A tailings dam breach simulation method, system, medium and terminal

Abstract

The application discloses a tailing pond dam-break simulation method, system, medium and terminal, and the method comprises the steps of acquiring multi-source heterogeneous spatial data of a target tailing pond and performing data preprocessing to obtain elevation data; based on the preprocessed elevation data, a double-path geometric model is constructed, grid division is performed, and the running parameters of the double-path geometric model are initialized; a deformation-seepage coupling control equation of the double-path geometric model is determined; based on the double-path geometric model after the grid division, a coupling evolution process of a deformation field and a seepage field of the target tailing pond is simulated and simulated until the target tailing pond is broken or the calculation step in the coupling calculation parameters reaches a preset value. The method fuses multi-source geographic information data, adopts multi-scale modeling, and realizes seepage-deformation full-process coupling tailing pond dam-break simulation.

Description

Technical Field

[0001] This invention relates to the field of tailings dam safety prevention and control technology in mining engineering, and in particular to a tailings dam failure simulation method, system, medium and terminal. Background Technology

[0002] Tailings dams are core ancillary facilities for the centralized storage of tailings after mineral processing in both metallic and non-metallic mines. They serve both environmental protection and production functions, but they are also high-potential-energy hazards. Dam failures can easily lead to significant casualties, ecological damage, and economic losses amounting to billions of yuan. With the increasing frequency of extreme rainfall caused by global climate change and the escalation of mining intensity, the situation regarding tailings dam safety risk prevention and control is becoming increasingly severe. Dam failure safety simulation technology has become a core tool for tailings dam risk assessment, protective design, and emergency response.

[0003] Existing tailings dam safety simulation technologies are mainly divided into physical simulation and numerical simulation. In dam failure scenario design, physical simulation primarily constructs the tailings dam failure topography through proportional scaling, focusing on typical triggers such as flooding and seepage failure. By adjusting parameters such as dam slope and reinforcement layers, it analyzes the differences in characteristic manifestations during the dam failure process under different variables, thereby exploring the impact of a single variable on dam failure evolution and revealing its mechanism. However, physical simulation suffers from high costs, long cycles, and difficulty in overcoming scale effects, failing to meet conventional prediction and assessment needs. Tailings dam numerical simulation methods refer to the technical process of fully digitally reconstructing, simulating, and predicting the geological structure, dam body, sedimentary beach, and physical and mechanical behavior of tailings within the tailings dam system in a computer, based on fundamental principles of solid mechanics, fluid mechanics, porous media seepage theory, and soil mechanics, using numerical calculation methods such as the finite element method, finite difference method, discrete element method, material point method, or depth integral method. Numerical simulation has become a mainstream research direction, but existing numerical simulation technologies and related similar technologies have many technical limitations:

[0004] (1) The data source is single and the efficient integration of multi-source heterogeneous data has not been achieved. For example, the seepage deformation simulation of the earth-rock dam of the reservoir only uses geological survey data and design drawings, the flood overtopping scenario construction of the tailings dam only uses feature point data collected by the total station, the seepage failure simulation of the tailings dam only uses a simple DEM and dam body parameters, and the three-dimensional seepage calculation of the tailings dam only uses topographic map elevation points, CAD wireframes and exploration borehole data. All of these have problems such as missing topographic details and mismatch between engineering profiles and real space, resulting in insufficient modeling accuracy.

[0005] (2) The modeling system lacks multi-scale design. Existing technologies only use a single two-dimensional model or a single three-dimensional model, such as two-dimensional seepage analysis, three-dimensional geometric visualization modeling, and single three-dimensional steady-state seepage modeling. It cannot take into account both the detailed analysis of the local slope instability mechanism and the dynamic simulation of the evolution of the whole-domain dam break. There is a contradiction between computational efficiency and simulation realism.

[0006] (3) The simulation degree of coupling between seepage and deformation is low. Existing technologies either only establish a basic fluid-structure interaction equation framework, or only perform segmented independent analysis of seepage and structural failure, or only realize single steady-state seepage calculation. There is no two-way dynamic full coupling mechanism between seepage field and deformation field, which cannot reveal the mechanical essence of tailings dam failure and severs the intrinsic connection between "slope instability failure mechanism" and "post-damage debris flow movement process".

[0007] (4) The simulation scenario is singular, only simulating single causes such as flooding and seepage failure. It can only realize the restoration of steady-state seepage or apparent dam failure process, and has no full-chain simulation capability for multiple working conditions and multiple causes. It cannot make forward-looking predictions and quantitative assessments of the stability of the tailings dam throughout its entire life cycle.

[0008] (5) The technology system is fragmented. Most of the existing technologies are single simulation methods without an integrated system architecture. There is no standardized process from data acquisition, modeling, calculation to result analysis. The operation is complex and the adaptability is poor, which cannot meet the simulation needs of tailings ponds of different types and geological conditions.

[0009] In summary, existing technologies cannot achieve high-precision, widely adaptable, practical, and low-cost simulation of the entire tailings dam failure chain. There is an urgent need for a tailings dam failure simulation method that integrates multi-source geographic information data, adopts multi-scale modeling, and realizes the coupling of the entire seepage-deformation process. Summary of the Invention

[0010] To address the problems of existing tailings dam failure simulation technologies, such as single data sources, insufficient modeling accuracy, lack of multi-scale design, low simulation fidelity of seepage-deformation coupling, limited simulation scenarios, and fragmented technical systems, this invention aims to construct a tailings dam failure simulation method, system, medium, and terminal. The method achieves full-chain simulation of the "instability causes-disaster consequences" of tailings dam failure through multi-source heterogeneous data fusion, dual-path multi-scale modeling, and bidirectional dynamic fully coupled calculation of seepage-deformation. This reveals the mechanical essence of dam failure, balances computational efficiency and simulation realism, improves simulation accuracy and adaptability, and provides enterprises and regulatory departments with scientific basis for tailings dam safety prevention and control, effectively reducing the risk of dam failure.

[0011] Firstly, a tailings dam failure simulation method includes:

[0012] S1: Acquire multi-source heterogeneous spatial data of the target tailings dam and perform data preprocessing to obtain elevation data;

[0013] S2: Based on the preprocessed elevation data, a dual-path geometric model is constructed, and meshing and initialization of the running parameters of the dual-path geometric model are performed; wherein, the dual-path geometric model includes a two-dimensional profile model and a three-dimensional global reality model; the running parameters are the mechanism parameters of the two-dimensional profile model, the spatial constraint data of the three-dimensional global model, and the coupling calculation parameters;

[0014] S3: Determine the deformation-seepage coupling control equations for the dual-path geometric model; the deformation-seepage coupling control equations are used to simulate the entire deformation-seepage coupling evolution process of the tailings dam.

[0015] S4: Simulate the coupled evolution of the deformation field and seepage field of the target tailings dam based on the dual-path geometric model after mesh generation, until the calculation step size in the target tailings dam failure / coupling calculation parameters reaches the preset value.

[0016] Furthermore, the multi-source heterogeneous spatial data includes macro-regional benchmark elevation data of the area where the target tailings dam is located, downloaded from a geospatial data cloud platform; CAD elevation data map of the target tailings dam's mining area; and topographic data of the target tailings dam obtained by drone aerial photography.

[0017] Furthermore, in S2, the process of constructing the two-dimensional profile model is as follows:

[0018] S211: Clean up the layers and remove redundant elements from the preprocessed elevation data, generate a closed dam body profile domain, clarify the boundaries of each material zone, and label the geometric dimensions and elevation parameters of each zone.

[0019] S212: Import the processed CAD profile into the modeling software, set the tensile thickness to meet the preset plane strain analysis requirements, and use commands to stretch the model along the normal of the profile to obtain a two-dimensional profile model with a preset geometric similarity ratio to the target tailings dam.

[0020] S213: Mesh the two-dimensional profile model, refine the mesh in the preset key areas, and sparse the mesh in the non-key areas;

[0021] S214: Evaluate the mesh quality based on preset quality standards: If the mesh quality fails, refine / coarse the local mesh until it meets the preset standards; otherwise, set the boundary conditions of the two-dimensional profile model, load the initial stress field and load, and complete the construction and debugging of the two-dimensional profile model.

