Geometric and mechanical characteristic fused side slope twinborn model construction method and device

Abstract

The invention provides a side slope twinborn model construction method and device fusing geometric and mechanical characteristics, and relates to the technical field of geological modeling. The method comprises the following steps: acquiring geometric features and mechanical features; constructing a first plane unit according to the first geometric feature, and detecting an intersection condition according to the second geometric feature so as to carry out topological optimization to obtain a second plane unit; determining a key geological interface in the excavation area according to the third geometric feature, and determining a key subspace and a non-key subspace; generating a first space unit in the key subspace according to the feature points, dividing the non-key subspace into a second space unit, and performing local optimization to obtain a third space unit; determining the mechanical characteristics of the third space unit according to the position relationship between the third space unit and the body node and the mechanical characteristics of the body node; and based on the mechanical characteristics of the second plane unit, the third space unit and the third space unit, constructing a side slope twinborn model. According to the invention, the quality of slope modeling is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of geological modeling, and in particular to a method and device for constructing a slope twin model integrating geometric and mechanical features. Background Art

[0002] Slopes are slopes with a certain inclination and are common geological structures in engineering projects such as dams, hydropower stations, and mines. Digital modeling of slopes is crucial for stability assessment, risk warning, and scientific management.

[0003] However, most related technologies suffer from low-quality slope modeling. For example, current slope modeling is generally based on static survey data. If dynamic conditions such as excavation exist within the slope, the digital model cannot accurately represent the characteristics of the excavated area, hindering the tracking and monitoring of the slope's dynamic conditions. Summary of the Invention

[0004] The present disclosure provides a method, apparatus, computer program product, and electronic device for constructing a slope twin model that integrates geometric and mechanical features, thereby improving, at least to a certain extent, the problem of low slope modeling quality in related technologies.

[0005] According to a first aspect of the present disclosure, a method for constructing a twin model of a slope that integrates geometric and mechanical features is provided, the method comprising: obtaining first geometric features of the surface nodes of the slope, second geometric features of the key line segments of the slope, and third geometric features and mechanical features of the volume nodes in the excavation area of the slope; constructing a first plane unit composed of the surface nodes according to the first geometric features, detecting the intersection of the key line segments and the first plane unit according to the second geometric features, and performing topological optimization on the first plane unit based on the intersection to obtain a second plane unit; determining the key geological interface in the excavation area according to the third geometric features, and dividing the target space where the excavation area is located into multiple sub-spaces. space, classifying the multiple subspaces into key subspaces and non-key subspaces according to the positional relationship between each subspace and the key geological interface; determining the characteristic points on the key geological interface in the key subspace, generating a first spatial unit according to the characteristic points, dividing the non-key subspace into a second spatial unit according to preset parameters, and locally optimizing the first spatial unit and the second spatial unit to obtain a third spatial unit; determining the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node; constructing a slope twin model based on the mechanical characteristics of the second plane unit, the third spatial unit and the third spatial unit.

[0006] According to a second aspect of the present disclosure, a device for constructing a twin model of a slope that integrates geometric and mechanical features is provided, characterized in that the device comprises: a feature acquisition module, configured to obtain a first geometric feature of the surface nodes of the slope, a second geometric feature of the key line segments of the slope, and a third geometric feature and mechanical feature of the body nodes in the excavation area of the slope; a plane unit construction module, configured to construct a first plane unit composed of the surface nodes according to the first geometric feature, detect the intersection of the key line segments and the first plane unit according to the second geometric feature, and perform topological optimization on the first plane unit based on the intersection to obtain a second plane unit; a space processing module, configured to determine the key geological interface in the excavation area according to the third geometric feature, and divide the target space where the excavation area is located into multiple plane units. subspace, classifying the multiple subspaces into key subspaces and non-key subspaces according to the positional relationship between each subspace and the key geological interface; a spatial unit construction module, configured to determine the characteristic points on the key geological interface in the key subspace, generate a first spatial unit according to the characteristic points, divide the non-key subspace into a second spatial unit according to preset parameters, and locally optimize the first spatial unit and the second spatial unit to obtain a third spatial unit; a mechanical feature processing module, configured to determine the mechanical features of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical features of the body node; a twin model construction module, configured to construct a slope twin model based on the mechanical features of the second plane unit, the third spatial unit and the third spatial unit.

[0007] According to a third aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method of the first aspect and possible implementations thereof are implemented.

[0008] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the method of the above-mentioned first aspect and its possible implementation methods by executing the executable instructions.

[0009] The technical solution disclosed in this disclosure has the following beneficial effects: On the one hand, a hybrid modeling technique is employed, constructing the topography of the slope surface through planar units and refining the three-dimensional geological structure of the excavation area through spatial units. This balances the needs of macro-topography display and micro-structural analysis, effectively integrating geometric and mechanical features. This allows for mapping the excavation state of the slope, improving the quality of slope modeling and facilitating simulation of the impact of excavation on slope stability in a twin environment. This allows users to obtain real-time and accurate information, enabling them to identify potential risk areas such as landslides and collapses in advance. On the other hand, during the three-dimensional modeling of the excavation area, by identifying key geological interfaces, the subspaces within the excavation area are classified into critical subspaces and non-critical subspaces, and spatial units are constructed differently for the two types of subspaces. This simplifies the overall modeling process and improves processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flow chart of a slope twin model construction method integrating geometric and mechanical features in an embodiment of the present disclosure is shown.

[0011] Figure 2 A flowchart of constructing a first plane unit in an embodiment of the present disclosure is shown.

[0012] Figure 3 A flow chart for determining a key geological interface in an embodiment of the present disclosure is shown.

[0013] Figure 4 A flow chart for obtaining mechanical characteristics in an embodiment of the present disclosure is shown.

[0014] Figure 5 A schematic diagram of a slope twin model before and after slope excavation in an embodiment of the present disclosure is shown.

[0015] Figure 6 A schematic diagram illustrating a method of generating an excavation visualization section in an embodiment of the present disclosure is shown.

[0016] Figure 7 A schematic diagram illustrating visualization of slope excavation progress in an embodiment of the present disclosure is shown.

[0017] Figure 8 A schematic diagram showing visualization of slope numerical simulation results in an embodiment of the present disclosure is shown.

[0018] Figure 9 A schematic structural diagram of a slope state prediction device based on physical constraints in an embodiment of the present disclosure is shown.

[0019] Figure 10 A schematic structural diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0020] Exemplary embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings.

[0021] The accompanying drawings are schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the accompanying drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, or in hardware modules or integrated circuits, or in networks, processors or microcontrollers. The embodiments can be implemented in various forms and should not be construed as being limited to the examples set forth herein. The features, structures or characteristics described in the present disclosure may be combined in one or more embodiments in any suitable manner. In the description below, many specific details are provided to provide a full description of the embodiments of the present disclosure. However, those skilled in the art will appreciate that one or more specific details may be omitted when implementing the technical solution of the present disclosure, or that other methods, components, devices, steps, etc. may be used to replace one or more specific details.

[0022] In engineering scenarios, it is often necessary to construct in slope-related areas and monitor the slopes. Taking the dam abutment slope as an example, most of them are characterized by high, steep, complex, and changeable geological conditions. If construction is carried out in the dam abutment slope area, the excavation scale is usually large. The inventors found that most of the related technologies construct digital slope models based on static survey data, without considering the integration of dynamic scenarios such as excavation in the slope with real geographical scenes. As a result, the constructed digital slope models are unable to integrate multi-source data, making it difficult to accurately present the characteristics of the excavation area and the actual state of the slope. The model quality is low, affecting the speed and accuracy of users obtaining information from it. It is not conducive to the stability assessment, risk warning and other work on the slope.

