters determined by the geometric parameters and strength parameters of the slope.

[0089] where the regression coefficients a and b and their standard deviations and the correlation coefficient R of the regression equation for different slope models are shown in Table 2. The range of R is 0.87-0.93, indicating that the permanent displacement of the slope has a good linear correlation with the ground motion intensity parameter PGV.

[0090] Table 2 Regression equation parameters and standard deviations

[0091]

[0092] The relationship between the dimensionless parameter ctan φ / γH and the regression coefficients a and b is analyzed, as shown in Figure 8 and Figure 9 As the dimensionless parameter ctan φ / γH increases, the regression coefficients a and b gradually decrease, and the coefficients a and b have a clear negative correlation with ctan φ / γH The linear fitting equations of the coefficients a and b and the dimensionless parameter ctan φ / γH are as follows:

[0093] ,

[0094] ,

[0095] where the correlation coefficient R of the fitting equation of the coefficient a is 0.835, the correlation coefficient R of the fitting equation of the coefficient b is 0.769, and both coefficients have a strong linear correlation with the dimensionless parameter ctan φ / γH Therefore, the linear interpolation method can be used to solve the regression coefficients a and b of a general slope.

[0096] S3, combining the permanent displacement regression equations of slopes with the same slope angle obtained in S2 to obtain a displacement prediction chart.

[0097] When the slope angle is determined, as the dimensionless parameter ctan φ / γH increases, the regression equation curve moves towards the lower part of the chart, as shown in Figure 10 Therefore, for a general slope, the regression equation parameters a and b can be predicted by calculating the dimensionless parameter ctan φ / γH of the slope, and then the permanent displacement prediction formula is obtained to 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 also gradually increases. Therefore, for slopes with different slope angles, the regression coefficients of specific slope angles can also be solved to interpolate the regression equation coefficients of a general slope.

[0098] AsFigure 10 , Figure 11 , Figure 12 As shown, slopes with angles of 25°, 35°, and 45° are represented. For other slopes with angles between 25° and 45°, the coefficients of the regression equation can be solved by interpolation.

[0099] S4. Solve for the permanent displacement of a general slope.

[0100] 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 of the soil is 20°, the dimensionless parameters of the slope are calculated as follows: ctan φ / γH = 0.012, the range of parameter a in the slope regression equation is 0.87~0.96, and the range of b is 0.39~0.69. Using linear interpolation, the regression coefficients are determined to be a = 0.942 and b = 0.63. The displacement regression equation can be expressed as:

[0101] ;

[0102] Calculate the dimensionless parameters of the slope 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°. ctan φ / γH = 0.021, also solved using linear interpolation, when ctan φ / γH When = 0.021, the regression equation for the slope is:

[0103] 25° slope angle: ,

[0104] 35° slope angle: ,

[0105] The slope angle is 34°. Using linear interpolation, the regression equation can be obtained as follows:

[0106] ,

[0107] The obtained displacement regression equation can be directly predicted by inputting the seismic intensity parameter PGV, and can also be used for slope vulnerability analysis under seismic loading.

[0108] To verify accuracy and feasibility, the material point method was used to solve for the permanent displacement of slope 1 in the example under 100 seismic motions in S1, obtaining 100 sets of (PGV, D) data. Fitting the displacement data to S2 yielded the regression equation:

[0109] .

[0110] The correlation coefficient R of the regression equation obtained by linear fitting is 0.8853, and the residual sum of squares is 2.26. The residual sum of squares of the equation obtained by using the chart method and the displacement data is 2.46. 2 =0.8853, and the residual sum of squares is 2.26. The residual sum of squares of the equation obtained by using the chart method and the displacement data is 2.46.

[0111] As shown in the following table, the results obtained by using the chart method and the results obtained by fitting the displacement data can be found to be very close, and the permanent displacement of the slope under the action of the earthquake can be quickly and accurately predicted. Figure 13

[0112] It should be noted that in the above embodiment, 18 groups of slopes and 100 seismic waves are used to construct the seismic slope permanent displacement prediction chart. If different slope models and seismic waves are used, the regression equation obtained will be different. Moreover, only the slopes with slope angles of 25°, 35° and 45° are calculated and solved, and the displacement chart obtained can only be used for the displacement solution of the seismic slope in this slope angle range. The main reason is that for soil slopes, most of the slope angles are within this range, so the results of the present application are applicable to most engineering practical situations.

