Slope numerical model establishment method, device, equipment and medium

Abstract

The application discloses a kind of establishment method, device, equipment and medium of slope numerical model.For the problem of complex lithology of open-pit mine slope, multiple failure modes, by presetting shear and tensile yield criterion and defining judgment logic, a constitutive model considering shear and tensile composite failure mode is constructed by using secondary development interface, which makes up for the deficiency of traditional model considering only shear yield.Then, small-scale verification is carried out using core test data to ensure the accuracy of the model at the material level.Furthermore, the numerical model of engineering scale is compared and verified combined with the field monitoring data, which overcomes the defects of existing technology lacking engineering scale verification and large deviation between simulation results and measured values.Through multi-level verification and calibration, the fit and prediction reliability of slope numerical simulation are significantly improved, so that the final obtained numerical model can truly reflect the mechanical response of the target slope area, and provide accurate and reliable model basis for open-pit mine slope stability analysis.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology, and in particular to a method, apparatus, equipment and medium for establishing a numerical model of a slope. Background Technology

[0002] Numerical analysis is a commonly used method in mine slope stability analysis. Its core lies in embedding the constitutive model into finite element software to establish a slope numerical model, thereby simulating the stress field, displacement field and strain response of the slope under its own weight and mining conditions, and then evaluating the stability state of the slope.

[0003] Currently, constitutive models used in numerical analysis are mainly divided into two categories: empirical models and theoretical models. Empirical models include power-law models and exponential models, which are simple in form and easy to apply in engineering, but their physical meaning is not clear enough to reveal the deformation mechanism of rock and soil in essence. Theoretical models include viscoelastic models and viscoelastic-plastic models, which have clear physical meaning and can better describe the complex deformation behavior of rock and soil. However, due to differences in lithology, regional tectonics, hydrogeology, climate conditions, mining conditions, etc., open-pit mine slopes often exhibit significant regional complexity. Even when using theoretical models, general constitutive models are difficult to accurately simulate the slope mechanical response under specific geological and mining conditions. This results in the constructed numerical model parameters lacking regional specificity and failing to simultaneously account for the combined failure mode of shear yielding and tensile yielding. Consequently, the simulation results deviate significantly from the field measured values, reducing the credibility of slope stability analysis and instability prediction based on simulation results and making it difficult to effectively guide safe production in open-pit mines. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, equipment and medium for establishing a numerical model of a slope, in order to solve the technical problems of poor regional specificity and large deviation of simulation results in the numerical model established by the existing constitutive model.

[0005] Firstly, a method for establishing a numerical model of a slope is provided, which includes: Acquire rock physical and mechanical parameters, core test data, and field monitoring data at multiple preset monitoring locations within the target slope area; Based on the preset shear yield criterion, preset tensile yield criterion, and preset judgment logic, a constitutive model is established through the secondary development application programming interface of the finite element analysis software platform. The physical and mechanical parameters of the rock mass are assigned to the constitutive model, and the assigned constitutive model is verified based on core test data. Based on the validated constitutive model, a finite element numerical model of the target slope region is established. The finite element numerical model is simulated, and the simulation results are compared and verified with the field monitoring data to obtain the verified finite element numerical model.

[0006] Secondly, a device for establishing a numerical model of a slope is provided, the device comprising: The acquisition module is used to acquire the rock physical and mechanical parameters of the target slope area, rock core test data, and field monitoring data of multiple preset monitoring locations within the target slope area; The first module is used to establish a constitutive model based on preset shear yield criteria, preset tensile yield criteria and preset judgment logic, through the secondary development application programming interface of the finite element analysis software platform. The first verification module is used to assign rock mass physical and mechanical parameters to the constitutive model and verify the assigned constitutive model based on core test data. The second module is used to establish a finite element numerical model of the target slope region based on the validated constitutive model. The second verification module is used to simulate the finite element numerical model, compare the simulation results with the field monitoring data, and obtain the verified finite element numerical model.

[0007] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned method for establishing a slope numerical model.

[0008] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the steps of the above-described method for establishing a slope numerical model.

[0009] In the aforementioned scheme for establishing numerical slope models, including methods, devices, equipment, and media, this application addresses the challenges of complex lithology and diverse failure modes in open-pit mine slopes. By pre-setting shear and tensile yield criteria and defining judgment logic, a constitutive model capable of simultaneously considering both shear and tensile combined failure modes is constructed using a secondary development interface, overcoming the shortcomings of traditional models that only consider shear yield. Subsequently, small-scale verification using core test data ensures the model's accuracy at the material level. Furthermore, comparative verification of the engineering-scale numerical model is conducted using field monitoring data, overcoming the shortcomings of existing technologies that lack engineering-scale verification and exhibit large deviations between simulation results and measured values. Through multi-level verification and calibration, the fit and predictive reliability of the slope numerical simulation are significantly improved, enabling the final numerical model to truly reflect the mechanical response of the target slope area, providing an accurate and reliable model foundation for open-pit mine slope stability analysis and instability early warning. Attached Figure Description

[0010] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a flowchart illustrating the method for establishing a slope numerical model in one embodiment of the present invention; Figure 2 This is a schematic diagram of the simulated slope displacement results after assigning values ​​to the physical and mechanical parameters calibrated by the experiment in one embodiment of the present invention; Figure 3 This is a schematic diagram showing the comparison between simulation results and on-site monitoring data in one embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a slope numerical model establishment device in one embodiment of the present invention. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in the present invention are only for illustrative and descriptive purposes and are not intended to limit the scope of protection of the present invention.

[0012] Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this invention illustrate operations implemented according to some embodiments of the invention. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or performed simultaneously. Moreover, those skilled in the art, guided by the content of this invention, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0013] Furthermore, the embodiments described herein are merely some, not all, of the embodiments of the invention. The components of the embodiments of the invention described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0014] It should be noted that the term "comprising" will be used in the embodiments of the present invention to indicate the presence of a feature subsequently declared, but does not exclude the addition of other features. It should also be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0015] Numerical analysis is a commonly used method in mine slope stability analysis. It can simulate complex strata and boundary conditions, and effectively compensate for the disadvantages of high cost and inconvenient operation of large-scale direct shear tests on rock slopes.