[0023] In view of the above problems, an embodiment of the present disclosure provides a slope twin model construction method that integrates geometric and mechanical features, aiming to improve the quality of slope modeling.

[0024] Figure 1 An exemplary process of the method is shown, including the following steps S110 to S160: Step S110, obtaining first geometric features of surface nodes of the slope, second geometric features of key line segments of the slope, and third geometric features and mechanical features of volume nodes in the excavation area of the slope; Step S120: constructing a first plane unit composed of surface nodes according to the first geometric feature, detecting the intersection of the key line segment and the first plane unit according to the second geometric feature, and performing topological optimization on the first plane unit based on the intersection to obtain a second plane unit; Step S130, determining a key geological interface in the excavation area based on the third geometric feature, dividing the target space where the excavation area is located into multiple subspaces, and classifying the multiple subspaces into key subspaces and non-key subspaces based on the positional relationship between each subspace and the key geological interface; Step S140: determining characteristic points on a key geological interface in the key subspace, generating a first spatial unit based on the characteristic points, dividing the non-key subspace into a second spatial unit according to preset parameters, and locally optimizing the first spatial unit and the second spatial unit to obtain a third spatial unit; Step S150, determining the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node; Step S160: constructing a slope twin model based on the second plane unit, the third space unit and the mechanical characteristics of the third space unit.

[0025] based on Figure 1 The method, on the one hand, adopts a hybrid modeling technology, constructing the topography of the slope surface through planar units and finely depicting the three-dimensional geological structure of the excavation area through spatial units. This takes into account the needs of macro-topography display and micro-structural analysis, and effectively integrates geometric and mechanical characteristics. It can map the excavation state of the slope, improve the quality of slope modeling, and facilitate the simulation of the impact of excavation projects on slope stability in a twin environment, allowing users to obtain real-time and accurate information, and thus identify potential risk areas such as landslides and collapses in advance. On the other hand, in the three-dimensional modeling process of the excavation area, by identifying key geological interfaces, the subspaces in the excavation area are classified into key subspaces and non-key subspaces, and spatial units are constructed in different ways for the two types of subspaces, thereby simplifying the overall modeling process and improving processing efficiency.

[0026] Below Figure 1 Provide detailed instructions for each step.

[0027] refer to Figure 1 In step S110, first geometric features of the surface nodes of the slope, second geometric features of the key line segments of the slope, and third geometric features and mechanical features of the volume nodes in the excavation area of the slope are obtained.

[0028] Surface nodes are survey points located on the slope surface. Key segments are those that play a decisive role in slope stability analysis and safety assessment, including but not limited to the crest, toe, shoulder, and bridleway lines. Excavation areas refer to the areas involved in the excavation process within the slope, which can be areas that have already been excavated or planned for excavation. Volume nodes are survey points located within the excavation area, which can be located on or below the slope surface, such as drill points or points on geophysical profiles.

[0029] Geometric features include geometry-related data such as position, orientation, size, and shape. The first geometric feature is the geometric feature of the surface node, the second geometric feature is the geometric feature of the key line segment, and the third geometric feature is the geometric feature of the volume node. The data types of the three geometric features can be the same or different. Mechanical features include mechanics-related data such as elastic modulus, Poisson's ratio, cohesion, and internal friction angle. It should be understood that geometric features or mechanical features can be directly detected by detection equipment or calculated based on detection data.

[0030] For example, drone oblique photography combined with equipment such as a total station can be used to collect point cloud data of the slope's surface nodes, with a density greater than 50 points per square meter. By constructing a coordinate system (such as a first coordinate system based on the slope surface), the point cloud data is converted into the positional coordinates of the surface nodes, which serve as the first geometric feature. Alternatively, the positional coordinates of the surface nodes can be used to determine the distance from the surface node to the slope boundary, the surface curvature at the node's location, and the type of the surface node (e.g., whether the node is a vertex, a turning point, or an ordinary point). These data can be used as the first geometric feature. A total station can be used to detect the positional coordinates of key line segments, such as the top and toe lines of the slope (e.g., the coordinates of the start and end points of key line segments), as the second geometric feature. Alternatively, the positional coordinates of the key line segments can be used to determine the length and type of the key line segment (e.g., whether the key line segment is a main contour line or an auxiliary contour line). These data can also be used as the second geometric feature. Collect geological exploration data and related mechanical test data, and combine them with construction monitoring data of slope excavation projects (such as displacement, stress, etc.) to obtain the third geometric characteristics and mechanical characteristics of volume nodes such as drilling points and geophysical profile points based on these data.

[0031] Continue to refer Figure 1 In step S120, a first plane unit consisting of surface nodes is constructed according to the first geometric feature, the intersection of the key line segment and the first plane unit is detected according to the second geometric feature, and the first plane unit is topologically optimized based on the intersection to obtain a second plane unit.

[0032] In the embodiment of the present disclosure, the slope is divided into two parts: the surface and the excavation area. The surface part is characterized by a surface model, and the excavation area is characterized by a volume model. Plane units are the basic units that compose the surface model, and space units are the basic units that compose the volume model. The present disclosure does not limit the specific forms of plane units and space units, and their specific forms can be determined based on experience or business needs. For example, the surface model can use the TIN (Triangulated Irregular Network) model, in which the plane units are triangular meshes, focusing on geometric expression. The volume model can use the TEN (Tetrahedral Element Network) model, in which the space units are tetrahedrons, to support modeling of geological body mechanical characteristics.

[0033] In one embodiment, reference Figure 2 As shown, the above-mentioned construction of the first plane unit composed of surface nodes according to the first geometric feature includes the following steps S210 to S240: Step S210 , determining first weights of surface nodes according to the first geometric feature, determining initial surface nodes and non-initial surface nodes from the surface nodes according to the first weights, and constructing initial plane units composed of the initial surface nodes.

[0034] The first weight is used to quantify the importance of the surface node in the overall structure of the slope surface. For example, the first weight can be calculated by referring to the following formula: (1) W i represents the first weight, i is the number of the surface node, L i is the distance from the surface node to the slope boundary; C i is the surface curvature at the location of the surface node; F i It is the characteristic attribute value determined by the type of surface node. For example, the characteristic attribute value of slope vertex and bridleway turning point is 1, and that of ordinary point is 0. α 、 β 、 γ is the weight coefficient, which is used to adjust the proportion of each parameter in formula (1) and can be set or adjusted based on experience or actual business needs.

[0035] Surface nodes whose first weights are greater than a certain threshold can be selected as initial surface nodes, or a certain proportion or number of surface nodes can be selected in descending order of first weights. Initial planar elements are constructed based on the initial surface nodes. For example, for each initial surface node, a triangular mesh is formed between it and the two closest initial surface nodes to serve as the initial planar element.

[0036] In one embodiment, the initial plane unit can be formed from the surface nodes in descending order of first weight. For example, the top three surface nodes are formed into a triangular mesh, the fourth surface node and the two closest surface nodes are formed into a triangular mesh, and so on. The initial plane unit is determined to be complete when the initial conditions are met, such as all surface nodes are located within the initial plane unit or the intersection-over-union ratio of the initial plane unit and the slope surface exceeds a certain threshold.

[0037] Step S220 , sorting the non-initial surface nodes according to the distance between the non-initial surface nodes and the initial plane unit and the regional features of the non-initial surface nodes.