[0113] In summary, the chart method is applied to the dynamic analysis of the earthquake-induced landslide in the present application, and the dimensionless parameter and the material point method simulation are combined to quickly and simply predict the permanent displacement of the slope under the action of the earthquake, thereby improving the accuracy and practicality of the analysis and providing efficient technical support for slope engineering.

[0114] Secondly, the earthquake-induced slope displacement prediction device according to the present application is described with reference to the accompanying drawings.

[0115] Figure 14 is a block schematic diagram of the earthquake-induced slope displacement prediction device according to the present application.

[0116] As shown in the following table, the results obtained by using the chart method and the results obtained by fitting the displacement data can be found to be very close, and the permanent displacement of the slope under the action of the earthquake can be quickly and accurately predicted. Figure 14

[0117] The setting module 100 is configured to set different slope models and determine the target seismic intensity parameter according to the seismic wave record. The fitting module 200 is configured to simulate the permanent displacement of each slope model under the action of the seismic wave based on the material point method, and fit a linear regression equation of the slope with the same slope angle according to the permanent displacement of the slope. The prediction module 300 is configured 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.

[0118] It should be noted that the foregoing explanation and description of the earthquake-induced slope displacement prediction method embodiment are also applicable to the earthquake-induced slope displacement prediction device of the present application, and will not be described here again.​​

[0119] The device for predicting slope displacement induced by earthquake according to the embodiment of the application, by setting diversified slope models and combining with actual seismic motion records to determine target seismic motion intensity parameters, significantly improves the prediction accuracy of slope permanent displacement. Advanced material point method is used for numerical simulation to obtain permanent displacement data of each slope model under the action of earthquake, and a linear regression equation suitable for slopes with the same slope angle is fitted according to the data, 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 can be conveniently predicted without complex numerical simulation calculation. Thus, the problems of simplified solution method, limited precision, complex numerical simulation, strong dependence and lack of unified standard in the prior art are solved.

[0120] Figure 15 The structural schematic diagram of the electronic device provided by the embodiment of the application is provided. The electronic device can include:

[0121] The memory 1501, the processor 1502 and the computer program stored in the memory 1501 and executable on the processor 1502.

[0122] The processor 1502 implements the method for predicting slope displacement induced by earthquake provided in the above embodiment when executing the program.

[0123] Further, the electronic device further includes:

[0124] The communication interface 1503 is used for communication between the memory 1501 and the processor 1502.

[0125] The memory 1501 is used to store the computer program executable on the processor 1502.

[0126] The memory 1501 can include a high-speed RAM (Random Access Memory, random access memory) memory, and can also include a non-volatile memory, for example, at least one disk memory.

[0127] 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 complete communication between each other. The bus can be an ISA (Industry Standard Architecture, Industry Standard Architecture) bus, a PCI (Peripheral Component, Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture, Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 15 Only one thick line is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0128] 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 complete communication between each other through an internal interface.

[0129] The processor 1502 can be a CPU (Central Processing Unit, Central Processing Unit) or an ASIC (Application Specific Integrated Circuit, Application Specific Integrated Circuit) or one or more integrated circuits configured to implement one or more embodiments of the present application.

[0130] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the above-mentioned method for predicting displacement of a slope induced by an earthquake.

[0131] The embodiments of the present application also provide a computer program product, which includes a computer program or instructions, and the computer program or instructions are executed to implement the above-mentioned method for predicting displacement of a slope induced by an earthquake.

[0132] In the description of the application, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the application. In the description of the application, the illustrative description of the above terms is not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or N embodiments or examples. In addition, different embodiments or examples described in the description of the application and the features of different embodiments or examples can be combined and combined by those skilled in the art without contradiction.