[0016] Currently, constitutive models in numerical analysis are divided into two main categories: empirical models and theoretical models. Empirical models include power-law models and exponential models, which are simple in form and easy to apply in engineering, but their physical meaning is not clear enough. Theoretical models include viscoelastic models and viscoelastic-plastic models, which have clear physical meaning and can better describe the complex deformation behavior of soil and rock masses.

[0017] Due to differences in lithology, regional tectonics, hydrogeology, climate, and mining conditions, open-pit mine slopes often exhibit significant complexity, threatening the safety and production of open-pit mines. Classical numerical constitutive models are insufficient to accurately simulate the mechanical response of open-pit mine slopes under specific conditions.

[0018] Based on the above problems, this application proposes a method for establishing a numerical model of open-pit mine slopes. By secondary development of the constitutive model of the rock mass, the final numerical model can simulate the stress-strain state of the slope rock mass in a realistic manner, thereby better assisting in slope stability analysis and improving the accuracy of analysis and prediction.

[0019] The following is a detailed description of this case, in conjunction with the relevant accompanying drawings in the instruction manual.

[0020] Please see Figure 1 This description and embodiment provides a method for establishing a slope numerical model, specifically including the following steps: S10: Obtain the rock physical and mechanical parameters of the target slope area, core test data, and field monitoring data at multiple preset monitoring locations within the target slope area.

[0021] It is understood that the executing entity of this invention can be a device for establishing a slope numerical model, or it can be a terminal or a server; no specific limitation is made here. This embodiment of the invention will be described using a server as an example.

[0022] In this step, the target slope area refers to a specific open-pit mine slope section requiring stability analysis and instability early warning, such as the east slope profile of an open-pit coal mine. This section possesses a clearly defined stratigraphic structure (e.g., Quaternary overburden, siltstone, mudstone, coal seam), geometric shape (slope height, gradient), and engineering geological conditions. For this target slope area, on-site drilling and core sampling are conducted, collecting core samples at different depths and strata. The core samples are then sent to a laboratory where triaxial compression tests, Brazilian splitting tests, uniaxial compression tests, and density tests are performed to determine the rock mass's cohesion, internal friction angle, tensile strength, elastic modulus, Poisson's ratio, and density, among other physical and mechanical parameters. Simultaneously, triaxial compression tests are conducted under the same confining pressure conditions (e.g., 1 MPa, 4 MPa, 8 MPa), and the axial stress-strain curves are recorded as core test data.

[0023] Furthermore, several key locations in the target slope area (including the slope crest, slope toe, and shear exit) were pre-selected as preset monitoring locations. Displacement gauges, stress gauges, and other monitoring instruments were installed at each location to continuously collect on-site monitoring data. This monitoring data records the deformation and stress changes of the slope rock mass under actual working conditions, which is used for subsequent comparison and calibration with numerical simulation results.

[0024] Optionally, preset monitoring locations can be selected based on the engineering geological conditions and potential instability modes of the slope. Typically, key locations that are most sensitive to changes in slope stability, such as the top of the slope (area prone to tension cracks), the toe of the slope (stress concentration area), and the shear exit (location where potential slip surfaces are exposed), are selected. The deformation and stress response at these locations can most directly reflect the stability state of the slope.

[0025] S20: Based on the preset shear yield criterion, preset tensile yield criterion, and preset judgment logic, a constitutive model is established through the secondary development application programming interface of the finite element analysis software platform.

[0026] In this step, while the constitutive models (such as the Mohr-Coulomb model and the Drucker-Prag model) built into existing general-purpose finite element analysis software (such as FLAC3D and ABAQUS) can handle conventional geotechnical engineering problems, they have significant shortcomings when dealing with open-pit mine slopes with complex lithology and diverse failure modes. On the one hand, these models typically only consider shear yielding and lack explicit descriptions of tensile yielding, making it impossible to accurately simulate actual failure phenomena such as tensile cracking at the slope crest and tensile cracking at the trailing edge. On the other hand, even if some theoretical models (such as viscoelastic-plastic models) have a more complete mechanical framework, their specific mathematical forms and parameter systems are still fixed in the software kernel, and users cannot adjust or extend them according to the regional characteristics of mudstone, soft rock, etc. in specific mining areas. Because the calculation logic of the software's built-in models cannot be modified, engineers are often forced to use approximate models that do not fit reality, resulting in significant deviations between numerical simulation results and field monitoring data. Based on this, this application proposes a pre-defined shear yield criterion and tensile yield criterion, and defines the judgment logic for shear yield and tensile yield. Through the secondary development application programming interface (API) provided by the finite element analysis software platform, a custom constitutive model is embedded into the software as a dynamic link library, thereby achieving accurate simulation of shear-tensile combined failure modes that cannot be covered by the standard model. The secondary development API allows users to embed custom mathematical and physical models into the software as dynamic link libraries (DLLs) without modifying the software kernel source code. This fully utilizes the software's mature solver and pre- and post-processing functions, while also enabling the extension or replacement of the standard constitutive model, significantly improving the relevance and accuracy of slope numerical analysis.

[0027] Optionally, the expression for the preset shear yield criterion is:

[0028]

[0029] in, For shear stress, is the shear stress function in the shear case. This is the maximum principal stress; It is the minimum principal stress; It is the internal friction angle; c is the pressure coefficient; c is the cohesion. For the shear stress function; The expression for the preset tensile yield criterion is:

[0030]

[0031] in, Let be the shear stress function under tension. Let be the normal stress function under tension. It is tensile stress.

[0032] Furthermore, the preset judgment logic is as follows: A judgment is made based on whether the yield function is greater than 0. If the yield function is greater than 0 and the tensile function is less than 0, then it is judged as tensile yielding; conversely, if the yield function is less than 0 and the shear function is less than 0, then it is judged as shear yielding. Specifically, in each calculation step, the shear yield function is first calculated. and tensile yield function Then perform the following judgment: If If the value is greater than 0, then the material is determined to be in a tensile yield state; otherwise, if... If >0, it is determined to be in a shear yield state; if ≤0 and If the value is ≤0, it is determined to be in an elastic state. This judgment logic clearly divides the three mechanical response regions, ensuring that the constitutive model can automatically switch the appropriate yield mode and stress update algorithm according to the actual stress conditions, thereby accurately simulating the deformation and failure behavior of rock mass under complex stress conditions.