[0038] Among them, the surface nodes that do not participate in the construction of the initial plane unit are regarded as non-initial surface nodes and are sorted according to their distance from the initial plane unit and regional characteristics. For example, the priority of non-initial surface nodes can be calculated by referring to the following formula: (2) I j Indicates priority, j is the number of the non-initial surface node, Dist is the distance from point j to the nearest initial plane element, is the average distance from all non-initial surface nodes to the initial plane element, Cp j is the neighborhood terrain complexity of non-initial surface nodes, Ds j is the data density of the area where the non-initial surface nodes are located, λ 、 μ is the weight coefficient, which is used to adjust the proportion of each parameter in formula (2). It can be set or adjusted based on experience or actual business needs. Sort the non-initial surface nodes in descending order of priority.

[0039] Step S230 : adding non-initial surface nodes in sequence according to the order of the non-initial surface nodes, and updating the initial plane unit based on the added non-initial surface nodes.

[0040] For example, non-initial surface nodes can be added one by one according to the order of the non-initial surface nodes. Each time a node is added, the node is connected to the previously added node (including the initial surface node). For example, the newly added node can be connected to the corner points of the initial plane unit in which it is located. In this way, the existing initial plane unit is adjusted or reconstructed to achieve the update of the initial plane unit.

[0041] Step S240 : If all non-initial surface nodes have been added and the updated initial plane units all meet the first preset condition, the updated initial plane unit is used as the first plane unit.

[0042] Among them, the updated initial plane unit must meet the first preset condition, which can be set based on experience or specific business needs. For example, if the initial plane unit is a triangular mesh, the first preset condition may include: the circumscribed circle of the updated triangular mesh does not contain other surface nodes, and the area of the circumscribed circle does not exceed the preset area threshold. In this way, each time a new non-initial surface node is added, the existing triangular mesh is updated based on the newly added node, and the circumscribed circle of the updated triangular mesh is determined. The circumscribed circle does not contain other surface nodes, and the area of the circumscribed circle does not exceed the preset area threshold. S cir Does not exceed the preset area threshold S max . S max It can be set according to the slope area, accuracy requirements, etc., and can be selected for the excavation construction period. S max =10m 2 If the updated initial planar unit does not satisfy the first preset condition, the initial planar unit that does not satisfy the first preset condition is adjusted or reconstructed to satisfy the first preset condition.

[0043] After all non-initial surface nodes are added and the updated initial plane elements all meet the first preset condition, the updated initial plane element is used as the first plane element, thereby completing the preliminary construction of all plane elements.

[0044] The plane unit network formed by the first plane unit can reflect the surface morphology of the slope to a certain extent. Key line segments such as the top line and the foot line in the slope affect the fit between the twin model and the actual slope shape. Therefore, the plane unit network should match the key line segments. In the embodiment of the present disclosure, the intersection of the first plane unit and the key line segment is detected. For example, the second geometric feature may include the position coordinates of the key line segment, and the key line segment is drawn in the first plane unit according to the position coordinates of the key line segment, and the intersection is detected. The first plane unit is topologically optimized according to the intersection, and the plane unit after topological optimization is called the second plane unit, that is, the plane unit finally constructed.

[0045] In one embodiment, the detecting of the intersection between the key line segment and the first plane unit according to the second geometric feature includes the following steps: determining a length and a type of the key line segment according to the second geometric feature, and determining a second weight of the key line segment based on the length and the type of the key line segment; Intersections between the one or more key line segments and the first plane unit are detected according to the second weight.

[0046] Exemplarily, the second weight is calculated with reference to the following formula: (3) in, L k Represents key line segments ，k is the key segment number, n represents the total number of key segments, i Used to identify from 1 to n For each key segment of Length k is the length of the key segment, is the total length of all key segments, Type k The type value of the key line segment (such as the main contour line is assigned a value of 1, and the auxiliary line is assigned a value of 0.5), δ is the weight coefficient, which can be set based on experience or specific business needs, such as 0.3.

[0047] The target key segment can be identified from the key segments based on the second weight, such as a key segment whose second weight is greater than a specific threshold, or a certain proportion or number of key segments selected in descending order of the second weight. The intersection between the target key segment and the first plane unit is detected, without detecting the intersection between non-target key segments and the first plane unit. This further simplifies the calculation process and improves efficiency.

[0048] Alternatively, the intersections between each key segment and the first plane element are detected sequentially, in descending order of second weight, and topological optimization is performed. Specifically, topological optimization is prioritized for the intersections between key segments with the highest second weight and the first plane element. This ensures that more important key segments are embedded preferentially in the plane element network, allowing the plane element network to accurately reflect the true topography of the slope and avoid model distortion caused by improper boundary processing.

[0049] In one embodiment, performing topological optimization on the first planar unit based on the intersection to obtain the second planar unit includes the following steps: Reconstruct one or more first plane units according to the intersection position of the first plane unit and the key line segment so that the reconstructed first plane unit does not intersect the key line segment and minimizes the angle deviation; the angle deviation is the difference between the sum of the interior angles of the first plane unit before and after reconstruction; The reconstructed first plane unit is used as the second plane unit.

[0050] The goal of topology optimization is to ensure that critical line segments do not intersect with planar elements. This ensures that the critical line segments coincide with the boundaries of the planar elements and are represented by the planar elements. Furthermore, during topology optimization, minimizing angular deviation is a constraint to minimize the overall structural changes of the planar elements before and after topology optimization.

[0051] After detecting the intersection of the first plane unit and the key line segment, the first plane unit at the intersection and the adjacent first plane units can be reconstructed. For example, the edges where the intersection occurs in the first plane unit can be deleted, the relevant surface nodes can be reconnected to generate new edges, and edges can be generated along the key line segment. The system can generate multiple reconstruction schemes and calculate the angular deviation of each reconstruction scheme. Taking triangular mesh reconstruction as an example, refer to the following formula: (4) Among them, Δ θ is the angular deviation, θ i is the inner angle of the reconstructed triangle mesh, m1 is the number of triangular meshes before reconstruction, m2 is the number of reconstructed triangular meshes. The reconstruction scheme with the smallest angular deviation is selected and executed, and the reconstructed first planar element is used as the second planar element. This results in the final planar element network, improving the model's geometric quality.

[0052] Continue to refer Figure 1 In step S130, the key geological interface in the excavation area is determined according to the third geometric feature, the target space where the excavation area is located is divided into multiple subspaces, and the multiple subspaces are classified into key subspaces and non-key subspaces according to the positional relationship between each subspace and the key geological interface.

[0053] Among them, the key geological interface is the interface that reflects the important geological structure of the excavation area, such as rock layer interface, fault surface, joint surface, etc.

[0054] In one embodiment, reference Figure 3 As shown, the above-mentioned determination of the key geological interface in the excavation area according to the third geometric feature includes the following steps S310 to S330: Step S310, generating interpolation points in the excavation area, and determining third weights between the interpolation points and the body nodes based on the variance function values between the interpolation points and the body nodes and the variance function values between the body nodes; Step S320, obtaining the elevation of the body node according to the third geometric feature, and determining the elevation of the interpolation point according to the elevation of the body node and a third weight between the interpolation point and the body node; Step S330 : determining the discontinuous interface in the excavation area based on the elevation of the volume node and the elevation of the interpolation point, and determining the key geological interface based on the discontinuous interface.

[0055] For example, a spherical variogram model can be constructed to calculate the variogram value : (5) in, h is the spatial distance between two points, C 0 is the nugget effect, which means the variability and measurement error are less than the minimum sampling interval. C is the arch height, which represents the total variability, a is the range, which indicates the scope of spatial correlation. a There is no longer any spatial correlation between the two points.

