A dynamic modeling system and method for slope support anchor rod reinforcement combination

Abstract

The application provides a kind of slope support anchor rod reinforcing combination dynamic modeling system and method, by constructing anchor rod-slope dynamics coupling dynamic simulation model;According to the stress evolution process of target slope in different monitoring points in target slope and surrounding soil deformation information of anchor rod, the stress distribution structure of each region of target slope is obtained by dynamic inversion;Extract the displacement response characteristics of each anchor rod under different vibration loads, determine the deformation vector field of anchor rod reinforcing combination in slope support under different vibration loads through the mapping relationship of all displacement response characteristics and soil deformation under different vibration loads;According to the stress distribution structure and deformation vector field of each region of target slope, the simulation granularity of local stress simulation in dynamic simulation model is determined, and then the discretization level of dynamic simulation model is adjusted based on simulation granularity. Using the scheme of the application, the adaptive adjustment of local discrete level in anchor rod reinforcing combination simulation model can be realized.

Description

Technical Field

[0001] This application relates to the field of dynamic modeling technology, and more specifically, to a dynamic modeling system and method for slope support anchor reinforcement combination. Background Technology

[0002] With the increasing complexity of slope protection engineering, especially in earthquake-prone areas, traditional design methods can no longer meet actual needs. Dynamic modeling can simulate vibration loads, deformation processes, and failure modes of the support system, providing a reliable basis for engineering design and ensuring the stability and safety of slopes under different working conditions. Furthermore, dynamic modeling can optimize the design of the support structure through real-time simulation data, improving its seismic performance and economy, which is of great significance for improving the overall effectiveness of the support system and disaster prevention capabilities.

[0003] Current technologies for slope support design have significant shortcomings in dynamic load response analysis. Traditional modeling and simulation methods mainly rely on static analysis, neglecting the impact of dynamic loads such as earthquakes on the support system. They cannot accurately reflect the interaction and deformation response between anchor bolts and soil under vibration loads. This leads to an inability to fully assess slope stability under extreme loads such as earthquakes in practical applications, particularly in predicting anchor bolt stress and soil deformation under complex conditions. Furthermore, existing technologies lack refined dynamic modeling tools when dealing with variable load conditions (such as earthquakes), often failing to make targeted precision adjustments for different areas of the slope, resulting in insufficient overall simulation accuracy. Therefore, how to achieve adaptive adjustment of local discrete levels in the simulation model of anchor bolt reinforcement has become a challenge for the industry. Summary of the Invention

[0004] This application provides a dynamic modeling system and method for slope support anchor reinforcement combination, which can realize adaptive adjustment of local discrete levels in the simulation model of anchor reinforcement combination.

[0005] In a first aspect, this application provides a dynamic modeling method for combined slope support anchor reinforcement, comprising the following steps: A dynamic simulation model of anchor-slope dynamic coupling is established based on the geological parameters of the target slope and the topology of anchor placement in the anchor reinforcement combination. During the slope support operation phase, the correlation coefficients of the anchor bolt-slope response characteristics between different monitoring points are determined based on the anchor bolt stress conditions and surrounding soil deformation information at different monitoring points in the target slope. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients, and the stress distribution structure of each area of ​​the target slope is obtained. In the dynamic simulation model, different magnitudes of vibration loads are applied to the target slope, and the displacement response characteristics of each anchor under different vibration loads are extracted. The deformation vector field of the anchor reinforcement combination in slope support under different vibration loads is determined by the mapping relationship between all displacement response characteristics and soil deformation under different vibration loads. Based on the stress distribution structure of each region of the target slope and the deformation vector field, the simulation granularity of the local stress simulation in the dynamic simulation model is determined, and then the discretization level of the dynamic simulation model is adjusted based on the simulation granularity.

[0006] Preferably, the dynamic simulation model of anchor-slope dynamic coupling based on the geological parameters of the target slope and the topology of anchor placement in the anchor reinforcement combination specifically includes: A three-dimensional model of the anchor-slope is constructed based on the three-dimensional data of the target slope and the anchor reinforcement combination. The boundary conditions for the anchor bolt-slope dynamic coupling simulation are determined based on the geological parameters and the layout topology. A dynamic simulation model of anchor bolt-slope dynamic coupling is constructed by combining the three-dimensional model and the boundary conditions using the finite element discretization method.

[0007] Preferably, three-dimensional data of the target slope and anchor reinforcement combination are acquired using laser scanning equipment.

[0008] Preferably, the correlation coefficient between the anchor bolts and the slope response characteristics at different monitoring points is determined based on the anchor bolt stress conditions and surrounding soil deformation information at different monitoring points in the target slope. Specifically, this includes: Select a monitoring point as the target monitoring point, and obtain the stress data of the anchor rod and the deformation data of the surrounding soil at the target monitoring point; Extract the force response characteristics of the anchor bolt from the force data of the anchor bolt; Extract the deformation response characteristics of the surrounding soil from the deformation data of the surrounding soil; Based on the stress response characteristics and the deformation response characteristics, determine the anchor bolt-slope response characteristics of the target monitoring point, and continue to determine the anchor bolt-slope response characteristics of the remaining monitoring points; Determine the Spearman correlation coefficient of the anchor bolt-slope response characteristics among different monitoring points; The correlation coefficients of the anchor-slope response characteristics between different monitoring points were determined by using all Spearman correlation coefficients.

