Methods and Systems for Stability Analysis of Lock Chamber Slopes

Abstract

This application provides a method and system for analyzing the stability of a lock chamber slope, relating to the field of slope stability analysis technology. The method includes: constructing a three-dimensional finite element analysis model corresponding to the lock chamber using the finite element method based on geological and hydrological information of the lock chamber area and the current status information of the lock chamber slope; simulating the response of the lock chamber slope under different working conditions using numerical simulation based on the three-dimensional finite element analysis model and a set of design parameters for various working conditions; constructing a model knowledge graph corresponding to the three-dimensional finite element analysis model; comparing the response data and monitoring data at the same monitoring point based on the model knowledge graph to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements; and analyzing the stability of the lock chamber slope under different working conditions to obtain the stability analysis results of the lock chamber slope. This application improves the accuracy of the stability analysis results.

Description

Technical Field

[0001] This application relates to the field of slope stability analysis technology, and in particular to a method and system for analyzing the stability of a lock chamber slope. Background Technology

[0002] Ship locks are crucial facilities for inland waterway transportation, and the stability of the lock chamber walls is essential for operational safety. During the excavation of the lock chamber foundation, changes in the geological conditions of the base and slopes affect quality and safety. With the development of the shipping industry, ship locks are used frequently and have high load-bearing requirements, necessitating expansion and renovation to reinforce the lock chamber slopes and ensure long-term safety.

[0003] Traditional slope stability analysis methods mostly rely on empirical formulas or simplified two-dimensional models. While these methods are simple and easy to implement, they often neglect the influence of complex geological conditions and actual working conditions, making it difficult to provide sufficiently accurate stability analysis results. This stability analysis not only provides the slope performance in its unreinforced state but also shows the changes brought about by various possible reinforcement measures (such as anti-slide piles), reflecting the effectiveness of anti-slide pile reinforcement to a certain extent. In recent years, with the advancement of computer technology and numerical simulation methods, the finite element analysis method has gradually become an effective tool for solving such problems. It can more realistically reflect the mechanical behavior of the slope and its surrounding environment by establishing a three-dimensional model, thus providing a more reliable basis for engineering decisions.

[0004] However, existing technologies rely on manual operation for many steps from model building to result analysis. Manual intervention is not only time-consuming and labor-intensive, but also prone to introducing subjective errors, which affects the quality of the final stability analysis results. Summary of the Invention

[0005] The present invention aims to provide a method and system for analyzing the stability of lock chamber slopes, in order to solve the problem of low accuracy of stability analysis results in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for analyzing the stability of a lock chamber slope, including:

[0007] Obtain information on the expansion and renovation project of the lock chamber, the geological and hydrological information of the area where the lock chamber is located, and the current status of the lock chamber slope;

[0008] Based on the geological and hydrological information of the area where the lock chamber is located, as well as the current status information of the lock chamber slope, a three-dimensional finite element analysis model corresponding to the lock chamber is constructed using the finite element analysis method.

[0009] Based on the information of the expansion and renovation project of the lock chamber, design parameter sets for various working conditions are determined. Based on the three-dimensional finite element analysis model and the design parameter sets for various working conditions, numerical simulation calculation method is used to simulate the response of the lock chamber slope under different working conditions, and the response dataset of the lock chamber slope under different working conditions is obtained. The response dataset includes the response data of each monitoring point on the lock chamber slope.

[0010] A model knowledge graph corresponding to a three-dimensional finite element analysis model is constructed. The nodes in the model knowledge graph are monitoring points, and the node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationship between the nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements.

[0011] With the accuracy of the three-dimensional finite element analysis model meeting the preset accuracy requirements, the stability of the lock chamber slope under different working conditions is analyzed based on the response dataset of the lock chamber slope under different working conditions, and the stability analysis results of the lock chamber slope are obtained.

[0012] Optionally, the step of constructing a three-dimensional finite element analysis model corresponding to the lock chamber using the finite element analysis method based on the geological and hydrological information of the area where the lock chamber is located, and the current status information of the lock chamber slope, includes:

[0013] The first feature is extracted from the geological and hydrological information of the area where the lock chamber is located, and the second feature is extracted from the current information of the lock chamber slope. The first feature includes: stratigraphic structure, groundwater level distribution and soil properties. The second feature includes: slope morphology features, slope surface features, existing slope reinforcement measures and surrounding environmental conditions of the slope.

[0014] Based on the geological structure and groundwater level distribution, and combining decision tree algorithm and rule-based expert system, the spatial range and boundary conditions of the lock chamber are constructed to obtain a preliminary model framework. Batch processing technology is used to add the soil properties to the corresponding areas in the preliminary model framework to obtain a preliminary model with soil properties.

[0015] The slope morphology, slope surface features, existing slope reinforcement measures, and surrounding environmental conditions are incorporated into the preliminary model to obtain the intermediate model.

[0016] The intermediate model was meshed using the finite element analysis method to obtain a three-dimensional finite element analysis model corresponding to the lock chamber.

[0017] Optionally, based on the geological structure and groundwater level distribution, and combining a decision tree algorithm and a rule-based expert system, the spatial extent and boundary conditions of the lock chamber are constructed to obtain a preliminary model framework, including:

[0018] By combining information gain, a third feature for distinguishing different geological conditions is extracted from the stratigraphic structure and groundwater level distribution;

[0019] Based on the third feature, an initial decision tree model corresponding to the lock chamber is constructed using a decision tree algorithm. The initial decision tree model is then pruned using a pruning strategy to obtain the processed decision tree model.

[0020] By combining the spatial range and configuration rules of the first condition obtained from the rule-based expert system, the spatial range and boundary conditions of the lock chamber are constructed. Based on the spatial range and boundary conditions of the lock chamber, the processed decision tree model is optimized to obtain a preliminary model framework.

[0021] Optionally, the step of using the finite element analysis method to mesh the intermediate model to obtain a three-dimensional finite element analysis model corresponding to the lock chamber includes:

[0022] Identify key regions of the lock chamber slope in the intermediate model, including the top, middle, and bottom regions;

[0023] Obtain the grid configuration information for key areas, including grid type and grid size. Different key areas correspond to different grid configuration information.

[0024] Based on the grid configuration information, the corresponding key area is divided into multiple grids. Based on the grid quality index, the quality of all grids is verified. If the quality verification results of all grids indicate that they meet the grid quality standards, a discretized intermediate model is obtained. The grid quality index includes the grid's shape regularity, aspect ratio, distortion, density rationality, and smoothness.

[0025] Boundary conditions and loads are applied to the discretized intermediate model to obtain the three-dimensional finite element analysis model corresponding to the lock chamber.

[0026] Optionally, based on the three-dimensional finite element analysis model and the design parameter set for various working conditions, a numerical simulation method is used to simulate the response of the lock chamber slope under different working conditions, obtaining a response dataset of the lock chamber slope under different working conditions. The response dataset includes response data from various monitoring points on the lock chamber slope, including:

[0027] Define multiple working conditions and design parameter sets for multiple working conditions. The multiple working conditions include: a first working condition for simulating the impact of water level changes on slope stability, and a second working condition for simulating the impact of adding anti-slide piles on slope stability.