[0033] In one embodiment of this application, a specific constitutive model establishment scheme is provided. In S20, the constitutive model is established based on the preset shear yield criterion, the preset tensile yield criterion, and the preset judgment logic, through the secondary development application programming interface of the finite element analysis software. Specifically, it includes the following steps S21-S23: S21: Based on the preset shear yield criterion, preset tensile yield criterion, and preset judgment logic, write the source code of the constitutive model through the secondary development application programming interface of the general finite element analysis software.

[0034] S22: Compile and link the source code to generate a dynamic link library file.

[0035] S23: Store the dynamic link library file in the default directory of the general finite element analysis software for loading and calling.

[0036] For steps S21-S23, the preset shear yield criterion describes the yielding behavior of the rock mass under compressive-shear stress, and the preset tensile yield criterion describes the cracking failure of the rock mass under tensile stress. The preset judgment logic defines how to determine whether the material is in an elastic, shear yield, or tensile yield state based on the current stress state. When writing the code, first create a C++ project corresponding to the constitutive model in the software development environment (such as Microsoft Visual Studio). Following the function interfaces and data structures specified by the software API, write the shear yield function, tensile yield function, corresponding plastic potential function, and judgment rules into the source files (.cpp and .h files). Simultaneously, implement the basic functions such as model initialization, parameter passing, and stress updating according to the API requirements.

[0037] Further, after completing the source code writing, create a dynamic link library (DLL) project, add the source files to the project, set the compilation options compatible with the target software platform (such as platform toolsets, additional include directories, preprocessor definitions, etc.), and then execute the build command. After successful compilation and linking, a dynamic link library file with the .dll extension is output, which contains all the executable binary code of the custom constitutive model.

[0038] Next, store the generated dynamic link library (DLL) file in the default directory of the general-purpose finite element analysis software (e.g., the "plugins" subdirectory in FLAC3D or the specified path in "user subroutines" in ABAQUS). When the software starts, it will automatically scan this directory and load the DLL file, thereby registering the custom constitutive model into the software's material library. When building a slope numerical model subsequently, the user can select this custom constitutive model in the material property settings. During the calculation process, the software will call the functions in the DLL to perform stress-strain update calculations, thus enabling the engineering application of the custom constitutive model.

[0039] The above approach fully leverages the openness of the secondary development API, allowing users to seamlessly integrate custom constitutive models into the finite element analysis platform without modifying the software kernel, thereby providing accurate material constitutive relations for subsequent numerical simulations.

[0040] S30: Assign the physical and mechanical parameters of the rock mass to the constitutive model, and verify the assigned constitutive model based on core test data.

[0041] In this step, existing technologies typically directly define a constitutive model and apply it to numerical simulations at the engineering scale, neglecting to verify the model's correctness. This results in the model, while mathematically satisfying the preset yield criterion, failing to accurately reflect the actual deformation and failure characteristics of the target mining area's rock mass. Consequently, direct engineering simulation inevitably leads to unreliable prediction results. Therefore, this application proposes establishing a constitutive model through a secondary development interface, assigning the actually measured physical and mechanical parameters of the rock mass to the corresponding variables in the constitutive model, and then verifying the assigned constitutive model based on core test data. This ensures that the constitutive model can accurately reproduce the mechanical behavior of the indoor rock core before being applied to slope engineering simulations, thus providing a reliable model foundation for subsequent numerical simulations at the engineering scale.

[0042] In one embodiment of this application, a specific constitutive model verification scheme is provided. In S30, the rock mass physical and mechanical parameters are assigned to the constitutive model, and the assigned constitutive model is verified based on core test data. Specifically, this includes the following steps S31-S35: S31: Assign the physical and mechanical parameters of the rock mass to the constitutive model.

[0043] In this step, the physical and mechanical parameters of the rock mass obtained through indoor tests are assigned to the corresponding variables in the established custom constitutive model.

[0044] In practical applications, in finite element analysis software, the parameters of the constitutive model are usually entered sequentially through the material property setting interface or command line to complete the specification of the constitutive model parameters.

[0045] S32: Establish a numerical rock sample model for embedding constitutive models.

[0046] In this step, a small-scale numerical rock sample model is built in the finite element analysis software to simulate the indoor triaxial compression test. The geometric dimensions of the numerical rock sample model are typically a cylinder with a diameter of 50 mm and a height of 100 mm, divided into a sufficient number of mesh elements (e.g., hexahedral elements). This model is then assigned to an already configured constitutive model, thereby constructing a virtual specimen that can reflect the mechanical response of the real rock sample.

[0047] S33: Under the preset loading path, apply constant confining pressure to the numerical rock sample model and then apply deviatoric stress step by step until the specimen fails, and calculate the simulated stress-strain curve.

[0048] In this step, the preset loading path is first determined. The preset loading path refers to the loading method simulating the indoor triaxial compression test, that is, first applying a constant confining pressure, and then gradually increasing the axial deviatoric stress until the specimen fails. In the finite element analysis software, preset constant confining pressure values ​​are applied to the established numerical rock sample model, for example, set to 1 MPa, 4 MPa and 8 MPa respectively, to cover the rock sample response under different confining pressure conditions. Under the condition of keeping the confining pressure constant, deviatoric stress (i.e., the difference between axial stress and confining pressure) is applied gradually along the axial direction of the numerical rock sample model. The increment of deviatoric stress at each level is usually taken as 5% to 10% of the estimated peak strength, and finite element calculation is performed after each loading level to solve the stress field and displacement field of the model. The deviatoric stress is gradually increased until the numerical rock sample model reaches the failure state. The criteria for judging the failure state can be: the stress-strain curve shows a clear peak and then a downward segment, or the equivalent plastic strain increases significantly, or the calculation does not converge. Throughout the loading process, the axial strain value corresponding to each level of deviatoric stress was recorded. A simulated stress-strain curve was plotted with deviatoric stress as the ordinate and axial strain as the abscissa. This curve reflects the deformation and failure characteristics of the numerical rock sample under specific confining pressure, providing a quantitative basis for subsequent comparison with core test data.

[0049] S34: Quantitatively compare the simulated stress-strain curve with the core test data to obtain the comparison results.