[0009] Preferably, the dynamic simulation model, combined with all correlation coefficients, is used to dynamically invert the stress evolution process of the target slope, resulting in the stress distribution structure of each region of the target slope, specifically including: Based on all the correlation coefficients, construct a cross-correlation matrix of the anchor-slope response characteristics among different monitoring points; By combining the cross-correlation matrix with the initial stress data of different monitoring points in the target slope, and using the inversion module in the dynamic simulation model, the stress evolution curve of the target slope at different times is calculated by the inversion algorithm. Extract the stress distribution structure of each region of the target slope from the stress evolution curve.

[0010] Preferably, in the dynamic simulation model, different magnitudes of vibration loads are applied to the target slope, and the displacement response characteristics of each anchor rod under different vibration loads are extracted, specifically including: Multiple sets of vibration loads with different amplitudes, frequencies, and durations are set in the dynamic simulation model; Real-time recording of the displacement time history of each anchor bolt under each set of vibration loads; The displacement response characteristics of each anchor rod under different vibration loads are extracted from the displacement time history.

[0011] Preferably, determining the simulation granularity of local stress simulation in the dynamic simulation model based on the stress distribution structure of each region of the target slope and the deformation vector field specifically includes: The stability of the stress change in each region of the target slope is determined based on the stress distribution structure of each region and the deformation vector field. The simulation granularity of local force simulation in the dynamic simulation model is determined by the smoothness of force changes in each region.

[0012] Secondly, this application provides a dynamic modeling system for slope support anchor reinforcement combination, including: The model building module is used to establish a dynamic simulation model of anchor-slope dynamic coupling based on the geological parameters of the target slope and the topology of the anchor layout in the anchor reinforcement combination. The processing module is used to determine the correlation coefficient of the anchor-slope response characteristics between different monitoring points based on the anchor stress conditions and surrounding soil deformation information at different monitoring points in the slope support operation stage. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients to obtain the stress distribution structure of each area of ​​the target slope. The processing module is also used to load different magnitudes of vibration loads onto the target slope in the dynamic simulation model, thereby extracting the displacement response characteristics of each anchor under different vibration loads, and determining the deformation vector field of the anchor reinforcement combination in slope support under different vibration loads by mapping the displacement response characteristics and soil deformation under different vibration loads. The execution module is used to determine the simulation granularity of the local stress simulation in the dynamic simulation model based on the stress distribution structure of each area of ​​the target slope and the deformation vector field, and then adjust the discretization level of the dynamic simulation model based on the simulation granularity.

[0013] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described dynamic modeling method for slope support anchor reinforcement combination.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described dynamic modeling method for slope support anchor reinforcement combination.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: In this embodiment, a dynamic simulation model of anchor-slope dynamic coupling is established based on the geological parameters of the target slope and the topology of the anchor arrangement in the anchor reinforcement combination. During the slope support operation phase, the correlation coefficients of the anchor-slope response characteristics between different monitoring points are determined according to the anchor stress conditions and surrounding soil deformation information at different monitoring points in the target slope. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients to obtain the stress distribution structure of each region of the target slope. Different magnitudes of vibration loads are applied to the target slope in the dynamic simulation model, and the displacement response characteristics of each anchor under different vibration loads are extracted. The deformation vector field of the anchor reinforcement combination in the slope support under different vibration loads is determined by the mapping relationship between all displacement response characteristics and soil deformation under different vibration loads. The simulation granularity of the local stress simulation in the dynamic simulation model is determined according to the stress distribution structure of each region of the target slope and the deformation vector field, and the discretization level of the dynamic simulation model is adjusted based on the simulation granularity.

[0016] Therefore, this application determines the simulation granularity of local stress simulation in the dynamic simulation model by determining the stress distribution structure of each region of the target slope and the deformation vector field of the anchor reinforcement combination in the slope support under different vibration loads. Then, based on the simulation granularity, the discretization level of the dynamic simulation model is adjusted. First, by combining the correlation coefficient of the anchor-slope response characteristics between different monitoring points with the dynamic simulation model, the stress evolution process of the target slope is dynamically inverted, obtaining the stress distribution structure of each region of the target slope. Based on the correlation coefficient of the monitoring point data analysis, the response characteristics between each monitoring point are dynamically inverted during the slope support operation stage, thus accurately reflecting the stress evolution process of the slope under complex working conditions. This avoids the shortcomings of traditional methods that rely on simplified assumptions and empirical data, enabling precise characterization of stress distribution in different regions and providing a more reliable basis for support design. Then, by loading different vibration loads into the dynamic simulation model and extracting the displacement response characteristics of the anchors and the soil deformation mapping relationship, the anchor reinforcement combination under different vibration loads can be effectively constructed. By analyzing the deformation vector field under load, a deeper understanding of the slope deformation characteristics under different load conditions can be achieved. This dynamic modeling method based on the deformation vector field not only enhances the predictive ability of the slope support system under extreme loads but also provides a comprehensive perspective on the dynamic interaction between the anchor bolts and the soil, thereby significantly improving the accuracy and safety of the support design. Finally, based on the stress distribution structure and deformation vector field of each region of the target slope, the simulation granularity of the local stress simulation in the dynamic simulation model is determined. Then, the discretization level of the dynamic simulation model is adjusted based on the simulation granularity. By adaptively adjusting the simulation granularity, the simulation accuracy can be dynamically optimized for different regions of the slope support model according to the stress distribution structure and deformation characteristics. This solves the problem that traditional static analysis methods are difficult to model in detail in local areas, thus making the adjustment of the simulation granularity highly consistent with the actual working conditions and further improving the overall simulation accuracy of the simulation model. In summary, the proposed solution can achieve adaptive adjustment of the local discretization level in the anchor bolt reinforcement combination simulation model, thereby improving the overall simulation accuracy of the simulation model. Attached Figure Description