[0028] For each working condition, the three-dimensional finite element analysis model is locally optimized according to the characteristics of the working condition. The local optimization includes at least one of mesh optimization, soil property optimization, and boundary condition optimization. The locally optimized part of the optimized three-dimensional finite element analysis model is verified. If the verification passes, the monitoring point type and monitoring point location are determined based on the working condition characteristics and the project requirements in the expansion and renovation project information. Based on the optimized three-dimensional finite element analysis model and the design parameter set of the working condition, the response of each monitoring point on the lock chamber slope under the working condition is simulated using numerical simulation calculation method to obtain the response data of each monitoring point on the lock chamber slope. The response data of each monitoring point on the lock chamber slope is used as the response dataset of the lock chamber slope under the working condition.

[0029] Optionally, determining the monitoring point type and location based on the operating condition characteristics and project requirements in the expansion and renovation project information includes:

[0030] Based on the aforementioned working conditions, and combined with the topographic map and geological profile in the three-dimensional finite element analysis model, the areas of interest and monitoring point types on the lock chamber slope are determined.

[0031] Based on the project requirements in the expansion and renovation project information, and combined with the distribution of the areas of concern, terrain features, and construction impact areas, a genetic algorithm is used to determine the location of monitoring points. The location of a monitoring point is the position of the monitoring point in the area of ​​concern. The fitness function in the genetic algorithm is designed based on the size of the coverage area of ​​the monitoring point, the rationality of the distance between monitoring points, and the coverage repetition rate.

[0032] Optionally, the step of comparing response data and monitoring data at the same monitoring point based on the model knowledge graph to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements includes:

[0033] Based on the model knowledge graph, the monitoring point type of each monitoring point is identified, and the preset threshold corresponding to the monitoring point type is obtained. The monitoring point types include: groundwater level monitoring point, horizontal displacement monitoring point and vertical settlement monitoring point.

[0034] Calculate the mean square error between the response data and the monitoring data at the same monitoring point. If the mean square error between the response data and the monitoring data at all monitoring points on the lock chamber slope is less than or equal to the corresponding preset threshold, then the accuracy of the three-dimensional finite element analysis model is determined to meet the preset accuracy requirements.

[0035] Secondly, embodiments of this application provide a system for analyzing the stability of a lock chamber slope, comprising:

[0036] The acquisition module is used to acquire information on the expansion and renovation project of the lock chamber, the geological and hydrological information of the area where the lock chamber is located, and the current status information of the lock chamber slope.

[0037] The construction module is used to construct a three-dimensional finite element analysis model corresponding to the lock chamber based on the geological and hydrological information of the area where the lock chamber is located and the current status information of the lock chamber slope using the finite element analysis method.

[0038] The simulation module is used to determine the design parameter set for multiple working conditions based on the information of the expansion and renovation project of the lock chamber. Based on the three-dimensional finite element analysis model and the design parameter set for multiple working conditions, the numerical simulation calculation method is used to simulate the response of the lock chamber slope under different working conditions, and the response dataset of the lock chamber slope under different working conditions is obtained. The response dataset includes the response data of each monitoring point on the lock chamber slope.

[0039] A comparison module is constructed to build a model knowledge graph corresponding to the three-dimensional finite element analysis model. The nodes in the model knowledge graph are monitoring points, and the node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationship between the nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements.

[0040] The analysis module is used to analyze the stability of the lock chamber slope under different working conditions based on the response dataset of the lock chamber slope under different working conditions, provided that the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, and to obtain the stability analysis results of the lock chamber slope.

[0041] Thirdly, embodiments of this application provide a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are to be invoked and executed by the processing component to implement a method for analyzing the stability of a lock chamber slope as described in any of the first aspects.

[0042] Fourthly, embodiments of this application provide a computer storage medium storing a computer program, which, when executed by a computer, implements a method for analyzing the stability of a lock chamber slope as described in any of the first aspects.

[0043] This application provides a method for analyzing the stability of a lock chamber slope, comprising: acquiring information on the lock chamber expansion and renovation project, geological and hydrological information of the area where the lock chamber is located, and current status information of the lock chamber slope; based on the geological and hydrological information of the area where the lock chamber is located and the current status information of the lock chamber slope, constructing a three-dimensional finite element analysis model corresponding to the lock chamber using the finite element analysis method; determining a set of design parameters for various working conditions based on the lock chamber expansion and renovation project information; and simulating the response of the lock chamber slope under different working conditions using numerical simulation calculation methods based on the three-dimensional finite element analysis model and the set of design parameters for various working conditions, thereby obtaining a dataset of the lock chamber slope response under different working conditions. The response dataset includes response data from various monitoring points on the lock chamber slope. A model knowledge graph corresponding to the three-dimensional finite element analysis model is constructed. Nodes in the model knowledge graph represent monitoring points, and node attributes include monitoring point type, response data, and monitoring data. Edges represent the relationships between nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements. If the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, the stability of the lock chamber slope under different working conditions is analyzed based on the response dataset of the lock chamber slope under different working conditions, and the stability analysis results of the lock chamber slope are obtained.

[0044] This application embodiment ensures a comprehensive consideration of influencing factors by acquiring and integrating information on the expansion and renovation project, geological and hydrological information, and current slope status information, thus avoiding biases caused by simplification assumptions in traditional methods. This application embodiment utilizes the finite element analysis method to construct a detailed three-dimensional finite element analysis model, which can more realistically reflect the mechanical behavior of the slope and its surrounding environment, improving prediction accuracy. By constructing a model knowledge graph, using monitoring points as nodes, and comparing response data with actual monitoring data, the accuracy of the three-dimensional finite element analysis model is effectively verified, thereby ensuring the accuracy of the stability analysis results.

[0045] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart of a method for analyzing the stability of a lock chamber slope is provided in this application embodiment;

[0048] Figure 2 An exemplary lock chamber dimension diagram provided for embodiments of this application;

[0049] Figure 3 An exemplary settlement cloud map of a lock chamber provided for embodiments of this application;

[0050] Figure 4 An exemplary horizontal displacement cloud map of a lock chamber provided for embodiments of this application;

[0051] Figure 5 A cloud map of an exemplary potential sliding surface provided for embodiments of this application;

[0052] Figure 6 A comparison chart between simulated data and actual monitoring data of groundwater level provided for an embodiment of this application;

[0053] Figure 7 A comparison chart between simulated data and actual monitoring data for horizontal displacement provided in an embodiment of this application;

[0054] Figure 8 This application provides a comparison chart of data before and after reinforcement.

[0055] Figure 9 A schematic diagram showing the cumulative horizontal and vertical displacement of the slope after anti-slide pile reinforcement, as provided in the embodiments of this application.

[0056] Figure 10 A schematic diagram of a lock chamber slope stability analysis system provided in this application embodiment;

[0057] Figure 11 This is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0058] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0059] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 11, 12, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0060] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0061] Figure 1 A flowchart of a method for analyzing the stability of a lock chamber slope provided in this application embodiment is shown below. Figure 1 As shown, the method includes:

[0062] S11. Obtain information on the expansion and renovation project of the lock chamber, the geological and hydrological information of the area where the lock chamber is located, and the current status information of the lock chamber slope.