[0050] In this step, key characteristic parameters are extracted from the calculated simulated stress-strain curve, including peak strength, peak strain, elastic modulus (i.e., the slope of the initial linear elastic segment of the stress-strain curve), and residual strength after failure (if applicable). Simultaneously, corresponding parameters under the same confining pressure conditions are extracted from core test data. The deviation rate between the simulated and experimental values ​​is calculated, and the calculated deviation rates and overall goodness of fit are output as comparison results. This comparison result is used to determine whether the constitutive model accurately reproduces the mechanical behavior of the real core. If all deviation rates are within a preset error range (e.g., ±5%) and the overall curve shape is consistent, the model is considered to have passed validation; otherwise, further correction of model parameters or code logic is required.

[0051] For example, taking peak strength as an example, the deviation rate between the simulated value and the experimental value is calculated as follows: Deviation rate = (simulated value - experimental value) / experimental value × 100%. Similarly, the deviation rates of parameters such as peak strain and elastic modulus are calculated. In addition, the root mean square error or coefficient of determination can be used to evaluate the degree of agreement between the overall shapes of the two curves.

[0052] S35: If the comparison results exceed the preset error range, check and correct the source code of the constitutive model and recompile to generate the dynamic link library file, or adjust the rock physical and mechanical parameters in the constitutive model, and re-execute the steps of calculating the stress-strain curve and comparison until the comparison results are within the preset error range.

[0053] In this step, if the comparison between the simulated stress-strain curve and the core test data exceeds the preset error range (e.g., the absolute value of the deviation rate of peak strength, peak strain, or elastic modulus is greater than 5%, or the overall shape of the curve is mismatched), at least one of the following correction operations is performed. First correction method: Check and correct the source code of the constitutive model, specifically including verifying whether the mathematical expressions of the shear yield criterion and tensile yield criterion are correct, whether the judgment logic is correct, whether the implementation of the plastic flow law is accurate, and whether there are errors in the numerical calculation in the stress update algorithm; after completing the code correction, recompile the source file using the secondary development interface's compilation environment to generate a new dynamic link library file, and replace the original dynamic link library. Second correction method: Adjust the rock mass physical and mechanical parameters in the constitutive model, that is, without modifying the source code, adjust one or more of the following according to the direction of deviation in the comparison results: cohesion, internal friction angle, tensile strength, elastic modulus, Poisson's ratio, or density. For example, if the simulated peak strength is too low, the cohesion or internal friction angle can be appropriately increased. Regardless of the correction method used, after correction, the steps of applying confining pressure and deviatoric stress to the numerical rock sample model, calculating the simulated stress-strain curve, and quantitatively comparing the new curve with the core test data must be repeated. This cycle of correction, calculation, and comparison is repeated until all comparison indicators fall within the preset error range, at which point the validated constitutive model is obtained.

[0054] The above methods ensure that the constitutive model accurately reproduces the mechanical behavior of the core samples from the target mining area.

[0055] S40: Based on the validated constitutive model, establish a finite element numerical model of the target slope region.

[0056] In this step, after verifying the constitutive model and confirming that it can accurately reproduce the mechanical behavior of the indoor rock core, a finite element numerical model that can truly reflect the geological conditions and material properties of the target slope area can be established based on the verified constitutive model, thus laying the foundation for subsequent numerical simulation and comparative verification.

[0057] In practical applications, the first step is to determine the slope's geometry and stratigraphic distribution based on the actual engineering geological profile of the target slope area. For example, a 126m high open-pit mine slope has strata from top to bottom consisting of Quaternary overburden, siltstone, mudstone, silty mudstone, mudstone, coal seam, and bottom mudstone. In general-purpose finite element analysis software (such as FLAC3D), a two-dimensional or three-dimensional mesh model is established according to the aforementioned geometric dimensions and stratigraphic boundaries. Each stratigraphic unit is assigned a validated constitutive model and its corresponding rock mass physical and mechanical parameters (including cohesion, internal friction angle, tensile strength, elastic modulus, Poisson's ratio, and density). Then, the model's boundary conditions are set: the bottom nodes have fixed displacements in three directions, the two side boundaries constrain horizontal displacements, and the top is a free boundary. The initial stress field is applied based on the self-weight stress field, i.e., the vertical stress and horizontal lateral pressure are calculated according to the density and burial depth of each rock layer. Finally, a finite element numerical model reflecting the geological conditions and material properties of the target slope area is obtained.

[0058] S50: Simulate the finite element numerical model, compare and verify the simulation results with the field monitoring data, and obtain the verified finite element numerical model.

[0059] In this step, existing technologies typically use the constitutive model directly for deformation prediction or stability analysis after developing the constitutive model and establishing the slope numerical model, lacking a systematic verification step using actual field monitoring data to validate the engineering-scale numerical model. This leads to a situation where, although the constitutive model passes verification on small-scale rock samples, when extended to real slope conditions, the simulation results may still deviate significantly from the actual field response due to factors such as geometric simplification, approximate boundary conditions, and local variations in formation parameters. Such deviations are often overlooked in existing methods, reducing the reliability of the prediction results. Therefore, this application proposes numerical simulation of the established finite element numerical model and comparative verification of the simulation results with field monitoring data to ensure that the engineering-scale numerical model can accurately reflect the actual mechanical response of the target slope area, thus providing a reliable basis for determining subsequent instability early warning criteria.

[0060] In one embodiment of this application, a specific finite element numerical model verification scheme is provided. In S50, that is, simulating the finite element numerical model and comparing the simulation results with the field monitoring data to obtain the verified finite element numerical model, the scheme specifically includes the following steps S51-S54: S51: Apply gravity load to the finite element numerical model and calculate the mechanical response of the slope rock mass according to the preset boundary constraints to obtain the stress field and displacement field for each calculation step.

[0061] In this step, a gravitational acceleration (typically 9.81 m / s²) is applied to all elements of the entire model in the finite element analysis software, while maintaining the previously set boundary conditions: the bottom nodes have fixed displacements in three directions, the side boundaries constrain horizontal displacements (i.e., the normal displacement is zero), and the top is a free boundary. An explicit or implicit time-stepping iterative algorithm is used to perform static or time-history calculations on the model. In each calculation step, the software solves the equilibrium equations based on the given constitutive model and rock physical and mechanical parameters, updating the displacements and velocities of each node, as well as the stresses and strains of each element. The calculation continues until the model reaches equilibrium (e.g., the maximum unbalanced force is less than a preset threshold) or the preset number of calculation steps is completed. During the calculation, the system automatically outputs the stress field (including the maximum principal stress, minimum principal stress, shear stress, etc. of each element) and displacement field (including the horizontal displacement, vertical displacement, and total displacement vector of each node) for each calculation step. These field quantities provide the basis for subsequent extraction of simulated values ​​of key parts and comparative verification.