[0017] Figure 1 This is an exemplary flowchart of a dynamic modeling method for slope support anchor reinforcement combination according to some embodiments of this application; Figure 2 This is a schematic diagram of the monitoring point arrangement according to some embodiments of this application; Figure 3 This is a flowchart illustrating the determination of the deformation vector field according to some embodiments of this application; Figure 4 This is a structural schematic diagram of a dynamic modeling system for slope support anchor reinforcement combination according to some embodiments of this application; Figure 5 This is a structural schematic diagram of a computer device for implementing a dynamic modeling method for slope support anchor reinforcement combination, as shown in some embodiments of this application. Detailed Implementation

[0018] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] refer to Figure 1 The figure is an exemplary flowchart of a dynamic modeling method for slope support anchor reinforcement combination according to some embodiments of this application. The dynamic modeling method 100 for slope support anchor reinforcement combination mainly includes the following steps: In step 101, a dynamic simulation model of anchor-slope dynamic coupling is established based on the geological parameters of the target slope and the topology of the anchor arrangement in the anchor reinforcement combination.

[0020] It should be noted that slope protection refers to the engineering techniques used to constrain and reinforce the slope soil by setting up engineering measures (such as anchor bolts, shotcrete, and retaining walls) on the slope body, so as to improve the overall stability of the slope, prevent instability such as sliding and collapse, and thus ensure the long-term safe operation of the slope under natural or external forces.

[0021] It should also be noted that the geological parameters in this application refer to various data that characterize the physical and mechanical properties and hydrogeological conditions of the slope soil. They are used to describe the strength, deformation, and permeability behavior of geological materials. Specifically, the geological parameters include: the soil density and void ratio of the target slope, as well as the permeability coefficient of water in the soil. The layout topology in this application refers to the graphical structure used to reflect the distribution of anchor bolts in the slope space and their interconnection relationships.

[0022] In some embodiments, establishing a dynamic simulation model of anchor-slope dynamic coupling based on the geological parameters of the target slope and the topology of the anchor arrangement in the anchor reinforcement combination can be achieved through the following steps: A three-dimensional model of the anchor-slope is constructed based on the three-dimensional data of the target slope and the anchor reinforcement combination. The boundary conditions for the anchor bolt-slope dynamic coupling simulation are determined based on the geological parameters and the layout topology. A dynamic simulation model of anchor bolt-slope dynamic coupling is constructed by combining the three-dimensional model and the boundary conditions using the finite element discretization method.

[0023] It should be noted that the three-dimensional model in this application refers to the three-dimensional geometric model of the anchor bolt and slope; the anchor bolt-slope dynamic coupling simulation in this application refers to the numerical simulation process of simultaneously simulating the mutual force and deformation influence between the anchor bolt and the slope soil under dynamic load; the dynamic simulation model of anchor bolt-slope dynamic coupling in this application refers to the numerical model used to simulate the force and deformation interaction relationship between the anchor bolt and slope under dynamic load.

[0024] In specific implementation, the construction of a 3D model of the anchor-slope based on the 3D data of the target slope and anchor reinforcement combination can be achieved in the following way: 3D data (i.e., spatial 3D point cloud data) of the target slope and anchor reinforcement combination can be collected using laser scanning or UAV aerial surveying technology. This point spatial 3D cloud data can then be converted into a structured 3D geometric model using BIM modeling tools (such as Revit or Rhino), and this 3D geometric model can be used as the 3D model of the anchor-slope. The boundary conditions for the dynamic coupling simulation of the anchor-slope can be determined based on the geological parameters and the layout topology. This can be achieved in the following way: Based on the acquired geological parameters (including the soil density and void ratio of the target slope, and the permeability coefficient of water in the soil) and the topological information corresponding to the number, length, and angle of the anchors, combined with the actual topographic boundary and support conditions of the slope, the boundary conditions for the dynamic coupling simulation of the anchor-slope can be set using finite element software (such as ABAQUS). The constraints, loads, and contact relationships can be clearly defined, ensuring that the simulation model can realistically reflect the actual stress environment. The dynamic simulation model of anchor-slope dynamic coupling, constructed by combining the three-dimensional model and the boundary conditions using the finite element discretization method, can be achieved as follows: The three-dimensional model is divided into high-quality mesh elements based on the finite element discretization method, and anchor-soil coupling elements are added (the coupling elements refer to numerical simulation elements that realize the mechanical coupling relationship between the anchor and soil by setting the contact interface properties between the anchor and soil (such as friction coefficient and bond strength)). By setting the contact properties of the anchor-soil interface, time integration is performed using the Newmark-beta integration method. The coupled simulation model constructed in the above manner is then used as the dynamic simulation model of anchor-slope dynamic coupling. This dynamic simulation model can simulate the force transmission and mutual influence process between the anchor and the slope in real time, reflecting the dynamic response characteristics of the slope system under different working conditions.