[0063] It should be understood that expansion and renovation project information can refer to the specific planning and technical requirements for the expansion or upgrade of the lock chamber, including but not limited to the purpose, scale, engineering design drawings, construction plan, and expected increase in throughput capacity. This information guides how to improve upon the existing structure to ensure that the new structure meets future usage needs. Geological and hydrological information can refer to specific geological information, including stratigraphic structure, soil properties, and groundwater conditions. Soil properties can include model material parameters (including natural density, water content, etc.) and model material strength parameters (such as cohesion c and internal friction angle φ). Groundwater conditions can refer to hydraulic parameters (such as compressibility coefficient, permeability coefficient, etc.). This type of information is the basis for assessing slope stability and selecting appropriate reinforcement measures.

[0064] In this embodiment, the lock chamber slope can be simply referred to as the slope. The current status information of the lock chamber slope can refer to the slope's morphological characteristics (e.g., height, angle), surface condition (e.g., presence and size of cracks), existing state, and surrounding environmental conditions. The existing state is either reinforced or unreinforced. When the existing state is reinforced, the current status information of the lock chamber slope also includes existing reinforcement measures. These existing reinforcement measures can refer to the existing reinforcement measures adopted when the lock chamber slope is in a reinforced state (e.g., existing anti-slide piles or other support structures). This data helps identify potential risk points and provides a practical background for the construction of the three-dimensional finite element model.

[0065] S12. Based on the geological and hydrological information of the area where the lock chamber is located, as well as the current status information of the lock chamber slope, a three-dimensional finite element analysis model corresponding to the lock chamber is constructed using the finite element analysis method.

[0066] It should be understood that the finite element method (FEM) can discretize a complex lock chamber into a finite number of meshes, and then approximate the response of the entire system through the mechanical behavior of each mesh. In the construction process of this application, more intelligent algorithms can be introduced to combine with the FEM, reducing manual operation, avoiding subjective errors, and improving the efficiency of the three-dimensional FEM model. A three-dimensional FEM model can refer to a detailed digital representation that considers not only stress and strain in the horizontal direction but also variations in the vertical direction, thus more accurately reflecting the three-dimensional spatial structure of the lock chamber in the real world. This three-dimensional FEM model is used to simulate the mechanical properties of the lock chamber and its slopes under various conditions.

[0067] S13. Based on the information of the expansion and renovation project of the lock chamber, determine the design parameter set for multiple working conditions. Based on the three-dimensional finite element analysis model and the design parameter set for multiple working conditions, use numerical simulation calculation method to simulate the response of the lock chamber slope under different working conditions, and obtain the response dataset of the lock chamber slope under different working conditions. The response dataset includes the response data of each monitoring point on the lock chamber slope.

[0068] It should be understood that a working condition refers to the state of the lock chamber slope under specific conditions. Each working condition corresponds to a specific set of design parameters used to define factors such as loading conditions and boundary conditions. The design parameter set is a set of specific values ​​or rules used to describe the working environment and mechanical characteristics of the lock chamber and its slope under specific working conditions, such as water level, temperature changes, and external loads.

[0069] In practical applications, numerical simulation calculation methods can be implemented by calling modules. For example, the seep / w (seepage analysis), sigma / w (stress deformation analysis), and slope / w (slope stability analysis) modules in geotechnical engineering and environmental geotechnical engineering simulation analysis software can be used to calculate the groundwater flow, stress distribution, and safety factor of the lock chamber slope at each monitoring point.

[0070] It should also be understood that the response dataset can refer to a series of results obtained from the numerical simulation process, which records the performance of the lock chamber slope under different working conditions, especially the key indicators (such as displacement, stress, strain, etc.) at each monitoring point.

[0071] S14. Construct a model knowledge graph corresponding to the three-dimensional finite element analysis model. The nodes in the model knowledge graph are monitoring points. The node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationships between nodes. Based on the model knowledge graph, compare the response data and monitoring data of the same monitoring point to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements.

[0072] It should be understood that a model knowledge graph is a graphical representation method that treats monitoring points as nodes, connects them with relationships (edges), and assigns node attributes (such as monitoring point type, response data, and monitoring data). This approach helps to intuitively understand the relationships between data and supports advanced data analysis.

[0073] It should also be understood that monitoring point types are used to capture specific types of physical quantities, such as groundwater level, horizontal displacement, and vertical settlement. Response data is derived from simulation calculations and reflects the slope behavior predicted by the three-dimensional finite element analysis model. Monitoring data comes from field measurements and provides a true picture of the slope response.

[0074] S15. If the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, the stability of the lock chamber slope under different working conditions is analyzed based on the response dataset of the lock chamber slope under different working conditions, and the stability analysis results of the lock chamber slope are obtained.

[0075] It should be understood that the preset accuracy requirement can refer to a pre-set standard or threshold used to determine whether the difference between the simulation results (i.e., response data) and the actual situation (i.e., monitoring data) is within an acceptable range. The stability analysis results can comprehensively evaluate the safety and reliability of the lock chamber slope under different working conditions, and may include key indicators such as horizontal displacement, settlement rate, safety factor, and maximum allowable deformation.

[0076] This application embodiment can obtain the horizontal displacement, settlement rate, and safety factor of each monitoring point on the slope in the unreinforced state. For working condition 2, this application embodiment can also obtain the horizontal displacement, settlement rate, and safety factor of each monitoring point on the slope in the reinforced state. By comparing the differences in data before and after reinforcement, such as changes in horizontal displacement, settlement rate, and safety factor, the quantitative effect of anti-slide pile reinforcement can be obtained. For example, the horizontal displacement of the slope after reinforcement is significantly reduced, especially in the secondary slope section where the horizontal displacement is reduced by about 66.7%, while the settlement rate in the slope top area is reduced by about 140%. The safety factor of the slope after reinforcement, for example, increases to 1.85, far exceeding the critical value.

[0077] By executing steps S11 to S15, this embodiment acquires and integrates information on the expansion and renovation project, geological and hydrological information, and current slope status information, ensuring a comprehensive consideration of influencing factors and avoiding deviations caused by simplification assumptions in traditional methods. This embodiment utilizes the finite element analysis method to construct a detailed three-dimensional finite element analysis model, which can more realistically reflect the mechanical behavior of the slope and its surrounding environment, improving prediction accuracy. A model knowledge graph is constructed, using monitoring points as nodes, and by comparing response data with actual monitoring data, the accuracy of the three-dimensional finite element analysis model is effectively verified, thereby ensuring the accuracy of the stability analysis results.

[0078] In one possible embodiment, S12, based on the geological and hydrological information of the area where the lock chamber is located, and the current status information of the lock chamber slope, a three-dimensional finite element analysis model corresponding to the lock chamber is constructed using the finite element analysis method, including:

[0079] Step 121: Extract the first feature from the geological and hydrological information of the area where the lock chamber is located, and extract the second feature from the current status information of the lock chamber slope. The first feature includes: stratigraphic structure, groundwater level distribution and soil properties. The second feature includes: slope morphology, slope surface features, existing slope reinforcement measures and surrounding environmental conditions.

[0080] Among these, stratigraphic structure is used to identify the location, thickness, and distribution of different soil and rock layers, determine the impact of underground structures on slope stability, and help identify potential sliding surfaces or unstable areas. A potential sliding surface refers to a hypothetical or actual interface in a slope or soil structure that may form and lead to soil sliding due to factors such as geological processes, climatic conditions, engineering construction, and vibration loads. It is the path along which shear failure may occur during slope instability, and relative displacement may occur along this surface. Potential sliding surfaces can be planar, arc-shaped, polygonal, or other complex shapes, depending on geological conditions and stress distribution. Groundwater level distribution can determine the height of the groundwater level and its seasonal variation trend. Soil properties include natural density, water content, cohesion (c), and angle of internal friction. wait.