[0056] Generate one or more interpolation points in the excavation area P(x,y,z) , the third weight between it and the body node is obtained by solving the variogram equation group, referring to the following formula: (6) in, n is the number of body nodes involved in interpolation, Body Node i and j The variation function value between d ij Body Node i and j The distance between is the volume node i and the interpolation point P The variation function value between d ip Body Node i With interpolation points P The distance between μ is the Lagrange multiplier. d ij 、 d ip In the case of 、 , put it into formula (6) to calculate the third weight between the interpolation point and the body node ω j .

[0057] The body nodes can be determined according to the third geometric feature i Elevation z i , which can be based on the elevation of a specific datum. The interpolation point is calculated by the following formula P The elevation z P : (7) in, ω i is the third weight calculated according to formula (6). Based on the elevation of the volume node and the elevation of the interpolation point, the discontinuous interface in the excavation area is determined. For example, the rock layer interface can be determined based on the location where the elevation or gradient changes suddenly. The approximate location and occurrence information of the discontinuous interface can be determined by combining geological survey and geophysical data. The shape of the discontinuous interface is fitted using a mathematical function implicit polynomial function to accurately reflect the spatial distribution characteristics of the discontinuous interface, thereby accurately obtaining key geological interfaces such as faults and joints.

[0058] The target space can be the bounding box space of the excavation area. The target space is divided into multiple subspaces to facilitate subsequent subspace-based segmentation of spatial units. For example, a three-dimensional bounding box of the excavation area is constructed to obtain the target space. The target space is then recursively divided evenly into eight subspaces, and each subspace is further divided into eight subspaces until each subspace meets a determination criterion, such as the number of geological interfaces contained in each subspace is less than a threshold of three. Subspaces that intersect with critical geological interfaces are marked as critical subspaces, and all other subspaces are marked as non-critical subspaces.

[0059] In one embodiment, the target space can be divided according to key geological interfaces. For example, subspaces enclosing the key geological interfaces are identified within the target space, and the target space is then divided along the boundaries of the enclosing subspaces. This minimizes the number of key subspaces and improves the efficiency of subsequent processing.

[0060] Continue to refer Figure 1 In step S140, characteristic points on the key geological interface are determined in the key subspace, a first spatial unit is generated based on the characteristic points, the non-key subspace is divided into a second spatial unit according to preset parameters, and the first spatial unit and the second spatial unit are locally optimized to obtain a third spatial unit.

[0061] Among them, the characteristic points on the key geological interface can be body nodes on the key geological interface or points at important positions on the key geological interface (such as drilling exposure points, interface intersections), and the first spatial unit is generated based on the characteristic points. For example, the first spatial unit can be composed of characteristic points, or the boundary of the first spatial unit can pass through the characteristic points.

[0062] In one embodiment, the key subspace is a subspace that intersects the key geological interface. The above-mentioned determining the characteristic points on the key geological interface in the key subspace and generating the first spatial unit based on the characteristic points includes the following steps: Determine the characteristic points on the key geological interface in the key subspace and generate sampling points; Triangles are constructed based on the feature points and the sampling points, and the triangles are combined to form a tetrahedron as the first spatial unit.

[0063] For example, within the critical subspace, sampling points are randomly generated at a certain density, while retaining the characteristic points on the key geological interface within the critical subspace. A three-dimensional triangulation is performed on the set of sampling points and characteristic points. For example, the triangular mesh generation method described above can be used to obtain a triangular mesh composed of the sampling points and characteristic points. The triangular meshes are then combined to form a tetrahedron as the first spatial unit.

[0064] For non-critical subspaces, there is no need to perform spatial division based on feature points. Instead, the non-critical subspace is divided into second spatial units according to preset parameters. The preset parameters may include a preset size, a preset density, a preset number, etc. For example, if the non-critical subspace is a rectangular space, the non-critical subspace is divided into multiple regular tetrahedrons according to a preset number as the second spatial units. It can be seen that the processing process for the non-critical subspace is relatively simple, which helps to reduce the overall computational complexity.

[0065] In one embodiment, when generating a first spatial unit, preset parameters can be determined based on the first spatial unit. For example, the average density of the first spatial unit within each key subspace can be calculated as the preset density, or the average size of the first spatial unit can be calculated as the preset size. Then, a second spatial unit can be constructed according to the preset parameters, such that the second spatial unit is similar to the first spatial unit in terms of size, shape, distribution density, etc.

[0066] In one embodiment, the local optimization of the first spatial unit and the second spatial unit includes the following steps: If the first spatial unit or the second spatial unit does not meet the second preset condition, use it as a spatial unit to be optimized; The spatial unit to be optimized is adjusted according to an average distance between the first spatial unit and the second spatial unit adjacent to the spatial unit to be optimized, so that the adjusted spatial unit to be optimized meets a second preset condition.

[0067] The second preset condition is used to measure whether the quality of the first spatial unit or the second spatial unit meets the standard. The second preset condition can be set based on experience or specific business needs. For example, the second preset condition may include: the minimum dihedral angle is not less than the preset angle threshold. For example, the first spatial unit and the second spatial unit are both tetrahedrons, and the preset angle threshold is set based on experience. . Calculate the minimum dihedral angle for each tetrahedron ,like , the tetrahedron is judged to be of substandard quality and is selected as a spatial unit to be optimized. The spatial unit to be optimized can be slightly displaced toward the centroid of the surrounding first or second spatial units, and the minimum dihedral angle is recalculated after the adjustment until the minimum dihedral angle is not less than the preset angle threshold. When making displacement adjustments, the displacement amount can be calculated by referring to the following formula: (8) Among them, Δ d is the displacement, d avg is the average distance between the adjacent first space unit and the second space unit, β It is an adjustment coefficient, which can be set based on experience or specific business needs, such as 0.1~0.3.

[0068] If displacement cannot improve the quality, local reconstruction is performed on the optimized spatial unit and its adjacent areas. For example, the optimized spatial unit and its adjacent first and second spatial units can be re-triangulated in three dimensions, with priority given to retaining points and edges related to key geological interfaces to ensure that the triangular mesh fits the geological structure, thus forming a tetrahedron. The quality is then tested using the second preset condition to ensure compliance. The resulting first and second spatial units are referred to as the third spatial unit.

[0069] This disclosed embodiment fuses a fine mesh (first spatial unit) generated within a critical subspace with a coarse mesh (second spatial unit) generated within a non-critical subspace, completing a rapid tetrahedron-based segmentation of the target space. Quality is then verified using a second pre-set condition, and the quality of the resulting third spatial unit is ensured through local displacement adjustment and reconstruction. This segmentation discretizes complex three-dimensional geological structures, such as rock interfaces, faults, and joints, into a combination of spatial units, such as tetrahedrons, that conform to the shape and boundaries of critical geological interfaces, accurately representing the slope geometry and laying the foundation for interpolation and assignment of mechanical characteristics.

[0070] Continue to refer Figure 1 In step S150, the mechanical characteristics of the third spatial unit are determined according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node.

[0071] Mechanical characteristics are discrete and localized, while the body model of the excavation area requires continuous, global mechanical characteristics. The disclosed embodiment can convert discrete mechanical characteristics into mechanical characteristics of each third space unit, so that discrete data can be integrated into a continuous model framework, providing a data basis for numerical analysis, and improving the authenticity and accuracy of the model. Among them, each third space unit can be treated as a whole to calculate its mechanical characteristics. Or the mechanical characteristics of different positions in the third space unit can be calculated. For example, the mechanical characteristics of the body nodes can be interpolated by interpolation to obtain the mechanical characteristics of the third space unit.