[0025] It should also be noted that the process of setting boundary conditions in this application also includes setting the shear modulus, Poisson's ratio, and damping ratio of the soil and anchor rods, which can be obtained by consulting relevant technical materials and will not be elaborated here.

[0026] In step 102, during the slope support operation phase, the correlation coefficients of the anchor bolt-slope response characteristics between different monitoring points are determined based on the anchor bolt stress conditions and surrounding soil deformation information at different monitoring points in the target slope. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients, and the stress distribution structure of each area of ​​the target slope is obtained.

[0027] In some embodiments, reference Figure 2 As shown in the figure, this figure is a structural schematic diagram of the monitoring point layout in some embodiments of this application. In this embodiment, the monitoring point layout is based on the layout topology of the anchor reinforcement combination. The monitoring points are distributed in the anchor head and the soil deformation area around the anchor. The sensors at the monitoring points realize comprehensive real-time monitoring of the anchor stress, soil deformation and overall slope stability.

[0028] In some embodiments, the correlation coefficient of the anchor-slope response characteristics between different monitoring points can be determined based on the anchor stress at different monitoring points in the target slope and the deformation information of the surrounding soil, using the following steps: Select a monitoring point as the target monitoring point, and obtain the stress data of the anchor rod and the deformation data of the surrounding soil at the target monitoring point; Extract the force response characteristics of the anchor bolt from the force data of the anchor bolt; Extract the deformation response characteristics of the surrounding soil from the deformation data of the surrounding soil; Based on the stress response characteristics and the deformation response characteristics, determine the anchor bolt-slope response characteristics of the target monitoring point, and continue to determine the anchor bolt-slope response characteristics of the remaining monitoring points; Determine the Spearman correlation coefficient of the anchor bolt-slope response characteristics among different monitoring points; The correlation coefficients of the anchor-slope response characteristics between different monitoring points were determined by using all Spearman correlation coefficients.

[0029] It should be noted that the force data in this application refers to the mechanical data of tensile, compressive, and shear forces borne by the anchor at different monitoring points, collected by sensors; the deformation data in this application refers to the displacement information data of the soil structure at different monitoring points, collected by sensors; the force response characteristics in this application are the mechanical characteristics that quantify the force response state of the anchor; the deformation response characteristics in this application are the deformation characteristics that measure the response state of the surrounding soil; the anchor-slope response characteristics in this application refer to the behavioral characteristics of the combined response of the anchor and the surrounding soil under dynamic loads; and the correlation coefficient of the anchor-slope response characteristics in this application is a quantitative index that measures the degree of mutual influence between the anchor and the slope soil at different monitoring points during the stress and deformation process.

[0030] In specific implementation, acquiring the stress data of the anchor rod at the target monitoring point and the deformation data of the surrounding soil can be achieved in the following ways: Stress gauges and displacement gauges can be used to acquire the stress data of the anchor rod and the deformation data of the surrounding soil at the selected target monitoring point in real time; extracting the stress response characteristics of the anchor rod from the stress data can be achieved in the following ways: Feature extraction can be performed on the stress data of the anchor rod based on time series analysis methods, and the extracted peak values, frequencies, and cumulative stresses can be used as the stress response characteristics of the anchor rod; extracting the deformation response characteristics of the surrounding soil from the deformation data can be achieved in the following ways: Displacement amplitude and deformation rate extracted from the deformation data can be used as the deformation response characteristics of the surrounding soil; the target is determined based on the stress response characteristics and the deformation response characteristics. The anchor-slope response characteristics at monitoring points can be achieved as follows: the stress response characteristics and deformation response characteristics can be combined into a vector as the anchor-slope response characteristics of the target monitoring point; the Spearman correlation coefficient of the anchor-slope response characteristics between different monitoring points can be determined as follows: for any two monitoring points, the Spearman correlation coefficient of the anchor-slope response characteristics between the two monitoring points can be used as the Spearman correlation coefficient of the anchor-slope response characteristics between the two monitoring points; the correlation coefficient of the anchor-slope response characteristics between different monitoring points can be determined by using all Spearman correlation coefficients as follows: the Spearman correlation coefficient between every two monitoring points can be used as the correlation coefficient of the anchor-slope response characteristics between every two monitoring points.

[0031] In some embodiments, the dynamic simulation model, combined with all correlation coefficients, is used to dynamically invert the stress evolution process of the target slope to obtain the stress distribution structure of each region of the target slope. This can be achieved through the following steps: Based on all the correlation coefficients, construct a cross-correlation matrix of the anchor-slope response characteristics among different monitoring points; By combining the cross-correlation matrix with the initial stress data of different monitoring points in the target slope, and using the inversion module in the dynamic simulation model, the stress evolution curve of the target slope at different times is calculated by the inversion algorithm. Extract the stress distribution structure of each region of the target slope from the stress evolution curve.