[0081] Slope morphological features describe the slope's geometry, including height, angle, and length, which are then used to construct an accurate three-dimensional finite element analysis model, ensuring the realism and reliability of the data simulation. Slope surface features record the slope surface condition, such as the presence of cracks, spalling, or other anomalies, helping to identify potential risk points and providing a basis for selecting reinforcement measures. Existing slope reinforcement measures refer to the location and specifications of existing anti-slide piles, anchors, and other reinforcement facilities, allowing this application embodiment to consider the existing reinforcement effects, optimize the new design, and evaluate its long-term performance. Surrounding environmental conditions of the slope refer to the impact of nearby buildings and other factors on the slope, ensuring that the design scheme takes external factors into account and avoids potential adverse effects during construction.

[0082] The embodiments of this application can extract the first feature and the second feature through feature extraction techniques, including convolutional neural networks, generative adversarial networks, edge detection networks, feature point detection networks, principal component analysis, clustering methods, etc.

[0083] Step 122: Based on the geological structure and groundwater level distribution, and combining the decision tree algorithm and rule-based expert system, construct the spatial range and boundary conditions of the lock chamber to obtain a preliminary model framework. Use batch processing technology to add soil properties to the corresponding areas in the preliminary model framework to obtain a preliminary model with soil properties.

[0084] It should be understood that decision tree algorithms use a recursive segmentation strategy to establish an initial decision tree model for automatically selecting the key features that best distinguish different geological conditions, simplifying the modeling process. Rule-based expert systems can combine knowledge of the lock chamber slope domain to formulate corresponding configuration rules, guiding how to construct the spatial extent and boundary conditions of the lock chamber. Batch processing technology is an automated data processing method that can efficiently complete the task of adding soil properties without human intervention, reducing human error and accelerating modeling speed.

[0085] As one possible implementation, in step 122, based on the geological structure and groundwater level distribution, and combining a decision tree algorithm and a rule-based expert system, the spatial extent and boundary conditions of the lock chamber are constructed to obtain a preliminary model framework, including:

[0086] Step a1: Combining information gain, extract a third feature from the stratigraphic structure and groundwater level distribution to distinguish different geological conditions. It should be understood that the greater the information gain, the more important the corresponding feature is in classifying or distinguishing different situations. By calculating the information gain of each feature, selecting the key feature that most effectively distinguishes different geological conditions can simplify the subsequent analysis process. The third feature may be a specific stratigraphic type, the trend of groundwater level changes, etc., serving as the basis for constructing the initial decision tree model to ensure that the model can accurately capture the key features affecting slope stability.

[0087] Step a2: Based on the third feature, a decision tree algorithm is used to construct an initial decision tree model corresponding to the lock chamber. A pruning strategy is then applied to prune the initial decision tree model to obtain a processed decision tree model. It should be understood that the decision tree algorithm creates a tree structure by recursively splitting the dataset. Each node represents a test condition, each branch represents a possible outcome, and the leaf nodes represent the final classification or prediction result. This is used to automatically select the key features that best distinguish different geological conditions, simplifying the modeling process and providing intuitive rule explanations. Pruning strategies can be implemented through pre-pruning (stopping tree growth early) or post-pruning (generating a complete tree first and then pruning), improving the model's generalization ability and ensuring good performance on unseen data, avoiding overfitting to the training data. Compared to the initial decision tree model, the processed decision tree model simplifies the model structure and improves computational efficiency and prediction accuracy.

[0088] Step a3: Combining the spatial range and configuration rules of the first condition obtained from the rule-based expert system, construct the spatial range and boundary conditions of the lock chamber. Based on the spatial range and boundary conditions of the lock chamber, optimize the processed decision tree model to obtain the preliminary model framework.

[0089] It should be understood that the configuration rules for the spatial scope and the first condition specifically define the location, size, and boundary conditions (such as fixed end, free end, etc.) of the lock chamber in three-dimensional space, ensuring a reasonable spatial layout and correct boundary condition settings, thereby improving the realism and reliability of the simulation results. The preliminary model framework is a semi-finished model formed by integrating the rules provided by the decision tree model and the expert system. It includes the basic spatial structure and boundary conditions, but detailed material properties and other details have not yet been added.

[0090] By executing steps a1 to a3, this embodiment of the application achieves automated feature selection based on information gain evaluation and decision tree algorithms, reducing manual intervention and improving the efficiency and quality of model construction. Combining expert system rules ensures that the model is not only data-driven but also incorporates domain-specific knowledge and experience, enhancing its reliability and applicability. Pruning strategies optimize the decision tree model, avoiding overfitting caused by excessive model complexity and improving its generalization ability on unknown data. Rule settings based on the expert system ensure the accuracy of the model's spatial range and boundary conditions, providing a solid foundation for subsequent finite element analysis.

[0091] Step 123: Integrate the slope morphology, surface features, existing reinforcement measures, and surrounding environmental conditions into the preliminary model to obtain the intermediate model. It should be understood that the intermediate model is a semi-finished model formed after preliminary feature extraction and processing, providing a foundation for further refinement and optimization, and ensuring the integrity and accuracy of the final model.

[0092] Step 124: Using the finite element method, mesh the intermediate model to obtain a three-dimensional finite element analysis model corresponding to the lock chamber. It should be understood that meshing refers to discretizing the intermediate model representing the continuous lock chamber into a finite number of meshes, ensuring that the mechanical behavior on each mesh can be accurately simulated, thereby approximating the response of the entire system.

[0093] As one possible implementation, step 124 involves using the finite element analysis method to mesh the intermediate model, obtaining a three-dimensional finite element analysis model corresponding to the lock chamber, including:

[0094] Step b1: Identify the key regions of the lock chamber slope in the intermediate model. These key regions include the top, middle, and bottom. The key regions refer to the parts of the slope that are of significant importance, such as the top (which may bear large horizontal forces), the middle (stress concentration zone), and the bottom (foundation support zone). The mechanical behavior of these regions has a significant impact on the overall stability. Therefore, it is crucial to focus on these regions during mesh generation to improve simulation accuracy.

[0095] Step b2: Obtain the mesh configuration information for the key region. This information includes mesh type and mesh size, with different mesh configurations for different key regions. The mesh configuration information describes how a continuous physical domain is discretized into a finite number of meshes. Mesh types include tetrahedrons, hexahedrons, etc. Different mesh types are suitable for different geometries and stress distributions. In this embodiment, the mesh type best suited to the shape and mechanical properties of the key region is selected, which can improve simulation accuracy. Mesh size can refer to the mesh area. Key regions require finer meshes to capture local details; setting the mesh size appropriately ensures sufficient resolution to reflect their complex behavior. This embodiment can select a suitable mesh configuration based on the different characteristics of the key region to ensure computational efficiency and result accuracy.