[0062] The above methods can be used to comprehensively obtain the deformation and stress distribution characteristics of slope rock mass under its own weight.

[0063] S52: Extract simulated stress values ​​and simulated strain values ​​from multiple preset monitoring locations in the stress field and displacement field.

[0064] In this step, the stress and displacement components at each preset monitoring location are obtained in the finite element analysis software using node numbers or coordinate positioning at the same calculation time step. For stress values ​​at element integration points, shape function interpolation or averaging of adjacent nodes can be used to convert them to the coordinates of the preset monitoring location. The extracted data are then organized chronologically to form a sequence of simulated stress values ​​and simulated strain for each preset monitoring location, which is used for subsequent comparison and verification with field monitoring data.

[0065] Optionally, the extraction process can be automated using the software's built-in post-processing functions or by writing scripts (such as Fish or Python) to ensure data consistency and repeatability.

[0066] S53: Extract the monitoring stress value and monitoring strain of each preset monitoring location from the field monitoring data.

[0067] In this step, stress and displacement readings at each preset monitoring location at various time points are read from the pre-acquired field monitoring data of the target slope area. If the monitoring time points do not completely correspond to the simulation time steps, linear interpolation or nearest neighbor sampling methods are used to match the time. The extracted monitoring values ​​are arranged into a sequence in chronological order as benchmark data for comparison and verification.

[0068] S54: Based on the simulated stress value, simulated strain, monitored stress value, and monitored strain, the finite element numerical model is compared and verified to obtain the verified finite element numerical model.

[0069] In this step, for each preset monitoring location and each corresponding time point, the first deviation rate between the simulated stress value and the monitored stress value, and the second deviation rate between the simulated strain and the monitored strain are calculated. If the absolute values ​​of both deviation rates for all preset monitoring locations are less than or equal to the preset deviation threshold (e.g., 5%), and the statistical distribution of the overall deviation rate satisfies the preset normal distribution (e.g., the mean approaches 0 and the standard deviation does not exceed 2%), then the finite element numerical model is deemed to have passed verification and is output as the verified finite element numerical model. If any condition is not met, the verification is deemed to have failed. In this case, the model parameters (such as rock mass physical and mechanical parameters, boundary conditions, or constitutive model parameters) need to be adjusted, and the simulation and comparison verification should be performed again until the verification conditions are met.

[0070] By using the above methods, we can ensure that the finite element numerical model can accurately reflect the actual mechanical response of the target slope area on an engineering scale.

[0071] In one embodiment of this application, a specific finite element numerical model comparison and verification scheme is provided. In S54, that is, based on the simulated stress value, simulated strain, monitored stress value, and monitored strain, the finite element numerical model is compared and verified to obtain the verified finite element numerical model. Specifically, it includes the following steps S541-S543: S541: Calculate the first deviation rate between the simulated stress value and the monitored stress value, and the second deviation rate between the simulated strain and the monitored strain, respectively.

[0072] In this step, the first deviation rate = (simulated stress value - monitored stress value) / monitored stress value × 100%; the second deviation rate = (simulated strain - monitored strain) / monitored strain × 100%. For each preset monitoring location and each corresponding time point, the calculated deviation rate will be used as the quantitative basis for subsequent judgment.

[0073] Optionally, if a certain monitoring value is zero or close to zero, in order to avoid division by zero error, the absolute deviation or the preset minimum value denominator can be used for correction.

[0074] S542: When the absolute values ​​of the first deviation rate and the second deviation rate are both less than or equal to the preset deviation threshold, and the overall deviation rate distribution of all preset monitoring positions satisfies the preset normal distribution, the finite element numerical model is determined to have passed the verification.

[0075] In this step, a deviation threshold (e.g., 5%) is preset, along with a normal distribution condition (e.g., the overall distribution of deviation rates at all preset monitoring locations should satisfy a normal distribution with a mean of 0 and a standard deviation not exceeding 2%). When the absolute value of the first deviation rate at each time point for all preset monitoring locations is less than or equal to the preset deviation threshold, and the absolute value of the second deviation rate is also less than or equal to the preset deviation threshold, and the statistical distribution of all deviation rates (including the first and second deviation rates) conforms to the preset normal distribution characteristics, the finite element numerical model is deemed to have passed validation. This means that the simulation results are consistent with the field monitoring data within the acceptable error range for engineering, and the model can truly reflect the actual mechanical response of the target slope area.

[0076] S543: When the absolute value of the first deviation rate and / or the second deviation rate is greater than the preset deviation threshold, or when the overall deviation rate distribution of all preset monitoring positions does not meet the preset normal distribution, adjust at least one parameter in the finite element numerical model and re-perform numerical simulation and comparison verification until the verification conditions are met. Among them, at least one parameter includes rock mass physical and mechanical parameters, preset boundary constraints, or constitutive model parameters.

[0077] In this step, if the absolute values ​​of the first deviation rate and / or the second deviation rate are greater than the preset deviation threshold, or if the overall deviation rate distribution of all preset monitoring locations does not meet the preset normal distribution after statistical testing, the finite element numerical model is deemed to have failed verification. In this case, at least one parameter in the model needs to be adjusted, and numerical simulation and comparative verification need to be performed again until the verification conditions are met.

[0078] Optionally, adjustable parameters include, but are not limited to: rock mass physical and mechanical parameters (such as cohesion, internal friction angle, tensile strength, elastic modulus, Poisson's ratio, and density), preset boundary constraints (such as boundary constraint range, constraint stiffness, or displacement boundary type), and constitutive model parameters (such as flow law parameters in the yield criterion, plastic hardening parameters, etc.). Adjustment can be done manually based on the deviation direction, or by using automatic optimization algorithms (such as gradient descent or genetic algorithms) for parameter inversion. After parameter adjustment, the steps of applying gravity load, calculating stress and displacement fields, extracting simulated values ​​from preset monitoring locations, comparing with field monitoring data to calculate the deviation rate, and verifying the deviation rate distribution are repeated until all verification conditions are met, thus obtaining a validated finite element numerical model. This ensures the model's engineering applicability and predictive reliability.