[0022] Furthermore, in S2, the specific construction process of the 3D global reality model is as follows:

[0023] S221: Import the pre-processed elevation data of the target tailings dam into the 3D modeling software, complete the point cloud to surface conversion, terrain meshing, and dam outline fitting operations, construct the full-domain 3D real-scene model of the tailings dam and export it into the data format that the simulation software can receive.

[0024] S222: The simulation software completes model repair and mesh reconstruction based on the received data, refines the mesh of the dam body and the area affected by the seepage line, and clarifies the material partition boundaries, seepage channels and displacement boundary conditions.

[0025] S223: Preserve the topographic undulations and spatial correlation features of the entire tailings dam area, and perform full-domain adaptation of the 3D real-scene volume model; among them, the dual-path geometric models are mutually verified.

[0026] Furthermore, the deformation field in the deformation-seepage coupling control equation of the dual-path geometric model in S3 is set as follows:

[0027] Formula for converting pore water pressure into effective stress:

[0028] ;

[0029] In the formula, Corresponding to Direction, such as It is normal stress. Shear stress; For effective stress tensor; This is the total stress tensor; The Kronecker function; Pore ​​water pressure;

[0030] Arbitrary grid node If the rate of change of momentum equals the net external force, then the discrete incremental form of the nodal motion equations is:

[0031] ;

[0032] In the formula: For nodes Concentrated mass; For nodes Speed ​​increment; To calculate the time step; For nodes The sum of internal forces generated by the effective stress. Corresponding to direction; This is the external force term formed by the action of water;

[0033] Pore ​​water pressure is the source of force, the effective stress principle is the rule for force transformation, and the discrete nodal motion equation aims to transform pore water pressure into force that can be identified by the nodes through effective stress. Then, the iterative calculation of the deformation field is completed through the nodal motion equation, which is the core physical and numerical connection logic of seepage affecting deformation.

[0034] Displacement increment Update formula:

[0035] ;

[0036] ;

[0037] ;

[0038] In the formula: For nodes The displacement increment; for Time Node speed; for Time Node speed; for Time Node The displacement; for Time Node The displacement is calculated. In practice, based on the central difference scheme, the node velocity at time t+Δt is used as the average velocity within the time step to obtain the node displacement increment within the time step t~t+Δt. Then, the displacement increment is superimposed on the cumulative displacement at time t to complete the displacement update at time t+Δt.

[0039] Strain increment :

[0040] ;

[0041] in, For strain increment; , All are displacement increment components; This is the partial derivative of the displacement increment in the coordinate direction;

[0042] Elastic stress increment Calculation formula:

[0043] ;

[0044] ;

[0045] ;

[0046] in, This represents the increment of elastic stress. Shear modulus; Let Lamé constant be denoted by . For strain increment; For volumetric strain increment, specifically for The normal strain increments in the three directions are summed. It is the elastic modulus; Poisson's ratio;

[0047] Elastic stress calculation formula:

[0048] ;

[0049] In the formula: Let be the stress column vector at time t+Δt; Let be the column vector of elastic test stress at time t+Δt; Here is the elastic stiffness matrix; This represents the total strain increment;

[0050] The stress correction formula is:

[0051] ;

[0052] in, Let be the final elastoplastic stress tensor at time t+Δt; Let be the elastic stress tensor at time t+Δt; For the plastic strain increment tensor; This represents the plastic volumetric strain increment.

[0053] Furthermore, the seepage field setting in the deformation-seepage coupling control equation of the dual-path geometric model in S3 is as follows:

[0054] Incremental form of the seepage continuity equation:

[0055] ;

[0056] In the formula: For Hamiltonian operators; For permeability tensor; For fluid dynamic viscosity; This represents the increase in pore water pressure. For fluid density; It is the acceleration due to gravity; Elevation increment; Porosity; The fluid compressibility coefficient; For the increase of source and sink items; The volumetric strain increment output by the deformation field; The rate of change of volumetric strain increment over time;

[0057] Seepage velocity:

[0058] ;

[0059] In the formula, This represents the Darcy seepage velocity; the negative sign indicates that the velocity decreases along the direction of the total head. The gradient of pore water pressure; Elevation gradient;

[0060] Secondly, the present invention provides a tailings dam failure simulation system, the system being used to perform the steps of the method described above, including:

[0061] Data acquisition and preprocessing module: Acquires multi-source heterogeneous spatial data of the target tailings dam and performs data preprocessing to obtain elevation data;

[0062] Dual-path geometric model construction module: Based on preprocessed elevation data, a dual-path geometric model is constructed, and meshing and initialization of the running parameters of the dual-path geometric model are performed; wherein, the dual-path geometric model includes a two-dimensional profile model and a three-dimensional global reality model; the running parameters are the mechanism parameters of the two-dimensional profile model, the spatial constraint data of the three-dimensional global model, and the coupling calculation parameters;

[0063] Control equation determination module: determines the deformation-seepage coupling control equations of the dual-path geometric model; the deformation-seepage coupling control equations are used to simulate the entire deformation-seepage coupling evolution process of the tailings dam;

[0064] Simulation module: Based on the dual-path geometric model after mesh generation, the simulation module simulates the coupled evolution process of the deformation field and seepage field of the target tailings dam until the calculation step size in the target tailings dam failure / coupling calculation parameters reaches the preset value.

[0065] Furthermore, the system also includes a result analysis and visualization module: used to perform multi-dimensional quantitative analysis of the coupled calculation results, including seepage field, deformation field, mechanical field and the entire dam break process, to quantify the dam break disaster risk characteristics, and then present the calculation results through two-dimensional and three-dimensional visualization.

[0066] Thirdly, the present invention provides a readable storage medium storing a computer program that, when invoked by a processor, performs the steps of the method described above.

[0067] Fourthly, the present invention provides an electronic terminal comprising a processor and a memory, the memory storing a computer program, the processor invoking the computer program to perform the steps of the method described above.

[0068] This invention proposes a tailings dam failure simulation method, system, medium, and terminal. The method, by fusing multi-source geographic information data, employing dual-path modeling of two-dimensional profiles and three-dimensional real-world scenes, and achieving coupled simulation of the entire seepage-deformation process, overcomes the limitations of traditional tailings dam failure simulation in terms of data adaptability, modeling accuracy, scale applicability, and coupling simulation degree. Compared with existing technologies, it possesses the following significant advantages:

[0069] 1. Efficient fusion and standardized preprocessing of multi-source heterogeneous data improve the reliability of modeling data sources: This invention integrates two core data sources: CAD engineering profile vector data and DEM raster data from the geospatial data cloud. This solves the technical problems of missing terrain details and mismatch between engineering profiles and real-world space in single-source data. It also takes into account the engineering structural accuracy of CAD profiles and the terrain restoration accuracy of 3D real-world data, providing high-precision and highly consistent basic data support for subsequent multi-scale simulations.

[0070] 2. Constructing a dual-path, multi-scale modeling system to balance detailed local analysis with global real-world simulation: Addressing the varying scale requirements of tailings dam failure simulation, an innovative dual-path technical approach combining two-dimensional profile detailed modeling and three-dimensional global real-world modeling is designed. The two-dimensional path imports CAD profiles into simulation software for two-dimensional profile stretching modeling, enabling rapid and detailed analysis of typical cross-sectional mechanical and seepage characteristics, parameter calculations, and model verification. The three-dimensional path constructs a scaled-down real-world model based on a real DEM, fully reproducing the reservoir area's topographic relief, dam spatial morphology, and boundary conditions, achieving a realistic reproduction of the global dam failure evolution and disaster scope. The dual-path models can mutually verify and complement each other, simultaneously meeting the dual research needs of local mechanism research and global risk assessment, resolving the contradiction between computational efficiency and simulation realism inherent in traditional single-scale modeling.

[0071] 3. The simulation of the entire dam failure process is more in line with engineering reality, and the two-way coupling calculation of seepage-deformation has high accuracy: By embedding the effective stress principle, the seepage continuity equation of porous media, and the Mohr-Coulomb elastoplastic constitutive model into the simulation solution framework, the real-time transmission of pore water pressure and effective stress, and the dynamic feedback of volumetric strain and seepage field are realized. The coupling mechanism of seepage driving the deterioration of effective stress and deformation changing the pore permeability characteristics is fully depicted. Under the condition of constant load, the shear strength parameters of the soil and rock mass are gradually reduced until the critical instability is obtained. The slope safety factor obtained in this way can more realistically reflect the entire evolution law of the tailings dam from seepage infiltration, gradual deformation to breach expansion and instability failure compared with the non-coupled simulation. The consistency between the simulation results and the actual instability characteristics of the engineering is significantly improved.