[0096] Step b3: Based on the mesh configuration information, divide the corresponding key regions into multiple meshes. Verify the quality of all meshes based on mesh quality indicators. If the quality verification results of all meshes indicate that they meet the mesh quality standards, a discretized intermediate model is obtained. Mesh quality indicators are a series of standards for measuring mesh quality and applicability, including mesh shape regularity, aspect ratio, distortion, density rationality, and smoothness. These ensure that the generated mesh is not only geometrically correct but also suitable for numerical computation, avoiding inaccurate or unstable results due to mesh quality issues. Shape regularity is used to evaluate whether the mesh is close to an ideal geometric shape, such as a square or cube, to ensure the stability and accuracy of the numerical solution. Aspect ratio refers to the ratio of the longest side to the shortest side of the mesh. Limiting the aspect ratio can prevent excessively long or short cells, improving computational efficiency and result reliability. Distortion measures the degree to which the mesh deviates from the ideal shape; reducing distortion helps maintain the stability of the numerical solution. Density rationality ensures a reasonable spatial distribution of mesh cell density, especially in key regions, improving the ability to capture local details while avoiding unnecessary waste of computational resources. Smoothness is used to evaluate whether the transition between adjacent grid cells is smooth, avoid abrupt changes, and ensure the continuity and stability of numerical solutions.

[0097] Step b4: Apply boundary conditions and loads to the discretized intermediate model to obtain the three-dimensional finite element analysis model corresponding to the lock chamber. Boundary conditions specify the constraints at the model edges, such as fixed ends, free ends, and displacement limits, ensuring the model accurately reflects the stress conditions in the actual engineering environment. Loads are external forces or pressures applied to the model, such as water pressure, self-weight, and construction loads, simulating various external forces borne by the slope under actual working conditions.

[0098] By executing steps b1 to b4, this embodiment of the application accurately identifies key areas and configures reasonable mesh parameters. Combined with rigorous mesh quality verification and scientific boundary conditions and load application, it ensures efficient conversion from the intermediate model to the three-dimensional finite element analysis model, improving the model's accuracy and reliability. This provides a more accurate and reliable basis for slope stability analysis. This method not only optimizes the mesh generation process and improves computational efficiency but also enhances the model's adaptability to complex working conditions, ultimately achieving accurate assessment and effective prediction of the stability of the lock chamber slope.

[0099] By executing steps 121 to 124, this embodiment of the application combines decision tree algorithm and rule-based expert system to achieve intelligent model construction, improving model construction efficiency and quality. A detailed three-dimensional finite element analysis model is constructed, more realistically reflecting the mechanical behavior of the slope and its surrounding environment, thus improving prediction accuracy.

[0100] In one possible embodiment, in S13, based on a three-dimensional finite element analysis model and a set of design parameters for various working conditions, a numerical simulation method is used to simulate the response of the lock chamber slope under different working conditions, obtaining a response dataset of the lock chamber slope under different working conditions. The response dataset includes response data from various monitoring points on the lock chamber slope, including:

[0101] Step 131: Define multiple working conditions and design parameter sets for multiple working conditions. The multiple working conditions include: the first working condition for simulating the impact of water level changes on slope stability, and the second working condition for simulating the impact of adding anti-slide piles on slope stability.

[0102] For example, Case 1: a 6-day periodic water level rise and fall, used to simulate the impact of water level changes (such as floods and dry seasons) on slope stability; periodic water level changes can mimic groundwater level fluctuations caused by rainfall, snowmelt, or other natural phenomena in the real environment. Through this simulation, researchers can analyze the impact of water level changes on slope stability, including but not limited to landslide risk, changes in soil saturation, and possible slope deformation.

[0103] Scenario 2: After reinforcing the lock chamber slope with anti-slide piles, a one-month evaluation of slope stability and the effectiveness of the reinforcement was conducted. Under this scenario, the embodiments of this application can monitor and record the behavior of the lock chamber slope under different conditions, such as stress distribution and deformation, and compare it with the state before reinforcement. Furthermore, the embodiments of this application can also focus on whether the anti-slide piles effectively enhance the slope's resistance to sliding, and the performance of the anti-slide piles throughout the testing period. These data help verify the effectiveness of the reinforcement design.

[0104] Step 132. For each working condition, execute the following process: Step c1. Based on the characteristics of the working condition, perform local optimization on the three-dimensional finite element analysis model. Local optimization includes at least one of mesh optimization, soil property optimization, and boundary condition optimization. Step c2. Verify the locally optimized part of the optimized three-dimensional finite element analysis model. If the verification passes, proceed to step c3. Step c3. Based on the characteristics of the working condition and the project requirements in the expansion and renovation project information, determine the monitoring point type and monitoring point location. Step c4. Based on the optimized three-dimensional finite element analysis model and the design parameter set of the working condition, use numerical simulation calculation methods to simulate the response of each monitoring point on the lock chamber slope under the working condition, and obtain the response data of each monitoring point on the lock chamber slope. Step c5. Use the response data of each monitoring point on the lock chamber slope as the response dataset of the lock chamber slope under the working condition.

[0105] It should be understood that local optimization refers to adjustments made to parts of a three-dimensional finite element analysis model to improve its accuracy and computational efficiency. Mesh optimization can refer to adjusting the mesh configuration, such as changing the mesh size, type, or distribution, to better capture local details, improve the resolution of key areas, and ensure the accuracy of the numerical solution. Soil property optimization can refer to adjusting the physical and mechanical parameters of the soil according to the working conditions, such as natural density, internal friction angle, and cohesion, so that the optimized three-dimensional finite element analysis model can more accurately reflect the actual soil behavior, especially the changes under different working conditions. Boundary condition optimization refers to modifying the constraint conditions at the edge of the model to ensure that the optimized three-dimensional finite element analysis model truly reflects the stress state in the actual engineering environment, especially under complex working conditions. In this application embodiment, after performing local optimization, the optimized three-dimensional finite element analysis model is checked to see if it meets the expected standards and requirements, ensuring its rationality and applicability. By determining the monitoring point type and location, this application embodiment can select the monitoring indicators that best reflect the slope behavior, ensuring the validity of the data, ensuring that potential risk points can be captured in a timely manner, and providing effective early warning and decision support. By simulating design parameter sets under various working conditions, researchers can better understand slope performance under different scenarios, thereby optimizing design schemes and ensuring safety. Numerical simulation methods are used to predict the response of lock chamber slopes.

[0106] Specifically, step c3, based on the operating conditions and project requirements in the expansion and renovation project information, determines the monitoring point type and location, including:

[0107] Step c31: Based on the characteristics of the working conditions, and combining the topographic map and geological profile in the three-dimensional finite element analysis model, determine the areas of concern and monitoring point types on the lock chamber slope. The topographic map is a graphical representation of the surface undulations, which may include contour lines, slope information, etc., to help identify key topographic features of the slope, such as steep or gentle areas, to determine potential risk points. For potential risk points, this embodiment can set corresponding reinforcement measures. The geological profile is a vertical cross-sectional view showing the distribution of underground soil and rock layers and their physical and mechanical properties, used to reveal the internal structure of the slope, especially the location of weak interlayers, fault zones, etc., to guide the selection of monitoring points. Areas of concern can refer to slope sections that require special attention under specific working conditions, such as stress concentration areas, vulnerable areas, etc. Determining areas of concern ensures that this embodiment concentrates monitoring resources on the most likely areas to have problems, improving the early warning effect. Monitoring point types are used to capture specific types of physical quantities, such as groundwater level monitoring points, horizontal displacement monitoring points, vertical settlement monitoring points, etc.