[0032] It should be noted that the cross-correlation matrix in this application is a matrix that quantifies the degree of cross-correlation between anchor bolts and slope soil during the stress and deformation process at different monitoring points; the initial stress data in this application refers to the mechanical data of static tensile force, static compressive force, and static shear force borne by the anchor bolts at the monitoring points under the action of no external dynamic load; the stress evolution curve in this application refers to the curve of the stress state of each area of ​​the slope changing with time; and the stress distribution structure in this application is an index that quantifies the stress state and stress distribution of each area in the slope support simulation model.

[0033] In specific implementation, constructing the cross-correlation matrix of anchor-slope response characteristics among different monitoring points based on all correlation coefficients can be achieved in the following way: The correlation coefficients between all monitoring points can be organized into a matrix, and this matrix can be used as the cross-correlation matrix of anchor-slope response characteristics among different monitoring points. Each element in the cross-correlation matrix represents the degree of correlation between the anchor-slope response characteristics of two monitoring points, and each row or column in the cross-correlation matrix represents the relationship between one monitoring point and other monitoring points. Combining the cross-correlation matrix with the initial stress data of different monitoring points in the target slope, and using the inversion module in the dynamic simulation model to calculate the stress evolution curve of the target slope at different times through the inversion algorithm, can be achieved in the following way: The constructed cross-correlation matrix can be combined with the initial stress data of each monitoring point in the target slope (the initial stress data can be obtained through stress sensors), and then the inversion algorithm in the inversion module can be used to calculate the stress evolution curve of the target slope at different times. The stress state of the target slope at different time steps is inverted using methods such as least squares or genetic algorithms, and the inverted curves are used as the stress evolution curves of the target slope at different times. It should be noted that the inversion module in this application refers to the module that, in the dynamic simulation model, uses the inversion algorithm to infer the stress evolution process of the target slope at different times by inputting initial conditions and initial monitoring data. It should also be noted that the least squares method in this application optimizes the inversion model parameters by minimizing the sum of squared errors between the predicted values ​​and the actual observed values, while the genetic algorithm iteratively optimizes the inversion model parameters by simulating the natural selection process. The stress distribution structure of each region of the target slope can be extracted from the stress evolution curve in the following way: the stress distribution map of each region of the target slope can be extracted from the stress evolution curve by statistical analysis methods, and each stress distribution map is used as the stress distribution structure of each region. The stress distribution structure shows the stress concentration degree of different regions.

[0034] It should be noted that the stress distribution map in this application is extracted from the stress evolution curve using statistical analysis methods. It is a graphical representation of the stress state of each region of the target slope. The stress distribution structure can reflect the stress changes and distribution characteristics of each region of the slope, specifically including stress concentration areas, uniform distribution areas, and potential weak zones. The extraction of the stress distribution map of each region of the target slope from the stress evolution curve using statistical analysis methods can be achieved in the following ways: Statistical methods (such as regression analysis and cluster analysis) can be used to analyze and fit the stress evolution curve to generate the stress distribution of each region of the slope. By extracting the stress distribution map, the spatial distribution characteristics of stress on the slope at different times can be obtained, thus providing a scientific basis for slope reinforcement design and stability assessment. In addition, the application of the stress distribution map can help identify areas of uneven stress on the slope and predict possible landslides or deformation risks, thereby providing decision support for engineering.

[0035] In step 103, different magnitudes of vibration loads are applied to the target slope in the dynamic simulation model, and the displacement response characteristics of each anchor under different vibration loads are extracted. The deformation vector field of the anchor reinforcement combination in the slope support under different vibration loads is determined by the mapping relationship between all displacement response characteristics and soil deformation under different vibration loads.

[0036] In some embodiments, the following steps can be used to extract the displacement response characteristics of each anchor rod under different vibration loads by applying different magnitudes of vibration loads to the target slope in the dynamic simulation model: Multiple sets of vibration loads with different amplitudes, frequencies, and durations are set in the dynamic simulation model; Real-time recording of the displacement time history of each anchor bolt under each set of vibration loads; The displacement response characteristics of each anchor rod under different vibration loads are extracted from the displacement time history.

[0037] It should be noted that the displacement response characteristics in this application are indicators for measuring the strength of the anchor bolt displacement response under different vibration loads.

[0038] In specific implementation, setting multiple sets of vibration loads with different amplitudes, frequencies, and durations in the dynamic simulation model can be achieved in the following way: Multiple sets of vibration loads with different amplitudes, frequencies, and durations are set in the dynamic simulation model, and existing finite element analysis software (such as ABAQUS) is used to simulate the dynamic response of the slope under different vibration loads. Each set of vibration loads can represent different actual working conditions, such as earthquakes or mechanical vibrations. The amplitude, frequency, and duration of the vibrations can be adjusted according to the actual situation to simulate slope behavior under various environments. The dynamic response of each anchor bolt under each set of vibrations is recorded in real time. The displacement-time history under load can be realized in the following way: during the simulation, the displacement-time curve of each anchor is recorded in real time, and the displacement-time curve is used as the displacement-time history of the corresponding anchor under each set of vibration loads. The displacement response characteristics of each anchor under different vibration loads can be extracted from each displacement time history in the following way: the amplitude, frequency characteristics and response time history of the anchor displacement can be extracted from each displacement time history through data analysis methods (such as wavelet transform), and the extracted characteristics (i.e., displacement amplitude, frequency characteristics and response time history) are used as the displacement response characteristics of the corresponding anchor.