[0072] 4. Standardized simulation process and highly integrated system significantly improve the efficiency of dam break simulation: A standardized method for the entire process of data acquisition, preprocessing, dual-path modeling, and simulation evolution is formed, reducing the complexity of multi-software collaborative operation; at the same time, a corresponding simulation system is built to integrate data acquisition and preprocessing modules, dual-path geometric model construction modules, control equation determination modules, simulation modules, and result analysis and visualization modules. It can automatically complete data interaction, model import, parameter assignment, and post-processing analysis, shortening the model construction cycle and reducing human operation errors; two-dimensional profile modeling can quickly complete working condition calculations and parameter sensitivity analysis, and three-dimensional real-world volume model can be directly used for final risk assessment, significantly improving computational efficiency and simulation flexibility compared to traditional methods.

[0073] 5. Wide applicability, adaptable to simulation needs of different types of tailings dams. It exhibits excellent adaptability to various tailings dam types, including valley-type, hillside-type, and flat-type tailings dams. The 2D profile position, 3D model range, and calculation conditions can be flexibly adjusted. It is compatible with simulations of various typical conditions such as normal water level, sudden water level drop, rainstorm infiltration, and drainage failure. Its multi-source data fusion architecture is compatible with extended data sources such as UAV aerial surveys and on-site investigations, possessing excellent scalability and reusability. It can meet the needs of dam failure simulation and safety assessment for tailings dams of different sizes and geological conditions, providing enterprises and regulatory departments with scientific safety control basis and effectively reducing the risk of tailings dam failure. Attached Figure Description

[0074] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0075] Figure 1 This is a schematic diagram of the tailings dam failure simulation method provided in the embodiments of the present invention;

[0076] Figure 2 This is a flowchart illustrating the implementation of dual-path modeling according to an embodiment of the present invention; wherein, Figure 2 (a) is a flowchart of the construction process of the two-dimensional cross-sectional model. Figure 2 (b) is a flowchart of the construction process of the 3D global reality model;

[0077] Figure 3 This is a display diagram of a three-dimensional real-world volumetric model provided in an embodiment of the present invention; wherein, Figure 3 (a) The result of importing DEM data processed by GlobalMapper into Rhino software. Figure 3(b) is a rendering of the effect of importing only the three-dimensional surface elevation map of the entire tailings dam area;

[0078] Figure 4 This is a schematic diagram of model construction and measurement point layout provided in the application embodiment of the present invention: Figure 4 (a) is a schematic diagram of a cross-sectional model with a geometric similarity ratio of 1:100; Figure 4 (b) is a schematic diagram of the layout of measuring points at key nodes;

[0079] Figure 5 This is a slope displacement cloud map provided in an application embodiment of the present invention;

[0080] Figure 6 This is a displacement change curve of the set measuring points provided in the application embodiment of the present invention; wherein, Figure 6 (a) shows the monitoring results for monitoring points 1-5; Figure 6 (b) shows the monitoring results for monitoring points 6-7;

[0081] Figure 7 A multi-dimensional stress cloud diagram is provided for an application embodiment of the present invention; wherein, Figure 7 (a) is the maximum stress contour plot; Figure 7 (b) is the minimum stress contour diagram; Figure 7 (c) is the stress contour plot along the x-axis; Figure 7 (d) is the stress contour diagram along the y-axis; Figure 7 (e) is the stress contour diagram along the z-axis;

[0082] Figure 8 A slope area displacement vector diagram provided for an application embodiment of the present invention;

[0083] Figure 9 Displacement cloud diagrams for multiple calculation step stages during the reduction process provided in the application embodiment of the present invention; wherein, Figure 9 (a) has a calculation step size of 1000; Figure 9 (b) The calculation step size is 2000; Figure 9 (c) The calculation step size is 2500; Figure 9 (d) has a calculation step size of 3000; Figure 9 (e) has a calculation step size of 3500; Figure 9 (f) has a calculation step size of 4000; Figure 9 The calculation step size for (g) is 4500; Figure 9 The calculation step size for (h) is 5000; Figure 9 The calculation step size for (i) is 5255. Detailed Implementation

[0084] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0085] Example 1

[0086] like Figure 1 As shown, this embodiment provides a tailings dam failure simulation method, including:

[0087] S1: Obtain multi-source heterogeneous spatial data of the target tailings dam and perform data preprocessing to obtain elevation data.

[0088] Specifically, the multi-source heterogeneous spatial data includes macro-regional benchmark elevation data of the area where the target tailings dam is located, downloaded from a geospatial data cloud platform; CAD elevation data map of the target tailings dam's mining area; and topographic data of the target tailings dam obtained by drone aerial photography.

[0089] In practical implementation, this embodiment integrates three core data sources: public DEM resources from the geospatial data cloud, CAD elevation vector data of mining area engineering, and UAV aerial survey DOM and DEM real-scene data. This enables the comprehensive, multi-scale, and high-precision acquisition of mining area topographic elevation information. The three types of differentiated data are then uniformly imported into the Global Mapper professional GIS platform, completing data format standardization, coordinate system unification, topographic information visualization, and preprocessing analysis. This provides accurate and efficient data source support for subsequent 3D geological modeling and digital engineering design, solving industry pain points such as insufficient accuracy of traditional single data sources, incompatibility of multi-source data formats, and cumbersome preprocessing procedures.

[0090] The Geospatial Data Cloud is a free platform for acquiring remote sensing and geospatial data. It covers national / regional land use data (including cultivated land, forest land, grassland, construction land, and water areas) at 30-meter resolution, and also includes specialized land cover data for wetlands, coastal zones, and mining areas. The absolute errors of the global elevation datasets in SRTM GL3 (90m x 90m resolution) and ASTER GDEM V3 (30m x 30m resolution) are 16 meters and 20 meters respectively, suitable for macro-regional benchmark elevations, large-scale mining area surveys, and supplementary data for remote mining areas. This data platform allows for easy acquisition of preliminary digital terrain data for target mining areas. The DEM elevation data downloaded directly from this platform is essentially raster-formatted spatial elevation data. The mainstream native format is GeoTIFF, a raster format with geographic coordinate information that is the standard storage format for DEMs, containing key information such as the elevation value, spatial projection, and coordinate range of each pixel. Users can independently select the desired data range within the platform, and the downloaded data is essentially a compressed data archive with an .iso CD image extension.

[0091] In the traditional mine surveying and construction phase, CAD 2D drawings, especially in DWG / DXF format, are the most common and complete basic data, available in almost all mines. These drawings contain elements such as mine boundaries, exploration lines, roadway plans, surface features, elevation annotations, and contour lines, but are stored only in X and Y plane coordinates. Elevation information is mostly textual annotations rather than entity attributes, i.e., there is no Z-value. These 2D drawings are the source data for mine digitization, providing a ready-made planar framework and elevation information carrier for conversion into elevation data maps. Based on existing 2D drawings, through native CAD functions and plugins / general GIS tools, the planar X and Y data can be quickly upgraded into 3D elevation data maps containing Z-values. This requires no specialized surveying equipment or high-threshold technology; ordinary engineering technicians can master this skill with simple training. After conversion, it can be directly used for terrain analysis, earthwork calculation, slope design, 3D modeling, and numerical simulation, significantly enhancing the 3D application value of 2D drawings.

[0092] Both traditional CAD 2D maps and 3D digital elevation data have limitations in dynamically covering large areas of terrain. To overcome this limitation and address the insufficient resolution of public DEM data, drone aerial photography has become a core method for optimizing high-precision terrain data. Through low-altitude aerial surveying, drone aerial photography can quickly generate digital orthophotos (DOMs) with realistic textures and high-precision digital elevation models (DEMs), providing high-resolution, timely data sources of real-world scenery and terrain for 3D modeling of mining areas. UAV aerial survey data processing follows the steps of "data acquisition, preprocessing, aerial triangulation, 3D modeling, result generation, and format export (this is existing technology and will not be elaborated here)". First, a dense point cloud is generated: the software generates a high-density 3D point cloud containing the X / Y / Z coordinates and RGB color of each point based on a multi-view stereo matching algorithm. The dense point cloud is then filtered to remove non-ground points such as vegetation and buildings. In mining areas, terrain undulations need to be preserved, and artificial facilities are filtered out. DEM raster data is generated through raster interpolation. Based on the DEM, the original image is orthorectified to eliminate image distortion caused by terrain undulations and camera tilt, generating a distortion-free orthophoto map, while simultaneously overlaying coordinate information.