[0072] In one embodiment, reference Figure 4 As shown, the above-mentioned determination of the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node includes the following steps S410 to S430: Step S410: Acquire the position of the center point of the third spatial unit, interpolate the mechanical characteristics of the body nodes according to the position of the center point, and obtain the mechanical characteristics interpolation result of the center point.

[0073] Among them, mechanical characteristics can include elastic modulus, Poisson's ratio, cohesion, internal friction angle, stress and other parameters. E For example, for the center point of each third space unit Q ( x , y , z ), interpolation can be performed based on the mechanical characteristics of the body nodes, referring to the following formula: (9) in, E Q Center point Q The elastic modulus, E i Body Node i The elastic modulus, n is the total number of body nodes, ω i Body Node i With the center point Q The weight coefficient between them can be obtained by solving the above formulas (5) and (6). The center point can be calculated by formula (9): Q The elastic modulus of other mechanical features can be interpolated in the same way to obtain the center point Q Other mechanical characteristics.

[0074] Step S420: Input the geological attribute data of the third spatial unit into the deep learning model, and output the predicted value of the mechanical characteristics of the third spatial unit through the deep learning model.

[0075] Among them, geological attribute data may include lithology coding, burial depth, wave velocity, etc., and geological attribute data can be obtained through geological surveys. A deep learning model of the type of Convolutional Neural Network (CNN) can be constructed, which is used to predict mechanical characteristics based on the input geological attributes. For example, the geological attributes and mechanical characteristics of a known area (the mechanical characteristics are obtained through surveys and can be used as labels) can be used as sample data to train the deep learning model so that it can output accurate prediction results. The geological attribute data of the third spatial unit is input into the trained deep learning model, and the predicted value of the mechanical characteristics of the third spatial unit is output. For example, the predicted value of the elastic modulus obtained by the deep learning model can be recorded as E CNN .

[0076] Step S430 , obtaining the mechanical characteristics of the third spatial unit by fusing the mechanical characteristics interpolation result of the center point and the mechanical characteristics prediction value of the third spatial unit.

[0077] Taking the elastic modulus as an example, the mechanical characteristic interpolation result E Q and mechanical characteristics prediction values E CNN Weighted fusion to obtain the final mechanical characteristics of the third space unit E final : (10) in, q1 、 q2 is the weight coefficient, the sum of the two is 1. Its value can be set according to experience or specific business needs, and can be adjusted and optimized based on cross-validation of sample data.

[0078] Through the above methods, various mechanical characteristics of the third space unit can be accurately obtained.

[0079] Continue to refer Figure 1 ,In step S160, a slope twin model is constructed based on the mechanical characteristics of the second plane unit, the third space unit, and the third space unit.

[0080] The second plane unit and the third spatial unit can be combined to form a three-dimensional model that represents the entire slope. The mechanical characteristics of the third spatial unit can be bound to the three-dimensional model so that it can represent the mechanical properties of the excavation area.

[0081] In one embodiment, the slope twin model is constructed based on the second plane unit, the third space unit, and the mechanical characteristics of the third space unit, including the following steps: Mapping the second plane unit and the third space unit to a unified coordinate system; The second plane unit is rendered according to the first texture information, the third space unit is rendered according to the second texture information, and display parameters of the rendered third space unit are set according to mechanical characteristics of the third space unit to form a slope twin model.

[0082] Among them, the unified coordinate system is a coordinate system used to characterize the entire slope, such as the world coordinate system. The transformation relationship between the local coordinate system of the second plane unit, the local coordinate system of the third space unit and the unified coordinate system can be determined, and the second plane unit and the third space unit are mapped to the unified coordinate system based on the transformation relationship. The first texture information is the texture information about the slope surface, and the second texture information is the texture information about the excavation area. Both texture information can be specified manually or automatically by the system. The second plane unit is rendered according to the first texture information, and the third space unit is rendered according to the second texture information. The display parameters of the rendered third space unit are set according to the mechanical characteristics of the third space unit, such as different mechanical characteristics corresponding to different colors, transparency, etc., so that the display effect of the third space unit can characterize its mechanical characteristics and enhance the visibility of the model.

[0083] For example, the topography of a slope is displayed using both a TIN model and a TEN model. The excavation area of the slope is represented by the TEN model, while the rest (primarily the surface) is represented by the TIN model. The portion of the TIN model that does not belong to the excavation is retained as the basis for displaying the topography of the slope excluding the excavation. Within the tetrahedralized TEN model, the excavation area of particular interest can be meshed.

[0084] The coordinate systems of the TIN and TEN models are then aligned to ensure their positions in 3D space accurately correspond. The boundaries of the TIN and TEN models are adjusted so that the excavation area's TEN model boundary seamlessly connects with the TIN model's terrain surface boundary, avoiding gaps or overlaps.

[0085] Finally, different materials and textures are assigned to the TIN model and the TEN model. Figure 5 The twin slope models before and after excavation are shown. The terrain surface of the TIN model can use real satellite imagery terrain textures, while the excavation area of the TEN model can use textures representing rock materials. Colors or transparency settings are set based on mechanical characteristics to intuitively display the geological characteristics of the excavation area. The layered display function in the visualization interface allows the TIN model, TEN model, or both to be displayed separately, allowing users to observe the slope topography and excavation characteristics from different angles.

[0086] Taking the excavation of the dam abutment slope of a large domestic hydropower project as an example, the implementation process of the present disclosure is explained.

[0087] First, a TIN model based on parallel processing is generated. During the automatic TIN model generation process, key segments are divided into multiple subtasks and processed using multi-threaded parallel constraints. Each thread independently processes the embedding and optimization of a set of key segments, and finally merges the results. Data is synchronized through a shared memory mechanism to avoid conflicts. The specific steps are as follows: Key line segment grouping: All key line segments of the slope are grouped together and sorted into r groups according to the length of the line segments from large to small, which are recorded as , each key segment group contains roughly the same number of key segments.

[0088] Priority allocation: Combined with the previously calculated influence weight ,Assign priorities to each key segment group. The group containing key segments with high weights is given higher priority to ensure that key boundaries are processed first.

[0089] Thread pool initialization: Create a thread pool of size q based on computer hardware resources (such as the number of CPU cores) , each thread processes a critical segment group.

[0090] Task allocation: group the key segment tasks Assigned to a thread in the thread pool .

[0091] Independent task execution: After each thread receives a task, it independently performs the following operations: Segment Embedding: Pair Groups Each key segment in , according to the boundary constraint processing method, calculate the intersection with the edge of the existing triangle mesh, and insert new nodes to interrupt the edge of the triangle mesh.

[0092] Topology optimization: For the local area after inserting the node, the local diagonal exchange and node relocation algorithm are used to minimize the angle deviation Δ of the intersection area θ , optimize the triangulated network topology.

[0093] Local result preservation: During the processing, each thread saves the processed local triangle mesh information (including newly added nodes, updated triangle mesh topology, etc.) in its own temporary storage area to avoid interference between different thread data.

[0094] Shared memory structure design: Create a shared memory area to store global triangle mesh information (including node sets and triangle mesh sets). At the same time, design a mutex to control access to the shared memory, ensuring that only one thread can modify the shared memory data at a time.

[0095] Result merging: After all threads complete their tasks, they merge their local triangle meshes into the global triangle mesh in shared memory. During the merging process, duplicate nodes and triangle meshes are removed, and node numbers and topological relationships are unified.

[0096] Then automatically generate a TEN model based on parallel processing. The specific steps are as follows: The three-dimensional geological space is divided into layers of 50 meters each according to elevation. Each layer is assigned to different threads as an independent subtask, and each subtask corresponds to a geological interface construction area.