[0079] In one embodiment of this application, a specific scheme for determining instability early warning criteria is provided. This involves comparing and verifying a finite element numerical model based on simulated stress values, simulated strain, monitored stress values, and monitored strain. After obtaining the verified finite element numerical model, the following steps are further included: Based on the simulation results of the validated finite element numerical model, the critical deformation of the key points of the slope is determined. The critical deformation is the deformation value when the simulation results show that the slope begins to show significant damage or accelerated deformation. The critical deformation is multiplied by a preset safety factor to obtain a critical deformation threshold with a preset safety margin. The critical deformation threshold is then used as an instability warning criterion to determine the stability state of the target slope area.

[0080] In this embodiment, existing technologies often only provide a safety factor or the final displacement cloud map after completing numerical simulations, lacking a quantitative early warning criterion that can directly compare the simulation results with on-site monitoring data. This makes it difficult for engineers to determine when protective measures should be taken. Therefore, this application proposes extracting displacement-time curves from preset monitoring locations such as the slope top, slope toe, and shear exit from the validated finite element numerical model. Observing the changes in the curve shape, the inflection point where the deformation rate changes from constant to accelerating, or the critical point where the displacement exceeds the elastic stage and enters the plastic stage, is selected as the critical deformation amount. Next, the critical deformation amount is multiplied by a preset safety factor (e.g., 1.2 to 1.5) to obtain a critical deformation threshold with a preset safety margin. Finally, this critical deformation threshold is used as an instability early warning criterion to determine the stability state of the target slope area. When the on-site monitored displacement is less than this threshold, the slope is considered to be in a safe state; when the monitored displacement approaches or exceeds this threshold, an instability warning is issued. By extracting critical deformation from simulation results and assigning a safety margin, a clear mapping from numerical simulation to instability early warning was established, forming a clear and operable instability early warning criterion. This solves the problem that simulation results are difficult to directly guide on-site early warning in existing technologies, and improves the operability and reliability of open-pit mine slope safety management.

[0081] Furthermore, as a refinement and extension of the specific implementation methods of the above embodiments, in order to fully explain the specific implementation process of this embodiment, in conjunction with... Figure 2 and Figure 3 The method for establishing the slope numerical model proposed in this embodiment is explained and verified in detail, including the following: The method for establishing a numerical model of a slope includes the following steps: S1: Conduct analysis preparation work.

[0082] Specifically, in the general-purpose finite element analysis software platform FLAC3D and its development environment Visual Studio 2015, the source file code is modified using its secondary development interface to generate a new model, and the generated dynamic link library file is placed in the software root directory for loading and calling.

[0083] S2: Construct constitutive models that implement each function.

[0084] Specifically, a constitutive equation model is constructed, comprising a basic function, a plastic yield indicator function, and an assignment function. Further, the CPP file is modified to complete function initialization, and preset shear yield criteria and preset tensile yield criteria based on the Mohr-Coulomb model are defined.

[0085] S3: Verify the response of the model by testing its replication.

[0086] Specifically, under typical loading paths, i.e., under constant confining pressures of 1MPa, 4MPa, and 8MPa, deviatoric stresses are applied stepwise until deformation stabilizes or the specimen fails, thus reproducing the responses of various classical models. The deformation behavior predicted by the new model is then quantitatively compared and analyzed with the experimental results under the same stress conditions.

[0087] S4: Apply model simulation to engineering cases.

[0088] Specifically, using the aforementioned developed constitutive model and its experimentally calibrated parameters, a finite element numerical model of the slope was established, and the long-term deformation of the slope rock mass under its own weight and boundary conditions was calculated. The simulated engineering case is an open-pit mine slope, 126m high, with strata consisting of Quaternary overburden, siltstone, mudstone, silty mudstone, mudstone, coal seam, and mudstone, with relatively little groundwater. Figure 2 The figure shows a schematic diagram of the simulated slope displacement results after assigning values ​​to the physical and mechanical parameters calibrated in the experiment. The displacement near the shear exit at the leading edge of the slope is more significant, with the maximum displacement being approximately 8.71 × 10⁻⁶. -2 The displacement contour lines gradually decrease from the toe to the crest of the slope along the potential slip surface (0.0871m), indicating poor stability near the shallow slip surface. The simulation results are in good agreement with the large displacement areas monitored in the field, verifying the rationality of the constitutive model and parameter selection.

[0089] S5: Compare and calibrate the model simulation results with the measured values.

[0090] Specifically, the model's reliability is verified by comparing and calibrating the simulated stress and strain at preset monitoring locations with the measured values ​​in the field. Preset monitoring locations include, but are not limited to, the slope crest, slope toe, and shear exit points. The deviation rates of simulated stress and measured stress, and simulated strain and measured strain at the preset monitoring locations are calculated respectively. The deviation rate is defined as (simulated value - measured value) / measured value × 100%. It is required that the absolute value of the deviation rate for each key location does not exceed 5%, and the overall deviation rate distribution satisfies a normal distribution N(0, 0.02). 2 ).like Figure 3The figure shows a comparison between the simulation results and the field monitoring data, illustrating the cumulative horizontal displacement of key points over monitoring time. Both the monitoring data and the simulation results show that the displacement gradually increases with the number of monitoring days. Within the range of 0 to 180 days, the monitoring data increased from 0 mm to approximately 80 mm, while the simulation results increased from 0 mm to approximately 8 mm. The values ​​at various time points are quite close; for example, on day 120, the monitoring value was 74 mm and the simulation value was 75 mm; on day 150, the monitoring value was 78 mm and the simulation value was 78 mm; and on day 180, the monitoring value was 80 mm and the simulation value was 80 mm. Overall, the simulation results and the monitoring data agree well, with the deviation rate controlled within the allowable range, further verifying the reliability of the constitutive model and the finite element numerical model.

[0091] S6: Select a critical threshold with a safety margin as the basis for evaluation.

[0092] Specifically, by comprehensively analyzing the simulation results, a critical deformation threshold with a specific engineering safety margin is selected as the instability early warning criterion, used to assess the stress field and stability state of the slope after deformation. This criterion can be determined based on the characteristics of significant deformation or near-failure observed in the simulation results.