[0093] After acquiring multi-source data, the obtained data undergoes preprocessing, including data format standardization, coordinate system unification, terrain information visualization, and preprocessing analysis. This provides accurate and efficient data source support for subsequent 3D geological modeling and digital engineering design. In this specific implementation, Global Mapper is used for the next step of processing. Global Mapper is a lightweight GIS data processing platform with core advantages such as comprehensive format compatibility, low learning curve, and one-stop data processing, covering the entire process from data import, coordinate transformation, terrain analysis to output. Global Mapper has the feature of automatically parsing packaged data. Whether it's an .iso CD image file downloaded from a geospatial data cloud, a converted CAD 2D drawing from mining exploration, or digital elevation data collected and processed by UAVs, the data package can be directly read without further decompression or conversion, skipping the encapsulation layer. After reading the core raster file, the software parses its geographic coordinates, projection, and pixel elevation values, converting discrete elevation values ​​into a visualized topographic map, presented through elevation grading and coloring, slope rendering, and other methods. Meanwhile, in terms of format conversion and export, Global Mapper has a built-in conversion engine for massive spatial data formats. It can first convert the read DEM raster data into a unified data model within the software, and then re-encode and output it in PXF, DEM, ASCII, SHP (after vectorization), CAD and other formats according to user needs to achieve cross-format compatibility.

[0094] S2: Based on the preprocessed elevation data, construct a two-dimensional profile model and a three-dimensional global reality model respectively.

[0095] To address the diverse research needs in tailings dam failure simulation, this study combines precise verification of two-dimensional profiles with three-dimensional full-domain real-world reconstruction. Based on the differentiated characteristics of multi-source heterogeneous data, a dual-path geometric model system of two-dimensional profile models and three-dimensional full-domain models is constructed. Two types of numerical models are differentiated: the two-dimensional profile model based on CAD engineering profiles focuses on the seepage deformation and local instability mechanism analysis of typical slope profiles, emphasizing modeling efficiency and engineering relevance; the three-dimensional full-domain model based on multi-source elevation data is used to reconstruct the overall topography, dam outline, and surrounding environment of the tailings dam, realizing the spatial dynamic evolution simulation of the dam failure process, balancing model realism and full-domain analysis capabilities.

[0096] Specifically, such as Figure 2 As shown in (a), the construction process of the two-dimensional profile model is as follows: S211: Clean up the layers and remove redundant elements of the pre-processed tailings dam CAD two-dimensional drawing, retain the core profile elements such as the dam outline, the stratigraphic boundary, and the drainage structure boundary, unify the coordinate system and unit (meter), fix the topological errors of the outline, and ensure the geometric integrity of the profile; in the CAD environment, based on the pre-processed outline, generate a closed dam profile domain, clarify the boundaries of the dam material partitions such as dam rockfill, seepage prevention, bedrock, and tailings sand, and mark the geometric dimensions and elevation parameters of each partition;

[0097] S212: Import the processed CAD section directly into FLAC3D software, and generate a two-dimensional section model by stretching the section along the normal direction by a specified length using the zone extrude command.

[0098] S213: Mesh the two-dimensional model (structured mesh is used in this embodiment), preset displacement constraints and seepage boundaries for boundary conditions; based on the characteristics of the two-dimensional model, simplify non-critical structures, such as simplifying small drainage pipes, ignoring minor topographic undulations, and optimizing mesh density, that is, densifying the mesh in critical areas and sparsening the mesh in non-critical areas, improving the efficiency of seepage-deformation coupling calculation, adapting to the detailed analysis needs of local slope instability, seepage line evolution, etc., and avoiding calculation errors caused by mesh distortion;

[0099] S214: Evaluate the mesh quality based on the preset quality standards. If the mesh quality fails, perform local mesh refinement / coarsening optimization. After the quality evaluation is passed, set the boundary conditions of the model (such as displacement constraints and seepage boundaries), load the initial stress field and gravity load (gravitational acceleration is taken as 10m / s²), and complete the construction and debugging of the two-dimensional profile fine model.

[0100] like Figure 2As shown in (b), the construction process of the 3D global reality model is as follows:

[0101] S221: Import geospatial data cloud DEM, UAV DOM / DEM, and CAD dam outline data into GlobalMapper, complete coordinate system transformation, data stitching, hole filling, terrain filtering to remove vegetation, buildings, and other non-ground features, and output a standardized GeoTIFF format global DEM and dam vector boundary; import the GlobalMapper-processed DEM data into Rhino software to achieve the following results: Figure 3 As shown in (a), however, importing only the data yields a three-dimensional surface elevation map of the entire tailings dam area, which is insufficient to achieve the desired results. Figure 3 (b) shows the effect of the three-dimensional real-world volumetric model. The global GeoTIFF format DEM data output by Global Mapper is imported into Rhino software. Operations such as point cloud to surface conversion, terrain meshing, and dam outline fitting are completed to construct a global three-dimensional real-world volumetric model of the tailings dam, restoring the dam shape, reservoir topography, surrounding slope, and spatial layout of flood discharge and seepage control facilities.

[0102] S222: Export the 3D model built in Rhino to STL / DXF format, import it into FLAC3D software, complete model repair and mesh reconstruction, refine the mesh of the dam body and the phreatic line influence zone, clarify the material partition boundaries, seepage channels and displacement boundary conditions, match the material parameters of the 2D profile model with the constitutive model, and ensure the consistency of the dual-path model parameters.

[0103] S223: Perform global adaptation of the 3D model, set geological uncertainty parameters, and complete the construction of a 3D global real-world model. In specific implementation, the topographic undulations and spatial correlation characteristics of the tailings dam are preserved without excessive simplification. The spatial evolution path of flood diffusion, slope slippage, and dam failure during the dam break is fully restored. The model adapts to the dynamic simulation requirements of the entire dam break range, inundation area, and disaster diffusion, resulting in an integrated 3D model of the terrain, dam body, and environment.

[0104] The dual-path model uses complementary data from the same source and consistent material parameters, mutually verifying each other. It retains the engineering practicality of traditional tailings dam slope profile simulation while overcoming the limitations of two-dimensional profiles to achieve dynamic reconstruction of the entire 3D dam-break process. It solves the limitation of traditional two-dimensional models in reflecting the overall dam-break diffusion while also compensating for the computational inefficiency of pure 3D models. In practice, the calculation parameters of the two-dimensional profile model are substituted into the 3D global reality model. The boundary conditions of the two-dimensional profile model are verified by the global terrain features of the 3D model; the accuracy of the material parameters of the 3D model is checked by the detailed calculation results of the two-dimensional profile model, achieving mutual verification between the two-path models and ensuring the reliability of the model.

[0105] Specifically, based on the mechanistic parameters of the two-dimensional profile model and the spatial constraint data of the three-dimensional global model, the initialization of the coupled calculation model of the finite element difference software is completed. In practice, the mechanistic parameters analyzed from the two-dimensional profile model are imported as the initial mechanistic input for the coupled calculation; the spatial constraint data of the three-dimensional global real-world model is imported as the spatial constraint basis for the coupled calculation; the coupled calculation parameters are configured in the finite element difference software to determine the basic operational rules for the time-step iteration of the seepage-deformation coupled calculation model; and then the above data and parameters are integrated to complete the overall initialization of the coupled calculation of the finite element difference software, forming a calculation model that can be directly iterated. The mechanistic parameters of the two-dimensional profile model include, but are not limited to, the location data of the sliding surface from the dam crest, the safety factor, and the pore water pressure distribution data. These are used as the initial mechanistic input for the coupled calculation to ensure that the coupled calculation can accurately capture the key mechanical characteristics of slope instability. The spatial constraint data of the three-dimensional global model includes, but are not limited to, global geometric data (such as dam dimensions, reservoir topographic coordinates, etc.), boundary conditions (such as upstream water level boundaries, downstream free outflow boundaries, dam foundation fixed displacement constraints, etc.), and engineering facility layout data (such as spatial location data of drainage blind pipes, permeability coefficient, etc.). These are used as spatial constraints for the coupled calculation to ensure that the coupled calculation fits the actual situation of the entire project. The coupled calculation parameters include, but are not limited to, the time step iteration step size, the calculation time, and the unbalanced convergence criterion value (which is a customizable numerical threshold).