[0108] Step c32: Based on the project requirements in the expansion and renovation project information, and combined with the distribution of the areas of interest, terrain features, and construction impact areas, a genetic algorithm is used to determine the locations of monitoring points. The location of a monitoring point is its position within the area of ​​interest. The fitness function in the genetic algorithm is designed based on the size of the monitoring point's coverage area, the reasonableness of the distance between monitoring points, and the coverage overlap rate. The genetic algorithm is an optimization algorithm based on natural selection and genetic mechanisms, simulating the biological evolution process to find the optimal solution for monitoring point locations. Coverage area refers to the spatial range that a single monitoring point can effectively monitor. The reasonableness of the distance between monitoring points is used to evaluate whether the distance between monitoring points is appropriate—neither too dense nor too sparse—to ensure that the monitoring point layout provides sufficient detail without wasting resources. The coverage overlap rate is used to evaluate the degree of overlap between the coverage areas of multiple monitoring points.

[0109] By executing steps c31 and c32, this embodiment of the application accurately locates the area of ​​interest by combining topographic maps and geological profiles, and intelligently selects monitoring point locations using a genetic algorithm, ensuring a reasonable layout of the monitoring system. This method not only improves the accuracy and coverage of monitoring point placement but also optimizes resource allocation, reduces unnecessary duplicate monitoring, thereby enhancing the real-time monitoring capability and early warning accuracy of slope dynamic changes, and providing support for engineering safety.

[0110] By executing steps 131 and 132, this embodiment defines various working conditions and performs targeted local optimization and verification, ensuring that the three-dimensional finite element analysis model can accurately reflect the actual behavior of the slope under different conditions. This method not only improves the accuracy and reliability of the model but also enhances its adaptability to complex working conditions, thereby achieving a comprehensive assessment and effective prediction of the stability of the lock chamber slope. Ultimately, this process provides a technical basis for engineering design, ensuring the smooth implementation and long-term safe operation of the expansion and renovation project.

[0111] In one possible embodiment, in S14, based on the model knowledge graph, the response data and monitoring data at the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, including:

[0112] Step 141: Based on the model knowledge graph, identify the monitoring point type of each monitoring point and obtain the preset threshold corresponding to the monitoring point type. The monitoring point types include: groundwater level monitoring points, horizontal displacement monitoring points, and vertical settlement monitoring points. In other embodiments, the monitoring point types may also include: tilt monitoring points, crack monitoring points, stress-strain monitoring points, temperature monitoring points, seepage monitoring points, etc. Among them, tilt monitoring points are used to monitor the tilt degree of the slope or a certain area of ​​the slope to ensure its safety. Crack monitoring points are set at locations where cracks may occur to monitor the development of cracks. Stress-strain monitoring points are installed inside or on the surface of the slope to monitor the stress and strain borne by the slope and assess the health status of the slope. Temperature monitoring points are used to monitor changes in ambient temperature or the internal temperature of a specific object (such as dam concrete) to prevent damage caused by thermal stress. Seepage monitoring points are used to monitor the flow of water through the soil or rock medium.

[0113] Step 142: Calculate the mean square error between the response data and the monitoring data at the same monitoring point. If the mean square error between the response data and the monitoring data at all monitoring points on the lock chamber slope is less than or equal to the corresponding preset threshold, then the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements. If not, apply an online learning algorithm to automatically adjust the three-dimensional finite element analysis model until the adjusted model accurately reflects the mechanical behavior of the slope.

[0114] By executing steps 141 and 142, this embodiment of the application accurately matches the monitoring point type and calculates the mean square error value, improving the verification accuracy and reliability of the three-dimensional finite element analysis model. This method not only ensures that the model can truly reflect the actual behavior of the slope, but also provides technical support for engineering design, construction, and long-term monitoring, enhancing its adaptability to complex working conditions, and ultimately achieving accurate assessment and effective prediction of the stability of the lock chamber slope. This process greatly optimizes resource allocation, improves work efficiency, and provides a guarantee for the smooth implementation and long-term safe operation of the project.

[0115] In practical applications, the depth of the first-line ship lock chamber in a certain area is 13 meters, and it is 80 meters away from the centerline of the currently operating second-line ship lock chamber. Geological exploration indicates that an old river channel diagonally crosses the first-line ship lock, and the deepest layer of silty clay in the old river channel is approximately 9.5 meters thick. Approximately 100 meters of slope needs to be reinforced with anti-slide piles (such as cast-in-place piles). This old river channel has a significant impact on the expansion and renovation of the first-line ship lock chamber and the stability of the lock chamber slope. The engineering design drawings obtained in this application include a cross-sectional view of the first-line ship lock chamber. Based on the cross-sectional view of the first-line ship lock chamber, the results are obtained through geotechnical engineering and environmental geotechnical engineering simulation analysis software. Figure 2 The diagram shows the dimensions of the lock chamber. In this diagram, 1a represents silty clay, 1b represents plain fill, 1c represents miscellaneous fill, 2-1 represents one layer of silty clay, 2-1a represents another layer of silty clay, and 4-1 represents the reinforcement zone.

[0116] Based on geological survey data, the model parameters are determined as shown in Table 1. The model parameters include: model material parameters (including natural density, water content, etc.), model material strength parameters (such as cohesion c and internal friction angle φ), and groundwater conditions can refer to hydraulic parameters (such as compressibility coefficient, permeability coefficient, etc.).

[0117] Table 1 Model Parameters

[0118]

[0119] Based on the model parameters, this application embodiment constructs a three-dimensional finite element analysis model. Then, the following operations are performed in sequence: (1) Perform steady-state analysis, specifically, determine the initial seepage field based on the water level of the first lock chamber; (2) Solve the initial stress field in situ; (3) Perform fluid-structure interaction analysis on the slope stress change; (4) Use the limit balance valve to search for potential sliding surfaces and set reinforcement loads.

[0120] In actual working conditions, two anti-slide piles of two different specifications were installed. The anti-slide pile for the secondary slope platform was a cast-in-place pile with a specification of Φ1200@1.3m and a pile length of 24.4m, while the other was a cast-in-place pile with a specification of Φ1500@1.6m and a pile length of 24.4m.

[0121] Simulation conditions: Condition 1, lasting 6 days, with the water level rising at a rate of 0.5 m / d, rising for 2 days, maintaining for 2 days, and falling for 2 days, simulating the impact of water level changes on slope stability; Condition 2, lasting one month, simulating the stability of the reinforced slope, analyzing the reinforcement effect of anti-slide piles, and evaluating the safety of the slope.

[0122] After the numerical simulation was completed, the following results were obtained: Figure 3 The settlement cloud diagram of the lock chamber shown is as follows: Figure 4 The horizontal displacement cloud diagram of the lock chamber shown, and as follows Figure 5 The cloud map shown is of the potential sliding surface.

[0123] according to Figures 3 to 5 The various cloud maps shown indicate that the settlement is greatest at the top of the slope, while the horizontal displacement is most significant in the secondary slope section. The potential sliding surface is mainly located in the deep soil layer, posing a possibility of overall sliding. The hazard factor on the potential sliding surface reaches 1.086, almost equal to the critical value of 1. It is recommended to install anti-slide piles on the slope to enhance its anti-slide stability.