[0093] As can be seen, in the above-mentioned scheme, addressing the challenges of complex lithology and diverse failure modes in open-pit mine slopes, this application constructs a constitutive model that simultaneously considers both shear and tensile combined failure modes by pre-setting shear and tensile yield criteria and defining judgment logic, using a secondary development interface. This overcomes the shortcomings of traditional models that only consider shear yield. Subsequently, small-scale verification was performed using core test data to ensure the model's accuracy at the material level. Furthermore, the numerical model at the engineering scale was compared and verified using field monitoring data, overcoming the shortcomings of existing technologies that lack engineering-scale verification and exhibit large deviations between simulation results and measured values. Through multi-level verification and calibration, the fit and predictive reliability of the slope numerical simulation were significantly improved, enabling the final numerical model to truly reflect the mechanical response of the target slope area, providing an accurate and reliable model foundation for open-pit mine slope stability analysis and instability early warning.

[0094] In one embodiment, a device for establishing a slope numerical model is provided, which corresponds one-to-one with the slope numerical model establishment method described in the above embodiments. For example... Figure 4 As shown, the slope numerical model establishment device 100 includes: an acquisition module 101, a first establishment module 102, a first verification module 103, a second establishment module 104, and a second verification module 105. Detailed descriptions of each functional module are as follows: The acquisition module 101 is used to acquire the rock physical and mechanical parameters of the target slope area, rock core test data, and field monitoring data of multiple preset monitoring locations within the target slope area; The first module 102 is used to establish a constitutive model based on a preset shear yield criterion, a preset tensile yield criterion, and preset judgment logic, through the secondary development application programming interface of the finite element analysis software platform. The first verification module 103 is used to assign rock mass physical and mechanical parameters to the constitutive model and verify the assigned constitutive model based on core test data. The second module 104 is used to establish a finite element numerical model of the target slope region based on the verified constitutive model. The second verification module 105 is used to simulate the finite element numerical model, compare the simulation results with the field monitoring data, and obtain the verified finite element numerical model.

[0095] In one embodiment, the first establishment module 102 is specifically used for: Based on the preset shear yield criterion, preset tensile yield criterion, and preset judgment logic, the source code of the constitutive model is written through the secondary development application programming interface of the general finite element analysis software. The source code is compiled and linked to generate a dynamic link library file. Store the dynamic link library files in the default directory of the general finite element analysis software for loading and calling.

[0096] In one embodiment, the first verification module 103 is specifically used for: Assign values ​​to the rock mass physical and mechanical parameters to the constitutive model; Establish a numerical rock sample model with embedded constitutive model; Under the preset loading path, a constant confining pressure is applied to the numerical rock sample model, and then deviatoric stress is applied step by step until the specimen fails, and the simulated stress-strain curve is calculated. The simulated stress-strain curves were quantitatively compared with core test data to obtain the comparison results. If the comparison results exceed the preset error range, check and correct the source code of the constitutive model and recompile to generate the dynamic link library file, or adjust the rock physical and mechanical parameters in the constitutive model, and re-execute the steps of calculating stress-strain curves and comparison until the comparison results are within the preset error range.

[0097] In one embodiment, the second verification module 105 is specifically used for: Gravity load is applied to the finite element numerical model, and the mechanical response of the slope rock mass is calculated according to the preset boundary constraints to obtain the stress field and displacement field at each calculation step. Simulated stress values ​​and simulated strain values ​​at multiple preset monitoring locations are extracted from the stress field and displacement field; Extract the monitoring stress value and monitoring strain at each preset monitoring location from the on-site monitoring data; The finite element numerical model is compared and verified based on simulated stress values, simulated strain values, monitored stress values, and monitored strain values ​​to obtain the verified finite element numerical model.

[0098] In one embodiment, the second verification module 105 is further configured to: Calculate the first deviation rate between the simulated stress value and the monitored stress value, and the second deviation rate between the simulated strain and the monitored strain, respectively. When the absolute values ​​of the first deviation rate and the second deviation rate are both less than or equal to the preset deviation threshold, and the overall deviation rate distribution of all preset monitoring positions meets the preset normal distribution, the finite element numerical model is deemed to have passed the verification. When the absolute value of the first deviation rate and / or the second deviation rate is greater than the preset deviation threshold, or when the overall deviation rate distribution of all preset monitoring locations does not meet the preset normal distribution, at least one parameter in the finite element numerical model is adjusted, and numerical simulation and comparative verification are performed again until the verification conditions are met. The at least one parameter includes rock mass physical and mechanical parameters, preset boundary constraint conditions, or constitutive model parameters.

[0099] In one embodiment, the expression for the preset shear yield criterion is:

[0100]

[0101] in, For shear stress, is the shear stress function in the shear case. This is the maximum principal stress; It is the minimum principal stress; It is the internal friction angle; c is the pressure coefficient; c is the cohesion. For the shear stress function; The expression for the preset tensile yield criterion is:

[0102]

[0103] in, Let be the shear stress function under tension. Let be the normal stress function under tension. It is tensile stress.

[0104] In one embodiment, the device further includes: The determination module is used to determine the critical deformation of key points of the slope based on the simulation results of the validated finite element numerical model. The critical deformation is the deformation value when the simulation results show that the slope begins to show significant damage or accelerated deformation. The generation module is used to multiply the critical deformation amount by a preset safety factor to obtain a critical deformation amount threshold with a preset safety margin, and uses the critical deformation amount threshold as an instability early warning criterion to determine the stability state of the target slope area.

[0105] The slope numerical model establishment device 100 provided by this invention addresses the challenges of complex lithology and diverse failure modes in open-pit mine slopes. This application constructs a constitutive model that simultaneously considers both shear and tensile combined failure modes by pre-setting shear and tensile yield criteria and defining judgment logic, using a secondary development interface. This overcomes the shortcomings of traditional models that only consider shear yield. Subsequently, small-scale verification using core test data ensures the model's accuracy at the material level. Furthermore, comparative verification of the engineering-scale numerical model is conducted using field monitoring data, overcoming the shortcomings of existing technologies that lack engineering-scale verification and exhibit large deviations between simulation results and measured values. Through multi-level verification and calibration, the fit and predictive reliability of the slope numerical simulation are significantly improved, enabling the final numerical model to accurately reflect the mechanical response of the target slope area, providing an accurate and reliable model foundation for open-pit mine slope stability analysis and instability early warning.