[0097] Each thread divides the three-dimensional space into multiple subspaces for the assigned subtask, and each subspace is assigned to the thread as a partitioning task. Different partitioning accuracies are set for key and non-key subspaces, with key subspaces receiving higher partitioning accuracy.

[0098] After each thread divides the subspace into tetrahedrons, it splices the tetrahedrons of adjacent subspaces and synchronizes boundary node information through shared memory to avoid duplication or loss.

[0099] The tetrahedrons of the TEN model are assigned to different threads according to their unit numbers. Each thread is responsible for calculating the mechanical characteristics of the assigned tetrahedron.

[0100] After each thread completes the calculation, it writes the mechanical characteristics into the corresponding tetrahedron. The shared memory mechanism ensures that all tetrahedrons are assigned mechanical characteristics and the data is accurate.

[0101] Use multi-threaded parallelism to check the geometric and topological consistency of the TEN model. Export the verified TEN model to a 3D geological model format (such as 3DM, STL, etc.) to facilitate subsequent engineering analysis and visualization.

[0102] Finally, the TIN model and the TEN model are fused to generate a dynamic slope twin model.

[0103] The above slope twin model can further realize the following functions: Generate Excavation Visualization Sections: Reference Figure 6 As shown, users can use cutting planes to cut model units in the slope twin model. For example, the cutting plane is manually marked in the engineering twin model panorama. The system determines the nodes of all intersecting surfaces of the cutting plane and the model tetrahedron, and then reconstructs the section according to the nodes of the intersecting surface to generate Figure 6 The geological section shown on the right side of the center.

[0104] Excavation progress visualization: Reference Figure 7As shown in the figure, the excavation progress can be visualized based on the TEN model of the excavation area. The user can set the excavation progress, and the system will map the excavation progress to obtain the TEN model of the corresponding time point. In essence, it controls the tetrahedron segmentation, reconstruction, and hiding according to the construction time of the excavation area. By assigning different time attributes and engineering quantity attributes to the units in the excavation area, the excavation progress of the twin slope can be visualized. Figure 7 It shows that the panoramic view of the excavation progress is displayed when the excavation progress is set, and the excavation body can be presented as disappearing over time.

[0105] Visualization of numerical calculation model: The slope twin model can be used for numerical simulation calculation, and the numerical simulation results can be used to visually display the safety status of the twin slope. Figure 8 As shown in the figure, numerical analysis cloud maps are used to display numerical simulation results. In the slope twin model and excavation profile, different colors are used to represent the numerical simulation results of each area. For example, from blue to red, a geological parameter gradually increases. This realizes the visualization of slope safety information.

[0106] This disclosed embodiment utilizes hybrid mesh modeling technology, employing a high-precision TEN model for excavation areas (such as fault zones) and a simplified TIN mesh for less critical areas, such as the surface. This improves model computational efficiency while maintaining an overall geometric error of ≤2%. The twin model accumulates geological, monitoring, and construction data into a digital archive, providing a reference for subsequent similar projects (such as other dam abutment slope excavations), reducing the cost of repeated surveys and modeling.

[0107] The embodiment of the present disclosure also provides a device for constructing a slope twin model that integrates geometric and mechanical features. Figure 9 As shown, the slope twin model construction device 900 integrating geometric and mechanical features may include the following modules: A feature acquisition module 910 is configured to acquire first geometric features of surface nodes of the slope, second geometric features of key line segments of the slope, third geometric features and mechanical features of volume nodes in the excavation area of the slope; A planar unit construction module 920 is configured to construct a first planar unit composed of the surface nodes according to the first geometric feature, detect the intersection of the key line segment and the first planar unit according to the second geometric feature, and perform topological optimization on the first planar unit based on the intersection to obtain a second planar unit; a space processing module 930 configured to determine a key geological interface in the excavation area based on the third geometric feature, divide the target space in which the excavation area is located into a plurality of subspaces, and classify the plurality of subspaces into key subspaces and non-key subspaces based on a positional relationship between each subspace and the key geological interface; The spatial unit construction module 940 is configured to determine characteristic points on a key geological interface in the key subspace, generate a first spatial unit based on the characteristic points, divide the non-key subspace into a second spatial unit according to preset parameters, and locally optimize the first spatial unit and the second spatial unit to obtain a third spatial unit. a mechanical characteristic processing module 950 configured to determine the mechanical characteristic of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristic of the body node; The twin model construction module 960 is configured to construct a slope twin model based on the second plane unit, the third space unit and the mechanical characteristics of the third space unit.

[0108] In one embodiment, constructing a first plane unit composed of the surface nodes according to the first geometric feature includes: determining first weights of the surface nodes according to the first geometric features, determining initial surface nodes and non-initial surface nodes from the surface nodes according to the first weights, and constructing initial plane units composed of the initial surface nodes; sorting the non-initial surface nodes according to the distance between the non-initial surface nodes and the initial plane unit and the regional characteristics of the non-initial surface nodes; Adding the non-initial surface nodes in sequence according to the order of the non-initial surface nodes, and updating the initial plane unit based on the added non-initial surface nodes; If all non-initial surface nodes have been added and the updated initial plane elements all meet the first preset condition, the updated initial plane element is used as the first plane element.

[0109] In one embodiment, the initial planar unit is a triangular mesh; and the updated initial planar unit satisfies a first preset condition, including: The circumscribed circle of the updated triangular mesh does not contain other surface nodes, and the area of the circumscribed circle does not exceed a preset area threshold.

[0110] In one embodiment, detecting the intersection of the key line segment and the first plane unit according to the second geometric feature includes: determining the length and type of the key line segment according to the second geometric feature, and determining a second weight of the key line segment based on the length and type of the key line segment; An intersection between one or more key line segments and the first plane unit is detected according to the second weight.

[0111] In one embodiment, performing topological optimization on the first planar unit based on the intersection to obtain the second planar unit includes: Reconstructing one or more of the first planar units according to the intersection positions of the first planar units and the key line segments so that the reconstructed first planar units do not intersect the key line segments and minimize an angle deviation; the angle deviation is the difference between the sum of the interior angles of the first planar units before and after reconstruction; The reconstructed first plane unit is used as the second plane unit.

[0112] In one embodiment, determining the key geological interface in the excavation area according to the third geometric feature includes: generating an interpolation point in the excavation area, and determining a third weight between the interpolation point and the body node according to a variance function value between the interpolation point and the body node and a variance function value between the body nodes; Acquiring the elevation of the body node according to the third geometric feature, and determining the elevation of the interpolation point according to the elevation of the body node and a third weight between the interpolation point and the body node; Based on the elevations of the volume nodes and the elevations of the interpolation points, a discontinuous interface in the excavation area is determined, and a key geological interface is determined based on the discontinuous interface.

[0113] In one embodiment, the key subspace is a subspace intersecting the key geological interface; determining characteristic points on the key geological interface in the key subspace and generating the first spatial unit according to the characteristic points includes: Determining characteristic points on key geological interfaces within the key subspace and generating sampling points; A triangle is constructed based on the feature points and the sampling points, and the triangles are combined to form a tetrahedron as the first spatial unit.

[0114] In one embodiment, the locally optimizing the first spatial unit and the second spatial unit includes: If the first spatial unit or the second spatial unit does not meet the second preset condition, use it as a spatial unit to be optimized; According to an average distance between a first space unit and a second space unit adjacent to the space unit to be optimized, the space unit to be optimized is adjusted so that the adjusted space unit to be optimized meets a second preset condition.