[0039] In some embodiments, reference Figure 3 As shown in the figure, this is a flowchart illustrating the process of determining the deformation vector field in some embodiments of this application. In this embodiment, the deformation vector field of the anchor reinforcement combination in slope support under different vibration loads can be determined by the following steps through the mapping relationship between all displacement response characteristics and soil deformation under different vibration loads: In step 1031, the deformation data of the soil in each region under different vibration loads are recorded in the dynamic simulation model, and then the deformation characteristics of the soil in each region under different vibration loads are extracted. In step 1032, the mapping relationship of soil deformation under different vibration loads is determined by the deformation characteristics of soil in each region under different vibration loads. In step 1033, the displacement response characteristics of each anchor rod are associated with the deformation characteristics of the soil region where it is located based on the mapping relationship, thereby determining the deformation vector of each anchor rod under different vibration loads. In step 1034, the deformation vector field of the anchor reinforcement combination in the slope support under different vibration loads is determined by all the deformation vectors.

[0040] It should be noted that the deformation characteristics in this application refer to the deformation state parameter characteristics exhibited by the soil under external loads; the deformation vector in this application is a vector index that quantifies the strength of deformation of the anchor structure under different vibration loads; and the deformation vector field in this application is an index that measures the deformation distribution law of the anchor-reinforced composite structure under external loads.

[0041] In practical implementation, the deformation data of soil in each region under different vibration loads is recorded in the dynamic simulation model, and the deformation characteristics of soil in each region under different vibration loads are extracted. This can be achieved in the following way: Vibration loads of different amplitudes, frequencies, and durations can be applied to the dynamic simulation model, and the nodal displacement data of soil in each region during the simulation process can be recorded. The nodal displacement data refers to the displacement data of the soil around the anchor bolt. The recorded nodal displacement data is used as the deformation data of the corresponding region. Then, time history analysis methods (such as Newmark-β in the direct integration method) are used to extract the principal deformation direction, amplitude, and deformation characteristics of each region under different vibration loads. The deformation trend is analyzed, and the extracted principal deformation direction, displacement amplitude, and trend are used as the deformation characteristics of the soil in the region under different vibration loads. The mapping relationship of soil deformation under different vibration loads can be determined by the following method: Characteristic parameters of different vibration loads (such as amplitude, frequency, and duration) can be used as independent variables; the principal deformation direction, displacement amplitude, and trend (i.e., deformation characteristics) of the soil in each region under the corresponding load can be extracted as dependent variables; a training dataset can be established; and the relationship between the independent and dependent variables can be fitted using the least squares method to obtain a multiple linear regression model. This model is then analyzed using linear regression... The regression model outputs a relationship matrix of soil deformation under different vibration loads. The elements in this matrix represent mapping values ​​for soil deformation under specified vibration loads. This matrix is ​​then used as the mapping relationship for soil deformation under different vibration loads. Based on this mapping relationship, the displacement response characteristics of each anchor are correlated with the deformation characteristics of its corresponding soil region. The deformation vector of each anchor under different vibration loads can be determined as follows: First, based on the spatial positional relationship between the anchor and the soil region in the dynamic simulation model, each anchor is mapped to its corresponding soil region element. Then, the displacement response characteristics of the anchor under different vibration loads are extracted. The deformation characteristics of the soil region corresponding to the anchor are input into the aforementioned multiple linear regression model to obtain the expected deformation characteristics of the anchor under the corresponding vibration load. Finally, using the known principle of vector superposition, the displacement response of the anchor itself is superimposed with the regional deformation characteristic vector, and the superimposed vector information is used as the deformation vector of each anchor under different vibration loads. The deformation vector field of the anchor reinforcement combination in slope support under different vibration loads can be determined by the following method: the deformation vectors of all anchors can be combined into a matrix according to the anchor position information as the deformation vector field of the anchor reinforcement combination in slope support under different vibration loads.

[0042] It should be noted that the vector superposition principle in this application refers to the fact that, under the same coordinate system, the total effect of multiple vectors acting on the same point or the same system is equal to the sum of the individual vectors, and the result is the algebraic sum of each component in its respective direction. Specifically, for multiple force, displacement, or velocity vectors in two-dimensional or three-dimensional space, they are decomposed along the X, Y, and Z axes respectively, and the corresponding components in each direction are added together and then synthesized. The resulting total vector reflects the overall effect. This principle is widely used in structural force analysis and displacement response superposition to describe the comprehensive influence of multiple loads or multi-region deformation on the system.

[0043] In step 104, the simulation granularity of the local stress simulation in the dynamic simulation model is determined based on the stress distribution structure of each region of the target slope and the deformation vector field, and then the discretization level of the dynamic simulation model is adjusted based on the simulation granularity.

[0044] In some embodiments, determining the simulation granularity of local stress simulation in the dynamic simulation model based on the stress distribution structure of each region of the target slope and the deformation vector field can be achieved through the following steps: The stability of the stress change in each region of the target slope is determined based on the stress distribution structure of each region and the deformation vector field. The simulation granularity of local force simulation in the dynamic simulation model is determined by the smoothness of force changes in each region.