[0124] Based on the aforementioned cloud maps, in order to accurately obtain monitoring data, this embodiment of the application may install settlement displacement monitoring points (hereinafter referred to as displacement monitoring points) and groundwater level monitoring points on the eastern slope of the middle section of the lock chamber and nearby buildings. The displacement monitoring points are located at the top of the slope, the secondary slope, and the top of the sheet piles; the groundwater level monitoring points are located at the top of the slope and the secondary slope, totaling two points.

[0125] To achieve consistency evaluation between monitoring data and simulated data, this embodiment uses the mean square error (MSE) value as an indicator. The smaller the MSE value, the closer the simulated data (i.e., response data) is to the actual monitoring data, and the higher the accuracy of the three-dimensional finite element analysis model. Therefore, this embodiment can set a preset threshold of 0.1, that is, the reasonable range of the MSE value is (0, 0.1).

[0126] The formula for calculating the mean squared error is as follows:

[0127]

[0128] Where MSE represents the mean squared error, n represents the total number of data points, and y i This represents the actual test data, indicating the true value of the sample, y. i ′ represents simulated data, indicating the predicted value of the sample.

[0129] Figure 6 An exemplary comparison chart of simulated and actual monitoring data for groundwater levels is provided. The chart shows a mean squared error (MSE) of 0.051, which is within a reasonable range. Figure 7An exemplary comparison chart of simulated and actual monitoring data for horizontal displacement is provided, involving multiple horizontal displacement monitoring points: the top of the slope, the secondary slope, and the top of the sheet pile. Through... Figure 7 It can be seen that the horizontal displacement trends at each monitoring point are consistent, and the simulated data are close to the actual monitoring data. The mean square error values ​​of the horizontal displacement at the top of the slope, the secondary slope, and the top of the sheet pile are 0.09205, 0.08659, and 0.0912, respectively, all within a reasonable range. Therefore, it can be proved that the accuracy of the three-dimensional finite element analysis model is high, and the accuracy of the numerical simulation method is also high.

[0130] pass Figure 8 This embodiment compares the actual monitoring data with the simulated data for condition 2. The comparison shows that the reinforced slope stability is significantly improved, and the horizontal displacement is significantly reduced, decreasing by approximately 66.7% in the secondary slope section. The anti-slide piles enhance stability. Settlement is reduced, decreasing by approximately 140% in the slope crest area, demonstrating a significant control effect. The safety factor increases from 1.02 to over 1.5, indicating that the reinforcement measures improve slope safety.

[0131] pass Figure 9 It can be seen that the future cumulative displacement of the slope crest is greatly affected by rainfall or sudden rises in water level, so it is recommended to increase drainage during heavy rainfall. The settlement at the slope toe is also greatly affected by rainfall, so it is recommended to add drainage ditches at the slope toe to prevent rainwater accumulation and reduce erosion and softening of the slope toe.

[0132] Figure 10 A schematic diagram of a lock chamber slope stability analysis system provided in this application embodiment is shown below. Figure 10 As shown, the system includes:

[0133] The acquisition module 101 is used to acquire information on the expansion and renovation project of the lock chamber, the geological and hydrological information of the area where the lock chamber is located, and the current status information of the lock chamber slope.

[0134] Module 102 is used to construct a three-dimensional finite element analysis model corresponding to the lock chamber based on the geological and hydrological information of the area where the lock chamber is located, as well as the current status information of the lock chamber slope, using the finite element analysis method.

[0135] The simulation module 103 is used to determine the design parameter set for various working conditions based on the information of the expansion and renovation project of the lock chamber. Based on the three-dimensional finite element analysis model and the design parameter set for various working conditions, the numerical simulation calculation method is used to simulate the response of the lock chamber slope under different working conditions, and obtain the response dataset of the lock chamber slope under different working conditions. The response dataset includes the response data of each monitoring point on the lock chamber slope.

[0136] A comparison module 104 is constructed to build a model knowledge graph corresponding to the three-dimensional finite element analysis model. The nodes in the model knowledge graph are monitoring points, and the node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationship between the nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements.

[0137] Analysis module 105 is used to analyze the stability of the lock chamber slope under different working conditions based on the response dataset of the lock chamber slope under different working conditions, provided that the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, and to obtain the stability analysis results of the lock chamber slope.

[0138] Figure 10 The aforementioned lock chamber slope stability analysis system can perform... Figure 1 The implementation principle and technical effects of the lock chamber slope stability analysis method described in the illustrated embodiment will not be repeated here. The specific operation methods of each module and unit in the lock chamber slope stability analysis system in the above embodiments have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0139] In one possible design, Figure 10 The lock chamber slope stability analysis system of the embodiment shown can be implemented as a computing device, such as... Figure 11 As shown, the computing device may include a storage component 111 and a processing component 112.

[0140] The storage component 111 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 112.

[0141] The processing component 112 is used to: acquire information on the expansion and renovation project of the lock chamber, geological and hydrological information of the area where the lock chamber is located, and current status information of the lock chamber slope; based on the geological and hydrological information of the area where the lock chamber is located and the current status information of the lock chamber slope, construct a three-dimensional finite element analysis model corresponding to the lock chamber using the finite element analysis method; determine a set of design parameters for various working conditions according to the expansion and renovation project information of the lock chamber; and, based on the three-dimensional finite element analysis model and the set of design parameters for various working conditions, simulate the response of the lock chamber slope under different working conditions using numerical simulation calculation methods to obtain a response dataset of the lock chamber slope under different working conditions, the response dataset including the lock... The response data of each monitoring point on the lock chamber slope are collected. A model knowledge graph corresponding to the three-dimensional finite element analysis model is constructed. The nodes in the model knowledge graph are monitoring points, and the node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationships between nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements. If the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, the stability of the lock chamber slope under different working conditions is analyzed based on the response dataset of the lock chamber slope under different working conditions, and the stability analysis results of the lock chamber slope are obtained.

[0142] The processing component 112 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0143] Storage component 111 is configured to store various types of data to support operations at the terminal. The storage component can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as Random Access Memory (RAM), Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0144] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0145] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0146] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0147] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0148] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The embodiment shown illustrates a method for analyzing the stability of the lock chamber slope.

[0149] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0150] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0151] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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 this application.