[0106] Specific limitations regarding the apparatus for establishing slope numerical models can be found in the limitations on the methods for establishing slope numerical models described above, and will not be repeated here. Each module in the aforementioned apparatus for establishing slope numerical models can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in an electronic device, or stored in the memory of an electronic device in software form, so that the processor can call and execute the corresponding operations of each module.

[0107] In one embodiment, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for establishing a slope numerical model.

[0108] In one embodiment, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the above-described method for establishing a slope numerical model.

[0109] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or electronic device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0110] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0111] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0112] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for establishing a numerical model of a slope, characterized in that, include: Obtain the rock mass physical and mechanical parameters, core test data, and field monitoring data at multiple preset monitoring locations within the target slope area; Based on the preset shear yield criterion, preset tensile yield criterion, and preset judgment logic, a constitutive model is established through the secondary development application programming interface of the finite element analysis software platform. The physical and mechanical parameters of the rock mass are assigned to the constitutive model, and the assigned constitutive model is verified based on the core test data. Based on the validated constitutive model, a finite element numerical model of the target slope region is established. The finite element numerical model is simulated, and the simulation results are compared and verified with the field monitoring data to obtain the verified finite element numerical model.

2. The method for establishing a slope numerical model according to claim 1, characterized in that, The steps for establishing a constitutive model based on preset shear yield criteria, preset tensile yield criteria, and preset judgment logic, through the secondary development application programming interface of the finite element analysis software platform, specifically include: Based on the preset shear yield criterion, the preset tensile yield criterion, and the preset judgment logic, the source code of the constitutive model is written through the secondary development application programming interface of the general finite element analysis software. The source file code is compiled and linked to generate a dynamic link library file; The dynamic link library file is stored in the preset directory of the general finite element analysis software for loading and calling.

3. The method for establishing a slope numerical model according to claim 1, characterized in that, The steps of assigning the physical and mechanical parameters of the rock mass to the constitutive model and verifying the assigned constitutive model based on the core test data specifically include: The physical and mechanical parameters of the rock mass are assigned to the constitutive model; Establish a numerical rock sample model with embedded constitutive model; Under a preset loading path, a constant confining pressure is applied to the numerical rock sample model, followed by a stepwise application of deviatoric stress until the specimen fails, and the simulated stress-strain curve is calculated. The simulated stress-strain curves were quantitatively compared with the core test data to obtain the comparison results. If the comparison result exceeds the preset error range, check and correct the source code of the constitutive model and recompile to generate a dynamic link library file, or adjust the rock physical and mechanical parameters in the constitutive model, and re-execute the steps of calculating stress-strain curves and comparison until the comparison result is within the preset error range.

4. The method for establishing a slope numerical model according to claim 1, characterized in that, The steps of simulating the finite element numerical model, comparing the simulation results with the field monitoring data, and obtaining the verified finite element numerical model specifically include: Gravity load is applied to the finite element numerical model, and the mechanical response of the slope rock mass is calculated according to the preset boundary constraints to obtain the stress field and displacement field at each calculation step. Simulated stress values ​​and simulated strain values ​​at multiple preset monitoring locations are extracted from the stress field and the displacement field; Extract the monitoring stress value and monitoring strain at each preset monitoring location from the on-site monitoring data; Based on the simulated stress value, the simulated strain, the monitored stress value, and the monitored strain, the finite element numerical model is compared and verified to obtain the verified finite element numerical model.

5. The method for establishing a slope numerical model according to claim 4, characterized in that, The step of comparing and verifying the finite element numerical model based on the simulated stress value, the simulated strain, the monitored stress value, and the monitored strain to obtain the verified finite element numerical model specifically includes: Calculate the first deviation rate between the simulated stress value and the monitored stress value, and the second deviation rate between the simulated strain and the monitored strain, respectively. When the absolute values ​​of the first deviation rate and the second deviation rate are both less than or equal to the preset deviation threshold, and the overall deviation rate distribution of all preset monitoring positions satisfies the preset normal distribution, the finite element numerical model is determined to have passed the verification. When the absolute value of the first deviation rate and / or the second deviation rate is greater than the preset deviation threshold, or when the overall deviation rate distribution of all preset monitoring locations does not meet the preset normal distribution, at least one parameter in the finite element numerical model is adjusted, and numerical simulation and comparison verification are performed again until the verification conditions are met. The at least one parameter includes rock mass physical and mechanical parameters, preset boundary constraint conditions, or constitutive model parameters.

6. The method for establishing a slope numerical model according to claim 1, characterized in that, The expression for the preset shear yield criterion is: in, For shear stress, is the shear stress function in the shear case. This is the maximum principal stress; It is the minimum principal stress; It is the internal friction angle; c is the pressure coefficient; c is the cohesion. For the shear stress function; The expression for the preset tensile yield criterion is: in, Let be the shear stress function under tension. Let be the normal stress function under tension. It is tensile stress.

7. The method for establishing a slope numerical model according to claim 1, characterized in that, After simulating the finite element numerical model and comparing the simulation results with the field monitoring data to obtain the verified finite element numerical model, the process further includes: Based on the simulation results of the validated finite element numerical model, the critical deformation of the key points of the slope is determined, wherein the critical deformation is the deformation value when the simulation results show that the slope begins to show significant damage or accelerated deformation. The critical deformation amount is multiplied by a preset safety factor to obtain a critical deformation threshold with a preset safety margin. The critical deformation threshold is used as an instability warning criterion to determine the stability state of the target slope area.

8. A device for establishing a numerical model of a slope, characterized in that, include: The acquisition module is used to acquire the rock physical and mechanical parameters of the target slope area, rock core test data, and field monitoring data of multiple preset monitoring locations within the target slope area; The first module is used to establish a constitutive model based on preset shear yield criteria, preset tensile yield criteria and preset judgment logic, through the secondary development application programming interface of the finite element analysis software platform. The first verification module is used to assign the physical and mechanical parameters of the rock mass to the constitutive model, and to verify the assigned constitutive model based on the core test data. The second module is used to establish a finite element numerical model of the target slope region based on the verified constitutive model. The second verification module is used to simulate the finite element numerical model, compare the simulation results with the field monitoring data, and obtain the verified finite element numerical model.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for establishing a slope numerical model as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for establishing a slope numerical model as described in any one of claims 1 to 7.

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