[0045] It should be noted that the stability of stress change in this application is an indicator for measuring the stability of stress distribution in different areas of the slope; the simulation granularity in this application refers to the level of detail in the local model space division in numerical simulation.

[0046] In specific implementation, the stability of force changes in each region of the target slope can be determined based on the force distribution structure and the deformation vector field. This can be achieved by aligning all force distribution structures and deformation vector fields according to the regions of the target slope. For each region, the sum of the variance of the corresponding force distribution structure and the variance of the corresponding deformation vector field is taken as the stability of force changes in that region. Here, the variances of the force distribution structure and the deformation vector field are normalized variances. It should be noted that the variances in this application are used to measure the degree of fluctuation in the force distribution structure and deformation vector field of each region of the slope. Specifically, for each region, the force distribution structure of that region is first calculated... The mean of the structure and deformation vector field is calculated, and then the squared difference between each data point and the mean is calculated. The average of all squared differences is then used to obtain the variance. The larger the variance, the more drastic the force change or deformation fluctuation in that region, and vice versa. By calculating the variance of each region, the stability of force and deformation can be quantified, providing a quantitative basis for determining the granularity of local force simulation, thereby optimizing simulation accuracy and computational efficiency. The simulation granularity of local force simulation in the dynamic simulation model can be determined by the stability of force change in each region. This can be achieved by first normalizing the stability of force change in each region, and then using the stability obtained after normalization as the simulation granularity of local force simulation in the corresponding region.

[0047] It should be noted that adjusting the discretization level of the dynamic simulation model based on the simulation granularity in this application refers to setting the corresponding spatial grid density and time step accuracy level according to the fineness of the simulation granularity in each region. This ensures accurate simulation of displacement response in regions with different granularities. Specifically, for fine-grained regions, a higher discretization level is needed to accurately reflect the deformation response of the soil. For example, a denser grid can be used spatially or a smaller time step can be set in time. For coarse-grained regions, a lower discretization level can be used to reduce computation. It should also be noted that the scheme in this application dynamically adjusts the discretization level under different simulation granularities through an adaptive discretization level adjustment strategy. This means that the accuracy of the discretization level changes synchronously with the simulation granularity to ensure that the accuracy of the simulation results in each region is balanced with computational efficiency.

[0048] On the other hand, in some embodiments, this application provides a dynamic modeling system for slope support anchor reinforcement combination, referencing Figure 4 The figure is a schematic diagram of the dynamic modeling system for slope support anchor reinforcement combination according to some embodiments of this application. The dynamic modeling system 400 for slope support anchor reinforcement combination includes: a model building module 401, a processing module 402, and an execution module 403, which are described below: Model building module 401, in this application, is mainly used to establish a dynamic simulation model of anchor-slope dynamic coupling based on the geological parameters of the target slope and the topology of the anchor layout in the anchor reinforcement combination; The processing module 402 in this application is used to determine the correlation coefficient of the anchor-slope response characteristics between different monitoring points in the slope support operation stage based on the anchor stress conditions and surrounding soil deformation information at different monitoring points in the target slope. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients to obtain the stress distribution structure of each area of ​​the target slope. In this application, the processing module 402 is also used to load different magnitudes of vibration loads onto the target slope in the dynamic simulation model, thereby extracting the displacement response characteristics of each anchor under different vibration loads, and determining the deformation vector field of the anchor reinforcement combination in slope support under different vibration loads through the mapping relationship between all displacement response characteristics and soil deformation under different vibration loads. The execution module 403 in this application is mainly used to determine the simulation granularity of the local stress simulation in the dynamic simulation model based on the stress distribution structure of each area of ​​the target slope and the deformation vector field, and then adjust the discretization level of the dynamic simulation model based on the simulation granularity.

[0049] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-described dynamic modeling method for slope support anchor reinforcement combination.

[0050] In some embodiments, reference Figure 5 The figure is a schematic diagram of the structure of a computer device for implementing a dynamic modeling method for slope support anchor reinforcement combination according to some embodiments of this application. The dynamic modeling method for slope support anchor reinforcement combination in the above embodiments can be achieved through... Figure 5 The computer device shown is used to implement this, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0051] Processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0052] The communication bus 502 can be used to transmit information between the aforementioned components.

[0053] Memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 503 may exist independently and be connected to processor 501 via communication bus 502. Memory 503 may also be integrated with processor 501.

[0054] The memory 503 stores program code for executing the scheme of this application, and its execution is controlled by the processor 501. The processor 501 executes the program code stored in the memory 503. The program code may include one or more software modules. In the above embodiments, the dynamic modeling method for slope support anchor reinforcement can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0055] Communication interface 504 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0056] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0057] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0058] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described dynamic modeling method for slope support anchor reinforcement combination.