Claims

1. A method for analyzing the stability of a lock chamber slope, characterized in that, include: Obtain information on the expansion and renovation project of the lock chamber, the geological and hydrological information of the area where the lock chamber is located, and the current status of the lock chamber slope; Based on the geological and hydrological information of the area where the lock chamber is located, as well as the current status information of the lock chamber slope, a three-dimensional finite element analysis model corresponding to the lock chamber is constructed using the finite element analysis method. Based on the information of the expansion and renovation project of the lock chamber, design parameter sets for various working conditions are determined. Based on the three-dimensional finite element analysis model and the design parameter sets for various working conditions, numerical simulation calculation method is used to simulate the response of the lock chamber slope under different working conditions, and the response dataset of the lock chamber slope under different working conditions is obtained. The response dataset includes the response data of each monitoring point on the lock chamber slope. A model knowledge graph corresponding to a three-dimensional finite element analysis model is constructed. The nodes in the model knowledge graph are monitoring points, and the node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationship between the nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements. Under the premise that the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, the stability of the lock chamber slope under different working conditions is analyzed based on the response dataset of the lock chamber slope under different working conditions, and the stability analysis results of the lock chamber slope are obtained. The process of constructing a three-dimensional finite element analysis model corresponding to the lock chamber using the finite element analysis method includes: The first feature is extracted from the geological and hydrological information of the area where the lock chamber is located, and the second feature is extracted from the current information of the lock chamber slope. The first feature includes: stratigraphic structure, groundwater level distribution and soil properties. The second feature includes: slope morphology features, slope surface features, existing slope reinforcement measures and surrounding environmental conditions of the slope. Based on the geological structure and groundwater level distribution, and combining decision tree algorithm and rule-based expert system, the spatial range and boundary conditions of the lock chamber are constructed to obtain a preliminary model framework. Batch processing technology is used to add the soil properties to the corresponding areas in the preliminary model framework to obtain a preliminary model with soil properties. The slope morphology, slope surface features, existing slope reinforcement measures, and surrounding environmental conditions are incorporated into the preliminary model to obtain the intermediate model. The intermediate model was meshed using the finite element analysis method to obtain a three-dimensional finite element analysis model corresponding to the lock chamber.

2. The method according to claim 1, characterized in that, Based on the geological structure and groundwater level distribution, and combining decision tree algorithm and rule-based expert system, the spatial range and boundary conditions of the lock chamber are constructed to obtain a preliminary model framework, including: By combining information gain, a third feature for distinguishing different geological conditions is extracted from the stratigraphic structure and groundwater level distribution; Based on the third feature, an initial decision tree model corresponding to the lock chamber is constructed using a decision tree algorithm. The initial decision tree model is then pruned using a pruning strategy to obtain the processed decision tree model. By combining the spatial range and configuration rules of the first condition obtained from the rule-based expert system, the spatial range and boundary conditions of the lock chamber are constructed. Based on the spatial range and boundary conditions of the lock chamber, the processed decision tree model is optimized to obtain a preliminary model framework.

3. The method according to claim 1, characterized in that, The intermediate model is meshed using the finite element analysis method to obtain a three-dimensional finite element analysis model corresponding to the lock chamber, including: Identify key regions of the lock chamber slope in the intermediate model, including the top, middle, and bottom regions; Obtain the grid configuration information for key areas, including grid type and grid size. Different key areas correspond to different grid configuration information. Based on the grid configuration information, the corresponding key area is divided into multiple grids. Based on the grid quality index, the quality of all grids is verified. If the quality verification results of all grids indicate that they meet the grid quality standards, a discretized intermediate model is obtained. The grid quality index includes the grid's shape regularity, aspect ratio, distortion, density rationality, and smoothness. Boundary conditions and loads are applied to the discretized intermediate model to obtain the three-dimensional finite element analysis model corresponding to the lock chamber.

4. The method according to claim 1, characterized in that, Based on the aforementioned three-dimensional finite element analysis model and a set of design parameters for various working conditions, numerical simulation methods are used to simulate the response of the lock chamber slope under different working conditions, resulting in a response dataset of the lock chamber slope under different working conditions. The response dataset includes response data from various monitoring points on the lock chamber slope, including: Define multiple working conditions and design parameter sets for multiple working conditions. The multiple working conditions include: a first working condition for simulating the impact of water level changes on slope stability, and a second working condition for simulating the impact of adding anti-slide piles on slope stability. For each working condition, the three-dimensional finite element analysis model is locally optimized according to the characteristics of the working condition. The local optimization includes at least one of mesh optimization, soil property optimization, and boundary condition optimization. The locally optimized part of the optimized three-dimensional finite element analysis model is verified. If the verification passes, the monitoring point type and monitoring point location are determined based on the working condition characteristics and the project requirements in the expansion and renovation project information. Based on the optimized three-dimensional finite element analysis model and the design parameter set of the working condition, the response of each monitoring point on the lock chamber slope under the working condition is simulated using numerical simulation calculation method to obtain the response data of each monitoring point on the lock chamber slope. The response data of each monitoring point on the lock chamber slope is used as the response dataset of the lock chamber slope under the working condition.

5. The method according to claim 4, characterized in that, The determination of monitoring point types and locations based on the operating condition characteristics and project requirements in the expansion and renovation project information includes: Based on the aforementioned working conditions, and combined with the topographic map and geological profile in the three-dimensional finite element analysis model, the areas of interest and monitoring point types on the lock chamber slope are determined. Based on the project requirements in the expansion and renovation project information, and combined with the distribution of the areas of concern, terrain features, and construction impact areas, a genetic algorithm is used to determine the location of monitoring points. The location of a monitoring point is the position of the monitoring point in the area of ​​concern. The fitness function in the genetic algorithm is designed based on the size of the coverage area of ​​the monitoring point, the rationality of the distance between monitoring points, and the coverage repetition rate.

6. The method according to claim 1, characterized in that, The method of comparing response data and monitoring data at the same monitoring point based on the model knowledge graph to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements includes: Based on the model knowledge graph, the monitoring point type of each monitoring point is identified, and the preset threshold corresponding to the monitoring point type is obtained. The monitoring point types include: groundwater level monitoring point, horizontal displacement monitoring point and vertical settlement monitoring point. Calculate the mean square error between the response data and the monitoring data at the same monitoring point. If the mean square error between the response data and the monitoring data at all monitoring points on the lock chamber slope is less than or equal to the corresponding preset threshold, then the accuracy of the three-dimensional finite element analysis model is determined to meet the preset accuracy requirements.

7. A system for analyzing the stability of a lock chamber slope, characterized in that, This system is used to implement the method for analyzing the stability of the lock chamber slope as described in any one of claims 1-6, and the system includes: The acquisition module is used to acquire information on the expansion and renovation project of the lock chamber, the geological and hydrological information of the area where the lock chamber is located, and the current status information of the lock chamber slope. The construction module is used to construct a three-dimensional finite element analysis model corresponding to the lock chamber based on the geological and hydrological information of the area where the lock chamber is located and the current status information of the lock chamber slope using the finite element analysis method. The simulation module is used to determine the design parameter set for multiple working conditions based on the information of the expansion and renovation project of the lock chamber. Based on the three-dimensional finite element analysis model and the design parameter set for multiple working conditions, the numerical simulation calculation method is used to simulate the response of the lock chamber slope under different working conditions, and the response dataset of the lock chamber slope under different working conditions is obtained. The response dataset includes the response data of each monitoring point on the lock chamber slope. A comparison module is constructed to build a model knowledge graph corresponding to the three-dimensional finite element analysis model. The nodes in the model knowledge graph are monitoring points, and the node attributes include monitoring point type, response data, and monitoring data. The edges represent the relationship between the nodes. Based on the model knowledge graph, the response data and monitoring data of the same monitoring point are compared to determine whether the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements. The analysis module is used to analyze the stability of the lock chamber slope under different working conditions based on the response dataset of the lock chamber slope under different working conditions, provided that the accuracy of the three-dimensional finite element analysis model meets the preset accuracy requirements, and to obtain the stability analysis results of the lock chamber slope.

8. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement the method for analyzing the slope stability of a lock chamber as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements a method for analyzing the stability of a lock chamber slope as described in any one of claims 1-6.

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