[0106] S3: Determine the deformation-seepage coupling control equations for the dual-path geometric model; the deformation-seepage coupling control equations are used to simulate the entire deformation-seepage coupling evolution process of the tailings dam.

[0107] The essence of tailings dam failure evolution lies in the bidirectional dynamic coupling of the seepage field and the stress-deformation field. The spatiotemporal evolution of pore water pressure alters the effective stress state of the soil, driving dam deformation and failure. Conversely, the deformation of the dam's framework alters the pore structure and permeability, in turn affecting the distribution and development of the seepage field, forming a closed-loop coupling effect. FLAC3D, based on the effective stress principle, the law of conservation of mass, and Newton's second law, achieves a fully coupled solution for the seepage and deformation fields. Its core logic is as follows: the seepage field, through pore water pressure, is equivalent to a volume force acting on the soil framework, participating in the force balance calculation of the deformation field; the deformation field, through volumetric strain, changes the pore volume, acting as a source term to drive the dynamic evolution of the seepage field, ultimately achieving a numerical simulation of "seepage influencing deformation, and deformation feeding back to seepage." Therefore, the deformation-seepage coupling control equation is determined, which is then used to control the entire deformation-seepage coupling evolution process of the tailings dam in FLAC3D, including both the strain field and the seepage field, as detailed below:

[0108] (1) The calculation concept of strain field is based on the pore water pressure of each grid node at the current moment. The pore water pressure is converted into the corresponding equivalent nodal force through the effective stress principle. The nodal velocity increment is calculated by substituting it into the nodal motion equation of Newton's second law, and then the nodal displacement increment is obtained. The nodal displacement increment is converted into strain increment through geometric equation. The stress increment and stress state are calculated by the Mohr-Coulomb elastoplastic constitutive model to obtain the deformation field result of the current time step, and the volumetric strain increment is output at the same time.

[0109] Soil deformation and failure are controlled solely by effective stress. Changes in pore water pressure directly affect the soil's mechanical response by altering the effective stress; this is the core physical mechanism by which the seepage field and deformation field are coupled. The formula for converting pore water pressure into corresponding effective stress is as follows:

[0110] ;

[0111] In the formula, For effective stress tensor; This is the total stress tensor; For Kronek's letter, , The direction of the three-dimensional rectangular coordinate system. Corresponding to Direction, used to describe the directional properties of tensors such as stress, strain, and displacement; This refers to the pore water pressure.

[0112] FLAC3D employs the explicit finite difference method. Based on Newton's second law, it solves the force equilibrium problem of the deformation field, iteratively calculating the evolution of displacement, velocity, and stress through the incremental form of the nodal motion equations. This applies to arbitrary mesh nodes. If the rate of change of momentum equals the net external force, then the discrete incremental form of the nodal motion equations is:

[0113] ;

[0114] In the formula: For nodes Concentrated mass; For nodes Speed ​​increment; To calculate the time step; For nodes The sum of internal forces generated by the effective stress. Corresponding to direction; The external force term is composed of the total water force, which equals the normal force of pore water pressure plus the volume force of seepage force.

[0115] ;

[0116] Pore ​​water pressure normal force The normal force generated by pore water pressure acting on the soil element surface is obtained by discretizing and distributing it to the nodes:

[0117] ;

[0118] Penetration force and volume force The volume forces generated by the flow of pore water in the soil pores are transformed into nodal concentrated forces (derived from Darcy's law):

[0119] ;

[0120] In the formula, For the first Normal force of pore water pressure at each node; For the first The permeation force and volume force at each node; Pore ​​water pressure; Let be the component of the unit normal vector of the soil element surface in the j-direction; This represents the actual area of ​​the soil unit surface. For fluid density; It is the acceleration due to gravity; The head gradient after discretization in the j-direction; Let be the volume of the soil element.

[0121] For the first The sum of the vector sum of the nodal forces acting on each grid node due to the effective stress is obtained by discretizing the effective stress of the soil element through finite difference: first, using the principle of effective stress... The effective stress tensor of the element is calculated, converted into surface forces on the element surface, and then distributed to the surrounding mesh nodes according to the node weights. Finally, the vector contributions of all element forces received by the nodes are superimposed to obtain the final result. .

[0122] Based on the central difference scheme, the displacement increment is updated by the velocity increment, where the update formula is:

[0123] ;

[0124] ;

[0125] ;

[0126] In the formula: For nodes The displacement increment; for Time Node speed; for Time Node speed; for Time Node The displacement; for Time Node displacement

[0127] By using geometric equations, displacement increments are transformed into strain increments, providing a basis for stress calculation.

[0128] Strain increment :

[0129] ;

[0130] In the formula: The change in strain is dimensionless. , All are displacement increment components, in meters; It is the partial derivative of the displacement increment in the coordinate direction, used to describe the rate of change of displacement with spatial position.

[0131] The stress-strain relationship of soil in the elastic stage follows the generalized Hooke's law. FLAC3D adopts an isotropic linear elastic constitutive model, and its elastic stress increment form is as follows:

[0132] ;

[0133] In the formula: This represents the increment of elastic stress. Shear modulus Let Lamé constant be . For strain increment; For volumetric strain increment, It is a tensor shrinkage index, essentially a measure of... The normal strain increments in the three directions are summed.

[0134] shear modulus With Lamé constant The elastic modulus can be obtained from the engineering elastic constant. Poisson's ratio The conversion yields:

[0135] ;

[0136] ;

[0137] Elastic constitutive models are used to describe the stress-strain response of soil under small deformation and unyielded conditions, and are the foundational stage for elastoplastic calculations. When the effective stress of the soil reaches the yield strength, it enters the elastoplastic stage. FLAC3D uses the Mohr-Coulomb elastoplastic constitutive model to describe the shear failure and plastic flow characteristics of soil. This model includes three core steps: elastic prediction, yield determination, and plastic correction.

[0138] First, an elastic prediction is performed, and the elastic test stress is calculated from the total strain increment:

[0139] ;

[0140] In the formula: for The stress column vector at time t; for The column vector of elastic test stress at time t; Here is the elastic stiffness matrix; This represents the total strain increment.

[0141] Subsequently, the Mohr-Coulomb yield criterion is used to determine whether the element yields: when the shear yield function... When the element yields under shear, the tensile yield function... Tensile yielding occurs at this time.

[0142] Shear yield function for:

[0143] ;

[0144] Tensile yield function for:

[0145] ;

[0146] In the formula: , These are the maximum and minimum principal stresses, respectively; It is cohesive force; It is the internal friction angle; This represents the uniaxial tensile strength. Shear yield function. and tensile yield function Principal stresses , It is based on elastic test stress The two stresses, obtained by solving the tensor principal stresses, are different expressions of the same stress state. The elastic test stress is a stress tensor in a rectangular coordinate system, while the principal stresses are the eigenvalues ​​of this tensor after transformation into the principal stress space, serving as the direct calculation basis for determining whether the soil has yielded. Simply put, the elastic test stress is the basic input, the principal stresses are the tensor transformation result of the elastic test stress, and finally, the yield determination is completed by substituting the principal stresses into the yield function. These three constitute the core logical chain of elastic prediction and yield determination in the Mohr-Coulomb elastoplastic model.

[0147] FLAC3D uses the non-associated flow rule to describe plastic flow characteristics, and the shear plastic potential function. for:

[0148] ;

[0149] In the formula: To ensure the numerical stability of plasticity calculations, the dilatation angle is used. Yield function. Its function is to determine whether soil has undergone shear yielding, using the plastic potential function. After determining the soil yield, the direction of plastic deformation and the magnitude of deformation are determined. These two factors work together to complete the full elastoplastic calculation of "judging yield → determining deformation → correcting stress".