[0059] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0060] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A dynamic modeling method for combined slope support anchor reinforcement, characterized in that, Includes the following steps: A dynamic simulation model of anchor-slope dynamic coupling is established based on the geological parameters of the target slope and the topology of anchor placement in the anchor reinforcement combination. During the slope support operation phase, the correlation coefficients of the anchor bolt-slope response characteristics between different monitoring points are determined based on the anchor bolt stress conditions and surrounding soil deformation information at different monitoring points in the target slope. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients, and the stress distribution structure of each area of ​​the target slope is obtained. Specifically, by combining all correlation coefficients with the dynamic simulation model, the stress evolution process of the target slope is dynamically inverted, and the stress distribution structure of each region of the target slope is obtained, including: Based on all the correlation coefficients, construct a cross-correlation matrix of the anchor-slope response characteristics among different monitoring points; By combining the cross-correlation matrix with the initial stress data of different monitoring points in the target slope, and using the inversion module in the dynamic simulation model, the stress evolution curve of the target slope at different times is calculated by the inversion algorithm. Extract the force distribution structure of each region of the target slope from the force evolution curve; In the dynamic simulation model, different magnitudes of vibration loads are applied to the target slope, and the displacement response characteristics of each anchor under different vibration loads are extracted. The deformation vector field of the anchor reinforcement combination in slope support under different vibration loads is determined by the mapping relationship between all displacement response characteristics and soil deformation under different vibration loads. Based on the stress distribution structure of each region of the target slope and the deformation vector field, the simulation granularity of the local stress simulation in the dynamic simulation model is determined, and then the discretization level of the dynamic simulation model is adjusted based on the simulation granularity.

2. The method as described in claim 1, characterized in that, A dynamic simulation model of anchor-slope dynamic coupling is established based on the geological parameters of the target slope and the topology of anchor placement in the anchor reinforcement combination. Specifically, it includes: A three-dimensional model of the anchor-slope is constructed based on the three-dimensional data of the target slope and the anchor reinforcement combination. The boundary conditions for the anchor bolt-slope dynamic coupling simulation are determined based on the geological parameters and the layout topology. A dynamic simulation model of anchor bolt-slope dynamic coupling is constructed by combining the three-dimensional model and the boundary conditions using the finite element discretization method.

3. The method as described in claim 2, characterized in that, Three-dimensional data of the target slope and anchor reinforcement combination were acquired using laser scanning equipment.

4. The method as described in claim 1, characterized in that, The correlation coefficients of the anchor-slope response characteristics between different monitoring points are determined based on the anchor stress conditions at different monitoring points in the target slope and the deformation information of the surrounding soil. Specifically, this includes: Select a monitoring point as the target monitoring point, and obtain the stress data of the anchor rod and the deformation data of the surrounding soil at the target monitoring point; Extract the force response characteristics of the anchor bolt from the force data of the anchor bolt; Extract the deformation response characteristics of the surrounding soil from the deformation data of the surrounding soil; Based on the stress response characteristics and the deformation response characteristics, determine the anchor bolt-slope response characteristics of the target monitoring point, and continue to determine the anchor bolt-slope response characteristics of the remaining monitoring points; Determine the Spearman correlation coefficient of the anchor bolt-slope response characteristics among different monitoring points; The correlation coefficients of the anchor-slope response characteristics between different monitoring points were determined by using all Spearman correlation coefficients.

5. The method as described in claim 1, characterized in that, In the dynamic simulation model, different magnitudes of vibration loads are applied to the target slope, and the displacement response characteristics of each anchor rod under different vibration loads are extracted. Specifically, this includes: Multiple sets of vibration loads with different amplitudes, frequencies, and durations are set in the dynamic simulation model; Real-time recording of the displacement time history of each anchor bolt under each set of vibration loads; The displacement response characteristics of each anchor rod under different vibration loads are extracted from the displacement time history.

6. The method as described in claim 1, characterized in that, The simulation granularity of the local stress simulation in the dynamic simulation model is determined based on the stress distribution structure of each region of the target slope and the deformation vector field, specifically including: The stability of the stress change in each region of the target slope is determined based on the stress distribution structure of each region and the deformation vector field. The simulation granularity of local force simulation in the dynamic simulation model is determined by the smoothness of force changes in each region.

7. A dynamic modeling system for slope support anchor reinforcement combination, which uses the method described in any one of claims 1 to 6 to perform dynamic modeling of slope support anchor reinforcement combination, characterized in that, The system includes: The model building module is used to establish a dynamic simulation model of anchor-slope dynamic coupling based on the geological parameters of the target slope and the topology of the anchor layout in the anchor reinforcement combination. The processing module is used to determine the correlation coefficient of the anchor-slope response characteristics between different monitoring points based on the anchor stress conditions and surrounding soil deformation information at different monitoring points in the slope support operation stage. Then, the dynamic simulation model is used to dynamically invert the stress evolution process of the target slope by combining all the correlation coefficients to obtain the stress distribution structure of each area of ​​the target slope. The processing module is also used to load different magnitudes of vibration loads onto the target slope in the dynamic simulation model, thereby extracting the displacement response characteristics of each anchor under different vibration loads, and determining the deformation vector field of the anchor reinforcement combination in slope support under different vibration loads by mapping the displacement response characteristics and soil deformation under different vibration loads. The execution module is used to determine the simulation granularity of the local stress simulation in the dynamic simulation model based on the stress distribution structure of each area of ​​the target slope and the deformation vector field, and then adjust the discretization level of the dynamic simulation model based on the simulation granularity.

8. A computer device comprising a memory and a processor, the memory storing code, characterized in that, The processor is configured to acquire the code and execute the dynamic modeling method for slope support anchor reinforcement combination as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the dynamic modeling method for slope support anchor reinforcement combination as described in any one of claims 1 to 6.

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