[0115] In one embodiment, determining the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node includes: Obtaining a position of a center point of the third spatial unit, and interpolating the mechanical characteristics of the body node according to the position of the center point to obtain an interpolation result of the mechanical characteristics of the center point; Inputting the geological attribute data of the third spatial unit into a deep learning model, and outputting a predicted value of the mechanical characteristics of the third spatial unit through the deep learning model; The mechanical characteristics of the third spatial unit are obtained by fusing the mechanical characteristic interpolation result of the center point and the mechanical characteristic prediction value of the third spatial unit.

[0116] In one embodiment, constructing the slope twin model based on the second plane unit, the third space unit, and the mechanical characteristics of the third space unit includes: Mapping the second plane unit and the third space unit to a unified coordinate system; The second plane unit is rendered according to the first texture information, the third space unit is rendered according to the second texture information, and display parameters of the rendered third space unit are set according to the mechanical characteristics of the third space unit to form the slope twin model.

[0117] The specific details of each part of the above-mentioned device have been described in detail in the implementation method part. The undisclosed details can be found in the implementation method part, so they will not be repeated here.

[0118] It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0119] The embodiments of the present disclosure further provide a computer program product, which includes a computer program, and implements the above method when the computer program is executed by a processor.

[0120] In one embodiment, a computer program product may be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The computer-readable storage medium may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid state drive (SSD), and the like. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing the computer program, such as a read-only memory (ROM) or NAND flash memory.

[0121] In one embodiment, the computer program product may be an intangible product containing a computer program. For example, the computer program product may be implemented as a virtual digital product, such as an executable file or installation package storing the computer program.

[0122] The code of a computer program can be written in one or more programming languages, such as C, Java, C++, etc. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user's computing device via any type of network, such as a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via an internet connection provided by a carrier).

[0123] Computer programs can be carried or transmitted through electrical, magnetic, optical, electromagnetic, infrared and other signals. Electronic devices can convert signals carrying computer programs into digital signals, and then run the computer programs. When the computer program runs on an electronic device, its code is used to enable the electronic device to execute (more specifically, it can enable the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure, for example: Step S110, obtaining the first geometric features of the surface nodes of the slope, the second geometric features of the key line segments of the slope, and the third geometric features and mechanical features of the body nodes in the excavation area of the slope; Step S120, constructing a first plane unit composed of surface nodes according to the first geometric features, detecting the intersection of the key line segments and the first plane unit according to the second geometric features, and performing topological optimization on the first plane unit based on the intersection to obtain a second plane unit; Step S130, determining the key geological interface in the excavation area according to the third geometric features, The target space where the excavation area is located is divided into multiple subspaces, and the multiple subspaces are classified into key subspaces and non-key subspaces according to the positional relationship between each subspace and the key geological interface; step S140, determining the characteristic points on the key geological interface in the key subspace, generating a first spatial unit according to the characteristic points, dividing the non-key subspace into a second spatial unit according to preset parameters, and locally optimizing the first spatial unit and the second spatial unit to obtain a third spatial unit; step S150, determining the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node; step S160, constructing a slope twin model based on the mechanical characteristics of the second plane unit, the third spatial unit and the third spatial unit.

[0124] The above method is implemented based on a computer program. On the one hand, a hybrid modeling technique is used to construct the topography of the slope surface using planar units and to finely depict the three-dimensional geological structure of the excavation area using spatial units. This takes into account the needs of macro-topography display and micro-structural analysis, and effectively integrates geometric and mechanical characteristics. It can map the excavation state of the slope, improve the quality of slope modeling, and facilitate the simulation of the impact of excavation projects on slope stability in a twin environment, allowing users to obtain real-time and accurate information, and thus identify potential risk areas such as landslides and collapses in advance. On the other hand, during the three-dimensional modeling of the excavation area, by identifying key geological interfaces, the subspaces in the excavation area are classified into critical subspaces and non-critical subspaces. Different spatial units are constructed for the two types of subspaces, thereby simplifying the overall modeling process and improving processing efficiency.

[0125] Embodiments of the present disclosure also provide an electronic device. The electronic device may include a processor and a memory. The memory stores executable instructions for the processor, such as a computer program. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of the present disclosure.

[0126] Reference below Figure 10 , the electronic device is exemplarily described in the form of a general-purpose computing device. It should be understood that Figure 10 The electronic device 1000 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0127] like Figure 10 As shown, the electronic device 1000 may include: a processor 1010 , a memory 1020 , a bus 1030 , an I / O (input / output) interface 1040 , and a network adapter 1050 .

[0128] Memory 1020 may include volatile memory, such as RAM 1021 and cache unit 1022, and non-volatile memory, such as ROM 1023. Memory 1020 may also include one or more program modules 1024. Such program modules 1024 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, program modules 1024 may include the modules described above.

[0129] The processor 1010 may include one or more processing units. For example, the processor 1010 may include an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor and / or an NPU (Neural-Network Processing Unit) and other processing units.

[0130] The processor 1010 can be used to execute the executable instructions stored in the memory 1020, which can include the method steps of various exemplary embodiments of the present disclosure, such as: step S110, obtaining the first geometric features of the surface nodes of the slope, the second geometric features of the key line segments of the slope, and the third geometric features and mechanical features of the volume nodes in the excavation area of the slope; step S120, constructing a first plane unit composed of surface nodes according to the first geometric features, detecting the intersection of the key line segments and the first plane unit according to the second geometric features, and performing topological optimization on the first plane unit based on the intersection to obtain a second plane unit; step S130, determining the key geological interface in the excavation area according to the third geometric features, and placing the excavation area in the first plane unit. The target space is divided into multiple subspaces, and the multiple subspaces are classified into key subspaces and non-key subspaces according to the positional relationship between each subspace and the key geological interface; step S140, determining the characteristic points on the key geological interface in the key subspace, generating a first spatial unit according to the characteristic points, dividing the non-key subspace into a second spatial unit according to preset parameters, and locally optimizing the first spatial unit and the second spatial unit to obtain a third spatial unit; step S150, determining the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node; step S160, constructing a slope twin model based on the mechanical characteristics of the second plane unit, the third spatial unit and the third spatial unit.

[0131] Based on the execution of the above method by processor 1010, on the one hand, a hybrid modeling technology is adopted to construct the topography of the slope surface through planar units, and to finely depict the three-dimensional geological structure of the excavation area through spatial units. This takes into account the needs of macro-topography display and micro-structural analysis, and effectively integrates geometric features and mechanical features. It can map the excavation state of the slope, improve the quality of slope modeling, and is conducive to simulating the impact of excavation projects on slope stability in a twin environment, allowing users to obtain real-time and accurate information, and then identify potential risk areas such as landslides and collapses in advance. On the other hand, in the three-dimensional modeling process of the excavation area, by identifying key geological interfaces, the subspaces in the excavation area are classified into key subspaces and non-key subspaces, and different spatial units are constructed for the two types of subspaces, thereby simplifying the overall modeling process and improving processing efficiency.

[0132] The bus 1030 is used to realize the connection between different components of the electronic device 1000 and may include a data bus, an address bus, and a control bus.

[0133] The electronic device 1000 can communicate with one or more external devices 1100 (eg, a keyboard, a mouse, an external controller, etc.) through the I / O interface 1040 .

[0134] The electronic device 1000 can communicate with one or more networks via the network adapter 1050. For example, the network adapter 1050 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. The network adapter 1050 can communicate with other modules of the electronic device 1000 via the bus 1030.

[0135] although Figure 10 Not shown, other hardware and / or software modules may also be provided in the electronic device 1000, including but not limited to: a display, microcode, device drivers, redundant processors, an external disk drive array, a tape drive, and a data backup storage system.