[0150] Finally, plastic correction (stress reflection) is performed to adjust the elastic test stress to the yield surface. The essence of plastic correction (stress reflection) is: when the elastic test stress exceeds the Mohr-Coulomb yield surface ( >0), by correcting the elastic test stress of the over-yield through plastic strain increment, the corrected stress is finally allowed to fall back onto the yield surface, and the shear yield plastic multiplier These are the core parameters for correcting calculations. When soil undergoes shear yielding, the elastic test stress... This refers to the virtual stress exceeding the yield strength (i.e., the stress obtained by assuming the soil is perfectly elastic, exceeding the actual shear strength of the soil). Since the actual stress in the soil cannot exceed the yield surface, it is necessary to subtract the stress increment corresponding to the exceeding yield strength through plastic correction. This subtracted stress increment is determined by the plastic strain increment. It was calculated that, The direction is determined by the plastic potential function The gradient is determined by the plastic multiplier, and its magnitude is determined by the plastic multiplier. The only decision. The more severe the over-yield ( The larger ( The larger the value, the greater the increase in stress that needs to be corrected.

[0151] Plastic multiplier at shear yield for:

[0152] ;

[0153] In the formula: It is a plastic multiplier; This represents the shear yield function value corresponding to the elastic test stress.

[0154] ;

[0155] In the formula: For the plastic strain increment tensor; It is a plastic multiplier; Let be the partial derivative of the plastic potential function with respect to the total stress tensor.

[0156] The corrected final stress is:

[0157] ;

[0158] Through the above process, accurate simulation of soil elastic-plastic deformation is achieved, providing a mechanical field basis for coupled calculations.

[0159] In obtaining final elastoplastic stress at time Then, the volumetric strain increment is derived from the total elastic-plastic strain increment. This parameter is the core source term for the deformation field feedback seepage field, realizing the bidirectional coupling between the elasto-plastic deformation field and the seepage field. Under the small deformation assumption, the total elasto-plastic strain increment of the soil element is a linear superposition of the elastic strain increment and the plastic strain increment, i.e. = + The volumetric strain increment is within three-dimensional space. The sum of the elastic-plastic normal strain increments in the three directions is only related to the normal strain and not to the shear strain. The calculation formula is:

[0160] ;

[0161] In the formula: This represents the volumetric strain increment; This represents the elastic volumetric strain increment; For the plastic volumetric strain increment, For tensor shrinkage indices, take 1, 2, and 3 corresponding to... direction; >0 indicates soil volume expansion. <0 indicates that the soil volume is compressed.

[0162] The volumetric strain increment is connected to the seepage field through the volumetric strain rate, transforming the volumetric strain increment within the time step into a differential form of the volumetric strain rate. (Δt is the calculation time step), directly substitute the volume force term into the fluid-structure interaction continuity equation:

[0163] Soil volume deformation causes changes in pore volume, which in turn alters pore water pressure. The pore water pressure distribution is as follows: pore water pressure increases during volume compression and decreases during volume expansion. The new pore water pressure obtained from the solution is used as the initial input for the deformation field in the next time step. Substituting this input into the effective stress principle, a two-way coupled closed-loop iteration of the deformation field and seepage field is formed, achieving time-step synchronized coupled simulation.

[0164] (2) The calculation concept of the seepage field is to use the volumetric strain increment output by the strain field. As the source term, it is substituted into the incremental form of the seepage continuity equation, and the Darcy's law governing the seepage velocity is solved to obtain the increment of pore water pressure. Update the pore water pressure distribution and the seepage field distribution.

[0165] Specifically, in order to describe the fluid flow characteristics of deformable porous media, a seepage continuity equation is constructed, as follows:

[0166] ;

[0167] In the formula: For Hamiltonian operators; For permeability tensor; For fluid dynamic viscosity; The gradient of pore water pressure; For fluid density; It is the acceleration due to gravity; Elevation coordinates; Elevation gradient; Source and sink terms per unit volume; Porosity.

[0168] Introducing fluid compressibility The equations are expanded into a fluid-structure interaction form in relation to volumetric strain:

[0169] ;

[0170] In the formula: The volumetric strain rate is the core term of the deformation field feedback seepage field, reflecting the influence of skeleton deformation on the amount of pore fluid stored.

[0171] The seepage velocity follows Darcy's law, and its expression is:

[0172] ;

[0173] In the formula: Here, represents the Darcy seepage velocity; the negative sign indicates that the velocity decreases along the direction of the total head. Darcy's law, combined with the seepage continuity equation, forms a complete set of governing equations for the seepage field. In numerical calculations, the continuity equation is transformed into an incremental form to accommodate explicit iterative calculations in FLAC3D.

[0174] ;

[0175] In the formula: This represents the increase in pore water pressure. This represents the volumetric strain increment; This represents the elevation increment. Through this incremental equation, the dynamic coupling and iteration of the seepage field and the deformation field are achieved.

[0176] S4: Simulate the coupled evolution of the deformation field and seepage field of the target tailings dam based on the dual-path geometric model after mesh generation, until the calculation step size in the target tailings dam failure / coupling calculation parameters reaches the preset value.

[0177] In practice, the updated pore water pressure is substituted back into the effective stress principle to correct the effective stress state in the next time step, and it participates again in the force balance calculation of the deformation field. Simultaneously, the changes in pore structure caused by deformation update the permeability parameters and feed them back into the seepage field calculation. These steps are repeated until the model reaches the unbalanced force convergence criterion or the simulation reaches the specified calculation time, ultimately achieving a full simulation of the coupled evolution of seepage and deformation in the tailings dam. The unbalanced force convergence criterion in FLAC3D is the core basis for determining whether the model has reached mechanical equilibrium in static calculations. Essentially, it determines whether the model has converged by quantifying the out-of-balance force at each node grid point and its ratio to the reference force. This demonstrates the inherent connection between the seepage field and the deformation field, achieving bidirectional coupling through the effective stress principle and the volumetric strain source term. This ensures both the independence of mechanical calculations and seepage calculations while achieving dynamic synergy between the two, enabling accurate simulation of the complete evolution of the tailings dam from seepage and infiltration to slope deformation and dam failure. The two-way coupled calculation of the seepage field and deformation field is realized by FLAC3D time step iteration. Each calculation time step completes the complete loop of "deformation field calculation, seepage field calculation, and coupling feedback update".

[0178] Example 2

[0179] This embodiment provides a tailings dam failure simulation system, which is used to perform the steps of the method described above, including:

[0180] Data acquisition and preprocessing module: Acquires multi-source heterogeneous spatial data of the target tailings dam and performs data preprocessing to obtain elevation data;

[0181] Dual-path geometric model construction module: Based on preprocessed elevation data, a dual-path geometric model is constructed, and meshing and initialization of the running parameters of the dual-path geometric model are performed; wherein, the dual-path geometric model includes a two-dimensional profile model and a three-dimensional global reality model; the running parameters are the mechanism parameters of the two-dimensional profile model, the spatial constraint data of the three-dimensional global model, and the coupling calculation parameters;

[0182] Control equation determination module: determines the deformation-seepage coupling control equations of the dual-path geometric model; the deformation-seepage coupling control equations are used to simulate the entire deformation-seepage coupling evolution process of the tailings dam;

[0183] Simulation module: Based on the dual-path geometric model after mesh generation, the simulation module simulates the coupled evolution process of the deformation field and seepage field of the target tailings dam until the calculation step size in the target tailings dam failure / coupling calculation parameters reaches the preset value.

[0184] Furthermore, the system also includes a result analysis and visualization module: used to perform multi-dimensional quantitative analysis of the coupled calculation results, including seepage field, deformation field, mechanical field and the entire dam break process, to quantify the dam break disaster risk characteristics, and then present the calculation results through two-dimensional and three-dimensional visualization.

[0185] Specifically, the results analysis and visualization module focuses on two-dimensional verification and three-dimensional reconstruction. It verifies the reliability of the model through multi-source data analysis and visualization, reveals the seepage-deformation coupling evolution and dam failure instability law of tailings dam, quantifies disaster risk characteristics, and provides data support and decision-making basis for engineering prevention and control.