[0133] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the application, the meaning of "N" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0134] Any process or method descriptions in flow charts or otherwise described herein can be understood as representing code modules, segments, or portions of code that include one or more executable instructions for implementing specific logic functions (or steps) in the process, and that the various embodiments of the application can include additional or fewer steps or processes in alternative implementations, as will be appreciated by those skilled in the art. The various embodiments of the application can be implemented in hardware, software, firmware, or a combination thereof, as desired.

[0135] It should be understood that parts of the application can be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. As in another embodiment implemented in hardware, any one or a combination of the following technologies known in the art can be used: discrete logic circuit with logic gate circuit for implementing logic functions on data signals, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array, field programmable gate array, etc.

[0136] Those skilled in the art of the art can understand that the method of implementing the above-mentioned embodiments carries out all or part of the steps. The above-mentioned program can be stored in a computer readable storage medium, which includes one or a combination of the steps of the method embodiment when executed.

[0137] Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary, and are not to be interpreted as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A method for predicting earthquake-induced slope displacement, characterized in that, Includes the following steps: Set up different slope models and determine the target ground motion intensity parameters based on ground motion records; The permanent displacement results of each slope model under seismic motion were obtained by simulating the material point method. Based on the permanent displacement results, a linear regression equation for slopes with the same slope angle was obtained by fitting. A permanent slope displacement prediction chart is generated based on the linear regression equation of slopes with the same slope angle, wherein the permanent slope displacement prediction chart is a curve of the linear regression equation of slopes with the same slope angle but different dimensionless parameters; earthquake-induced slope displacement is predicted based on the permanent slope displacement prediction chart, including calculating the target dimensionless parameter, determining the regression coefficient based on the target dimensionless parameter, determining the target linear regression equation based on the regression coefficient and the permanent slope displacement prediction chart, inputting the target ground motion intensity parameter into the target linear regression equation, and predicting earthquake-induced slope displacement.

2. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that, The linear regression equation is as follows: ， 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 step of generating a permanent displacement prediction chart for slopes based on the linear regression equation of the slopes with the same slope angle includes: Analyze the relationship between the regression coefficients of the linear regression equation and the slope soil strength parameters; Dimensionless parameters for determining the performance of the slope itself are constructed, and the permanent displacement prediction chart of the slope is generated based on the relationship between the dimensionless parameters, regression coefficients and slope soil strength parameters.

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

5. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that, The prediction of earthquake-induced slope displacement based on the slope permanent displacement prediction chart includes: Calculate the dimensionless parameters based on the geometric and strength parameters of the slope in the example; The coefficients of the slope displacement regression equation for the example slope are obtained using 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 obtained.

6. The earthquake-induced slope displacement prediction method according to claim 1, characterized in that, Before determining the target ground motion intensity parameters based on ground motion records, the following steps are also included: Obtain the seismic motion database; The seismic hazard curve of the site where the slope is located is determined based on probabilistic seismic hazard analysis; Earthquake motion records are selected from the earthquake motion database based on the earthquake hazard curve.

7. A device for predicting earthquake-induced slope displacement, characterized in that, include: The setup module is used to set up different slope models and determine the target ground motion intensity parameters based on ground motion records. The fitting module is used to simulate the permanent displacement results of each slope model under seismic motion based on the material point method, and to fit the linear regression equation of the slope with the same slope angle based on the permanent displacement results. The prediction module is used to generate a slope permanent displacement prediction chart based on the linear regression equation of slopes with the same slope angle, wherein the slope permanent displacement prediction chart is a curve of the linear regression equation of slopes with the same slope angle but different dimensionless parameters; predicting earthquake-induced slope displacement based on the slope permanent displacement prediction chart includes calculating the target dimensionless parameter, determining the regression coefficient based on the target dimensionless parameter, determining the target linear regression equation based on the regression coefficient and the slope permanent displacement prediction chart, inputting the target ground motion intensity parameter into the target linear regression equation, and predicting earthquake-induced slope displacement.

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, the processor executing the program to implement the earthquake-induced slope displacement prediction method according to any one of claims 1-6.

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

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

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