[0136] As can be seen from the above, the technical solutions of the present disclosure can be implemented as methods, devices, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will appreciate that various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation that combines hardware and software aspects, such as "circuits," "modules," or "systems," respectively.

[0137] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. Those skilled in the art will easily think of other embodiments based on the specific embodiments provided by the present disclosure. Therefore, the specific embodiments provided by the present disclosure are merely exemplary, and the scope and spirit of the present disclosure are indicated by the claims, which should cover any variations, uses or adaptive changes of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the field of the present technology that are not disclosed in the present disclosure.

Claims

1. A slope twin model construction method integrating geometric and mechanical features, characterized by: The method comprises: Acquire first geometric features of surface nodes of the slope, second geometric features of key line segments of the slope, and third geometric features and mechanical features of volume nodes in an excavation area of the slope; Constructing a first plane unit composed of the surface nodes according to the first geometric feature, detecting the intersection of the key line segment and the first plane unit according to the second geometric feature, and performing topological optimization on the first plane unit based on the intersection to obtain a second plane unit; determining a key geological interface in the excavation area according to the third geometric feature, dividing the target space in which the excavation area is located into a plurality of subspaces, and classifying the plurality of subspaces into key subspaces and non-key subspaces according to a positional relationship between each subspace and the key geological interface; Determining characteristic points on a key geological interface in the key subspace, generating a first spatial unit based on the characteristic points, dividing the non-key subspace into a second spatial unit according to preset parameters, and locally optimizing the first spatial unit and the second spatial unit to obtain a third spatial unit; determining a mechanical characteristic of the third spatial unit according to a positional relationship between the third spatial unit and the body node and a mechanical characteristic of the body node; A slope twin model is constructed based on the mechanical characteristics of the second plane unit, the third space unit and the third space unit.

2. The method according to claim 1, characterized in that The step of constructing a first plane unit composed of the surface nodes according to the first geometric feature includes: determining first weights of the surface nodes according to the first geometric features, determining initial surface nodes and non-initial surface nodes from the surface nodes according to the first weights, and constructing initial plane units composed of the initial surface nodes; sorting the non-initial surface nodes according to the distance between the non-initial surface nodes and the initial plane unit and the regional characteristics of the non-initial surface nodes; Adding the non-initial surface nodes in sequence according to the order of the non-initial surface nodes, and updating the initial plane unit based on the added non-initial surface nodes; If all non-initial surface nodes have been added and the updated initial plane elements all meet the first preset condition, the updated initial plane element is used as the first plane element.

3. The method according to claim 2, characterized in that The initial planar unit is a triangular mesh; the updated initial planar unit satisfies a first preset condition, including: The circumscribed circle of the updated triangular mesh does not contain other surface nodes, and the area of the circumscribed circle does not exceed a preset area threshold.

4. The method according to claim 1, wherein Detecting the intersection of the key line segment and the first plane unit according to the second geometric feature includes: determining the length and type of the key line segment according to the second geometric feature, and determining a second weight of the key line segment based on the length and type of the key line segment; An intersection between one or more key line segments and the first plane unit is detected according to the second weight.

5. The method according to claim 1, wherein The topological optimization of the first planar unit based on the intersection condition to obtain the second planar unit includes: Reconstructing one or more of the first planar units according to the intersection positions of the first planar units and the key line segments so that the reconstructed first planar units do not intersect the key line segments and minimize an angle deviation; the angle deviation is the difference between the sum of the interior angles of the first planar units before and after reconstruction; The reconstructed first plane unit is used as the second plane unit.

6. The method according to claim 1, characterized in that Determining the key geological interface in the excavation area according to the third geometric feature includes: generating an interpolation point in the excavation area, and determining a third weight between the interpolation point and the body node according to a variance function value between the interpolation point and the body node and a variance function value between the body nodes; Acquiring the elevation of the body node according to the third geometric feature, and determining the elevation of the interpolation point according to the elevation of the body node and a third weight between the interpolation point and the body node; Based on the elevations of the volume nodes and the elevations of the interpolation points, a discontinuous interface in the excavation area is determined, and a key geological interface is determined based on the discontinuous interface.

7. The method according to claim 1, characterized in that The key subspace is a subspace that intersects with the key geological interface; Determining characteristic points on a key geological interface in the key subspace and generating a first spatial unit according to the characteristic points includes: Determining characteristic points on key geological interfaces within the key subspace and generating sampling points; A triangle is constructed based on the feature points and the sampling points, and the triangles are combined to form a tetrahedron as the first spatial unit.

8. The method according to claim 1, characterized in that The locally optimizing the first spatial unit and the second spatial unit includes: If the first spatial unit or the second spatial unit does not meet the second preset condition, use it as a spatial unit to be optimized; According to an average distance between a first space unit and a second space unit adjacent to the space unit to be optimized, the space unit to be optimized is adjusted so that the adjusted space unit to be optimized meets a second preset condition.

9. The method according to any one of claims 1 to 8, characterized in that The determining the mechanical characteristics of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristics of the body node includes: Obtaining a position of a center point of the third spatial unit, and interpolating the mechanical characteristics of the body node according to the position of the center point to obtain an interpolation result of the mechanical characteristics of the center point; Inputting the geological attribute data of the third spatial unit into a deep learning model, and outputting a predicted value of the mechanical characteristics of the third spatial unit through the deep learning model; The mechanical characteristics of the third spatial unit are obtained by fusing the mechanical characteristic interpolation result of the center point and the mechanical characteristic prediction value of the third spatial unit.

10. The method according to any one of claims 1 to 8, characterized in that The step of constructing a slope twin model based on the second plane unit, the third space unit, and the mechanical characteristics of the third space unit includes: Mapping the second plane unit and the third space unit to a unified coordinate system; The second plane unit is rendered according to the first texture information, the third space unit is rendered according to the second texture information, and display parameters of the rendered third space unit are set according to the mechanical characteristics of the third space unit to form the slope twin model.

11. A device for constructing a slope twin model integrating geometric and mechanical features, characterized in that: The device comprises: a feature acquisition module configured to acquire first geometric features of surface nodes of the slope, second geometric features of key line segments of the slope, third geometric features and mechanical features of volume nodes in an excavation area of the slope; a planar unit construction module configured to construct a first planar unit composed of the surface nodes according to the first geometric feature, detect an intersection between the key line segment and the first planar unit according to the second geometric feature, and perform topological optimization on the first planar unit based on the intersection to obtain a second planar unit; a space processing module configured to determine a key geological interface in the excavation area based on the third geometric feature, divide the target space in which the excavation area is located into a plurality of subspaces, and classify the plurality of subspaces into key subspaces and non-key subspaces based on a positional relationship between each subspace and the key geological interface; a spatial unit construction module configured to determine characteristic points on a key geological interface in the key subspace, generate a first spatial unit based on the characteristic points, divide the non-key subspace into second spatial units according to preset parameters, and locally optimize the first spatial unit and the second spatial unit to obtain a third spatial unit; a mechanical characteristic processing module configured to determine the mechanical characteristic of the third spatial unit according to the positional relationship between the third spatial unit and the body node and the mechanical characteristic of the body node; The twin model construction module is configured to construct a slope twin model based on the second plane unit, the third space unit and the mechanical characteristics of the third space unit.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 10 when the computer program is executed by a processor.

13. An electronic device, characterized in that: include: processor; as well as a memory for storing executable instructions of the processor; The processor is configured to perform the method according to any one of claims 1 to 10 by executing the executable instructions.

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