[0186] In terms of results analysis, to achieve quantitative analysis of multi-field coupling characteristics, the spatiotemporal distribution of the phreatic line, the characteristics of pore water pressure accumulation, and the changes in seepage gradient under different reservoir water level conditions were analyzed to identify piping and soil erosion risk zones, revealing the weakening mechanism of the seepage field evolution on effective stress and its temporal correlation with deformation initiation. To understand the evolution of the deformation field, the displacement and deformation rate of key points in the dam body were extracted, and the slip characteristics of the two-dimensional profile and the distribution of the three-dimensional global deformation concentration area were analyzed to define the stage threshold from elastic deformation to accelerated instability and clarify the morphology of potential slip surfaces and slip bodies. To reveal the mechanical field and instability characteristics, based on the Mohr-Coulomb criterion, the initiation and expansion path of the plastic zone, the stress concentration area, and the dynamic changes of the safety factor were analyzed to determine instability modes such as shear slip and tensile-slip composite, and to clarify the critical conditions for dam failure initiation. The entire process and risk analysis of dam failure rely on a three-dimensional model to analyze the initiation location and mechanism of dam failure, the timing and scale of breach expansion, and to quantify the trajectory of the sliding body, the accumulation range and downstream inundation area. Parameter sensitivity analysis is carried out to identify core risk control factors such as permeability coefficient and reservoir water level.

[0187] In terms of visualization, two-dimensional profiles are used to display the spatial distribution and dynamic evolution of seepage, deformation, and mechanical fields through cloud maps and time-series curves. The three-dimensional model uses spatial cloud maps to reconstruct the entire coupling process and the scope of dam failure disasters. Standardized legends, color codes, and annotations ensure the results are intuitive and rigorous. The visualization of the results leverages the core laws of dual-path simulation to identify key characteristics and weak points of tailings dam failures. Targeted suggestions are proposed for seepage control, slope reinforcement, water level management, and monitoring and early warning, providing technical support for the safe operation of the project.

[0188] Example 3

[0189] This embodiment provides a readable storage medium storing a computer program that, when invoked by a processor, performs the steps of the method described above.

[0190] Example 4

[0191] This embodiment provides an electronic terminal, including a processor and a memory, wherein the memory stores a computer program, and the processor calls the computer program to perform the steps of the method described above.

[0192] It should be understood that, in the embodiments of the present invention, the processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. The memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.

[0193] The readable storage medium is a computer-readable storage medium, which can be an internal storage unit of the controller described in any of the foregoing embodiments, such as the controller's hard drive or memory. The readable storage medium can also be an external storage device of the controller, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the controller. Further, the readable storage medium can include both the controller's internal storage unit and external storage devices. The readable storage medium is used to store the computer program and other programs and data required by the controller. The readable storage medium can also be used to temporarily store data that has been output or will be output.

[0194] Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0195] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0196] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

[0197] To further illustrate the technical solution of this application, an application example is provided as follows:

[0198] A tailings dam located near a mountain was selected as the implementation object. This tailings dam was constructed using the upstream method, with a current dam height of 37m and a designed slope of 1:2.2. The dam's dimensions along its strike are much larger than its cross-sectional width, and the topography and geological conditions vary uniformly along the strike, satisfying the plane strain mechanics assumptions. Using a profile model will not alter the core stability laws, allowing for a simplified two-dimensional analysis instead of a three-dimensional one. The dam fill material is fine sandy tailings, and the dam foundation is a layer of silty clay. The reservoir area is significantly affected by seasonal rainfall, and seepage traces are present in the upper and middle parts of the dam slope, indicating a prominent risk of local slope instability. Considering all factors, this embodiment is suitable for using CAD engineering profiles combined with FLAC3D's zone extrude command-based two-dimensional profile extrusion modeling to conduct a specialized analysis of typical cross-sectional slope stability, accurately determining the dam slope instability mode, safety margin, and weak points at the profile scale.

[0199] First, profile data acquisition and 2D profile extrusion modeling based on the zone extrude command were implemented. Typical main cross-section CAD as-built profiles of the tailings dam were collected, redundant lines were cleaned, and core geometric feature lines such as the dam crest outline, dam slope surface, dam foundation interface, location of drainage blind pipes, and reservoir water level were extracted. Vector topology closure processing was completed, and a FLAC3D compatible DXF format profile file was exported. The processed CAD profiles were imported into FLAC3D software, and a small-scale model was used for profile extrusion modeling based on the zone extrude command. The extrusion command was used to stretch the profile along the normal at a small scale, with a thickness of 50mm to meet the requirements of plane strain analysis. A profile model with a geometric similarity ratio of 1:100 was established, corresponding to entity dimensions of 260m × 50m × 86m. Figure 4 As shown in (a); then, structured mesh generation was adopted to refine the mesh in key areas such as the dam slope surface, dam toe, and dam foundation contact zone to avoid calculation errors caused by mesh distortion. At the same time, measuring points were set up at key nodes of the model, as shown in (a). Figure 4 As shown in (b).

[0200] After modeling was completed, the following mechanical parameters were assigned to the profile model based on the field test results: elastic modulus 13.89 MPa, shear modulus 7.94 MPa, Poisson's ratio 0.25, internal cohesion 10 kPa, internal friction angle of the caprock 15°, internal friction angle of the bedrock 16°, contact surface friction angle 12°, dilatation angle 5°, contact surface stiffness normal and shear stiffness are both 2 MPa, and gravitational acceleration (10 m / s²) is also specified. 2 The displacement distribution of the model was obtained through numerical simulation calculations, as shown below. Figure 5 As shown.

[0201] Analysis of profile deformation and slip characteristics: Slope deformation is mainly concentrated in the upper region, indicating that the upper part of the slope is more significantly affected by the load or that the upper soil strength is relatively low; the lower region has small displacement, indicating that this region may have stronger constraint due to bedrock support and more uniform stress distribution; monitoring results from monitoring points 1-5 set up at the pre-set slip zone location through the previous key measurement point layout are as follows: Figure 6 As shown in (a), the monitoring results of measuring points 6-7, which were set up at key locations on the slope, slope bottom, and slope surface, are as follows. Figure 6 As shown in (b), the maximum overall displacement was 4.884 mm, which is a minor deformation. If this condition is a natural operating state, it indicates that the current slope deformation is within a controllable range and there is no obvious trend of instability.

[0202] The two displacement curves show consistent trends, and the core characteristics of the displacement evolution are as follows: During the rapid deformation stage (Step = 0~0.4×10³), the displacements of all measuring points increase rapidly (large curve slope), indicating that the slope stress is rapidly redistributed and deformation is concentrated in the initial stage of calculation; this is the stable convergence stage. After Step = 0.4×10³, the displacement rate gradually slows down, and the curve tends to flatten, indicating that the slope deformation gradually stabilizes and the stress reaches a new equilibrium state. Figure 6 (b) The final displacement of some measuring points reached approximately -4.5 mm, which is higher than... Figure 6 (a) Some measuring points show greater deformation. This time history curve reflects the deformation convergence characteristics of the slope simulation process: the curve eventually flattens out, indicating that the slope deformation has converged and the slope has reached a new mechanical equilibrium under the current working condition, that is, no instability or failure has occurred.

[0203] Model stress cloud diagram as follows Figure 7 As shown, where, Figure 7 (a) to (e) are stress contour maps for multiple dimensions, including maximum, minimum, x-axis, y-axis, and z-axis. The red areas in the maps only show small-scale tensile stresses locally, while the yellow, green, and blue areas represent the dominant stress state color gradient of the slope. Figure 8As shown, the tensile stress zone only exhibits small-scale tensile stress at local protrusions on the slope, with a maximum of approximately 1.136 kPa and a very limited range. The compressive stress concentration zone is located in the lower and middle parts of the slope, with a minimum value of 2.2743 MPa, which is the core area of ​​stress concentration. From the lower and middle parts of the slope upwards and towards the top, the compressive stress gradually decreases, approaching zero at the top, where minor tensile stress appears. Combined with the slope's mechanical properties, this stress distribution indicates that the lower and middle parts of the slope bear the main load, hence the compressive stress concentration. If the soil strength in this area is insufficient, compressive-shear failure is likely to occur. The local tensile stress zone occurs at the protrusions on the slope; although the tensile stress level is small, under long-term loading or rainfall, the tensile stress may induce cracks, becoming seepage channels and thus weakening the slope stability. The contour map shows that the overall model is dominated by compressive stress, with a limited range of tensile stress, indicating that the slope's stress state under current conditions is mainly under compression, and there is currently no risk of large-scale tensile cracking.

[0204] Based on the above simulation results, the strength reduction calculation of the model is further performed. Figure 9 This represents the displacement contour plot changes at each stage of the reduction process, where... Figure 9 (a)~ Figure 9 (i) Displacement cloud maps corresponding to calculation steps of 1000, 2000, 2500, 3000, 3500, 4000, 4500, 5000, and 5255, respectively. The safety factor of the slope profile at normal water level is 1.31. When the safety requirements of the specification are met, the plastic zone is only sporadically distributed and not connected at the dam toe. When the safety factor drops to 0.90 under the condition of sudden drop in water level, the shear plastic zone is completely connected along the potential slip surface, and the slope profile is judged to be in an unstable state. The safety factor under the condition of rainstorm is only 0.83. The tensile plastic zone develops at the rear edge of the dam crest, forming a tensile-shear composite failure mode.

[0205] For the weak slip zone in the upper part of the dam slope presented by the two-dimensional profile tensile modeling simulation based on the zone extrude command, a treatment scheme of slope toe surcharge counterpressure plus slope anchor reinforcement was designed. The treatment parameters were substituted into the original Exclusion profile model for recalculation. The slope safety factor showed a rebound, the range of the plastic zone was greatly reduced, the burial depth of the phreatic line was restored to the safe range, and the profile slope returned to a stable state.

Claims

1. A method for simulating tailings dam failure, characterized in that, include: S1: Acquire multi-source heterogeneous spatial data of the target tailings dam and perform data preprocessing to obtain elevation data; S2: Based on the preprocessed elevation data, a dual-path geometric model is constructed, and meshing and initialization of the running parameters of the dual-path geometric model are performed; wherein, the dual-path geometric model includes a two-dimensional profile model and a three-dimensional global reality model; the running parameters are the mechanism parameters of the two-dimensional profile model, the spatial constraint data of the three-dimensional global model, and the coupling calculation parameters; S3: Determine the deformation-seepage coupling control equations for the dual-path geometric model; the deformation-seepage coupling control equations are used to simulate the entire deformation-seepage coupling evolution process of the tailings dam. S4: Simulate the coupled evolution of the deformation field and seepage field of the target tailings dam based on the dual-path geometric model after mesh generation, until the calculation step size in the target tailings dam failure / coupling calculation parameters reaches the preset value. The deformation field in the deformation-seepage coupling control equation of the dual-path geometric model in S3 is set as follows: Formula for converting pore water pressure into effective stress: ； In the formula: , The direction of the three-dimensional rectangular coordinate system. Corresponding to direction; For effective stress tensor; This is the total stress tensor; The Kronecker function; Pore ​​water pressure; Arbitrary grid node If the rate of change of momentum equals the net external force, then the discrete incremental form of the nodal motion equations is: ； In the formula: For nodes Concentrated mass; For nodes Speed ​​increment; To calculate the time step; For nodes The sum of internal forces generated by the effective stress. Corresponding to direction; This refers to the external force term resulting from the total water action. Displacement increment Update formula: ； ； ； In the formula: For nodes The displacement increment; for Time Node speed; for Time Node speed; for Time Node The displacement; for Node of time The displacement; Strain increment : ； in, For strain increment; , All are displacement increment components; This is the partial derivative of the displacement increment in the coordinate direction; Elastic stress increment Calculation formula: ； ； ； in, This represents the increment of elastic stress. Shear modulus; Let Lamé's constant be denoted by . For strain increment; The Kronecker function; For volumetric strain increment, specifically for The normal strain increments in the three directions are summed. It is the elastic modulus; Poisson's ratio; Elastic stress calculation formula: ； In the formula: Let be the stress column vector at time t+Δt; Let be the column vector of elastic test stress at time t+Δt; Here is the elastic stiffness matrix; This represents the total strain increment; The stress correction formula is: ； in, Let be the final elastoplastic stress tensor at time t+Δt; Let be the elastic stress tensor at time t+Δt; For the plastic strain increment tensor; This represents the plastic volumetric strain increment; The seepage field setting in the deformation-seepage coupling control equation of the dual-path geometric model in S3 is as follows: Incremental form of the seepage continuity equation: ； In the formula: For Hamiltonian operators; For permeability tensor; For fluid dynamic viscosity; This represents the increase in pore water pressure. For fluid density; It is the acceleration due to gravity; Elevation increment; Porosity; The fluid compressibility coefficient; For the increase of source and sink items; The volumetric strain increment output by the deformation field; The rate of change of volumetric strain over time; Seepage velocity: ； In the formula, This represents the Darcy seepage velocity; the negative sign indicates that the velocity decreases along the direction of the total head.

2. The method according to claim 1, characterized in that, The multi-source heterogeneous spatial data includes macro-regional benchmark elevation data of the area where the target tailings dam is located, downloaded from the geospatial data cloud platform, CAD elevation data map of the target tailings dam mining area, and topographic data of the target tailings dam obtained by drone aerial photography.

3. The method according to claim 2, characterized in that, In S2, the construction process of the two-dimensional profile model is as follows: S211: Clean up the layers and remove redundant elements from the preprocessed elevation data, generate a closed dam body profile domain, clarify the boundaries of each material zone, and label the geometric dimensions and elevation parameters of each zone. S212: Import the processed CAD profile into the modeling software, set the tensile thickness to meet the preset plane strain analysis requirements, and use commands to stretch the model along the normal of the profile to obtain a two-dimensional profile model with a preset geometric similarity ratio to the target tailings dam. S213: Mesh the two-dimensional profile model, refine the mesh in the preset key areas, and sparse the mesh in the non-key areas; S214: Evaluate the mesh quality based on preset quality standards: If the mesh quality fails, refine / coarse the local mesh until it meets the preset standards; otherwise, set the boundary conditions of the two-dimensional profile model, load the initial stress field and load, and complete the construction and debugging of the two-dimensional profile model.

4. The method according to claim 2, characterized in that, In S2, the specific construction process of the 3D global reality model is as follows: S221: Import the pre-processed elevation data of the target tailings dam into the 3D modeling software, complete the point cloud to surface conversion, terrain meshing, and dam outline fitting operations, construct the full-domain 3D real-scene model of the tailings dam and export it into the data format that the simulation software can receive. S222: The simulation software completes model repair and mesh reconstruction based on the received data, refines the mesh of the dam body and the area affected by the seepage line, and clarifies the material partition boundaries, seepage channels and displacement boundary conditions. S223: Preserve the topographic undulations and spatial correlation features of the entire tailings dam area, and perform full-domain adaptation of the 3D real-scene volume model; among them, the dual-path geometric models are mutually verified.

5. A tailings dam failure simulation system, said system being used to perform the steps of the method according to any one of claims 1-4, characterized in that, include: Data acquisition and preprocessing module: Acquires multi-source heterogeneous spatial data of the target tailings dam and performs data preprocessing to obtain elevation data; Dual-path geometric model construction module: Based on preprocessed elevation data, a dual-path geometric model is constructed, and meshing and initialization of the running parameters of the dual-path geometric model are performed; wherein, the dual-path geometric model includes a two-dimensional profile model and a three-dimensional global reality model; the running parameters are the mechanism parameters of the two-dimensional profile model, the spatial constraint data of the three-dimensional global model, and the coupling calculation parameters; Control equation determination module: determines the deformation-seepage coupling control equations of the dual-path geometric model; the deformation-seepage coupling control equations are used to simulate the entire deformation-seepage coupling evolution process of the tailings dam; Simulation module: Based on the dual-path geometric model after mesh generation, the simulation module simulates the coupled evolution process of the deformation field and seepage field of the target tailings dam until the calculation step size in the target tailings dam failure / coupling calculation parameters reaches the preset value.

6. The system according to claim 5, characterized in that, The system also includes a result analysis and visualization module: used to perform multi-dimensional quantitative analysis of the coupled calculation results, including seepage field, deformation field, mechanical field and the entire dam break process, to quantify the dam break disaster risk characteristics, and then present the calculation results through two-dimensional and three-dimensional visualization.

7. A readable storage medium, characterized in that: A computer program is stored, which, when invoked by a processor, performs the steps of the method according to any one of claims 1-4.

8. An electronic terminal, characterized in that: It includes a processor and a memory, the memory storing a computer program, the processor calling the computer program to perform the steps of the method according to any one of claims 1-4.

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