A numerical simulation analysis method and system for pollutant migration of a geotechnical barrier wall, an electronic device and a storage medium

Abstract

The application discloses a numerical simulation analysis method and system for pollutant migration of a geotechnical barrier wall, an electronic device and a storage medium, aiming to solve the technical problem that after a huge concentration change outside the barrier wall is captured by an existing algorithm, it is misjudged as a severe pollutant diffusion, and then the time step is reduced, resulting in waste of computing power or matrix oscillation. The method comprises obtaining initial physical parameters, performing spatial discretization grid division and determining an initial time step; calculating the penetration warning degree and the penetration coefficient of the grid node; updating the time step based on the global maximum value of the penetration coefficient; driving the finite element solver to iteratively solve until the preset engineering service period is reached. Through the calculation of the penetration warning degree and the penetration coefficient, the time step is adaptively updated, avoiding the misjudgment problem of the traditional algorithm, and improving the simulation efficiency and accuracy.

Description

Technical Field

[0001] This application relates to the field of data processing and numerical calculation technology, specifically to a numerical simulation analysis method, system, electronic device and storage medium for the migration of pollutants in a soil and rock barrier wall. Background Technology

[0002] In modern industrial and urban development, facilities such as landfills and chemical plants inevitably produce toxic and harmful leachate (i.e., pollutants). If these pollutants seep into the groundwater system, they will cause irreversible ecological disasters. To prevent the spread of pollutants, engineers construct a wall made of highly impermeable materials, known as a rock and soil barrier wall, underground around the pollution source. Because barrier walls are usually buried deep, have a long service life, and are located in areas with complex hydrogeological conditions and groundwater environments, relying solely on on-site drilling and sampling, and in-situ monitoring, is insufficient to effectively identify barrier defects and failure risks.

[0003] Currently, the analysis of pollutant migration processes in soil and rock barriers mainly relies on numerical simulation methods, which construct geometric models to achieve numerical solutions for steady-state or transient migration processes.

[0004] Current numerical simulation techniques for pollutant migration involve statically dividing the study area into grids and configuring independent parameters for each grid to simulate advection migration of pollutants. After discretizing the spatial grid, to simulate the unsteady migration process of pollutants over time, the partial differential equation solver needs to divide continuous physical time into multiple "time steps." However, because the permeability coefficient of the rock and soil barrier is significantly lower than that of the surrounding conventional soil layers, when groundwater carrying pollutants flows through highly permeable soil and impacts the extremely low permeability barrier, the fluid is instantly blocked, and a large amount of pollutants rapidly accumulates on the outside of the barrier, forming a concentration peak. Existing algorithms, after capturing the huge concentration change outside the barrier, misjudge it as a violent pollutant diffusion, and thus reduce the time step. However, this phenomenon is merely a physical accumulation illusion caused by the difference in interfacial permeability, leading to misjudgment. Summary of the Invention

[0005] This application discloses a numerical simulation analysis method for the migration of pollutants in a soil-rock barrier wall. It aims to solve the technical problems of existing numerical simulation algorithms encountering extremely low permeability barrier walls, such as the physical accumulation illusion caused by the difference in interfacial permeability or the parallel passage of high-concentration water flow, which leads to the meaningless shortening of the time step, resulting in a large waste of computing power in long-period simulations, and matrix oscillation and distortion caused by inappropriate time span.

[0006] To achieve the above objectives, the first aspect of this application provides a numerical simulation analysis method for pollutant migration in geotechnical barrier walls, comprising: The initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment are obtained. The initial physical parameters include the spatial grid node coordinate set, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector. Based on the set of spatial grid node coordinates, spatial discretization grid division is performed to obtain global grid nodes, and the initial time step is determined by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector. In the iterative process of solving transient partial differential equations, for any grid node at the current moment, the pollutant concentration values ​​of the node at the current moment and the previous moment are extracted, the absolute value of its concentration fluctuation is calculated, and the permeability coefficient of the node is combined with the ratio of the permeability coefficient of the rock and soil barrier wall material to calculate the permeability warning level of the node. Using the degree of infiltration warning as input, and combining the dot product projection of the current infiltration velocity vector of the node with the unit normal vector of the nearest barrier wall surface, the penetration coefficient of the node is calculated. Extract the global maximum value of the penetration coefficient of all grid nodes within a preset update cycle, input the global maximum value into a preset hyperbolic tangent function to generate a nonlinear smoothing coefficient, and update the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle; The time step of the current iteration cycle is used as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration until the cumulative simulation time reaches the preset engineering service cycle, and the simulation analysis results are output.

[0007] Optionally, the step of obtaining the initial physical parameters of the soil-rock barrier wall and the surrounding groundwater environment, and determining the initial time step by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector, includes: The three-dimensional geometric boundary data of the site is obtained, and the continuous spatial domain composed of the barrier wall and natural soil is divided using the finite element preprocessing algorithm to obtain the set of coordinates of the spatial grid nodes. The theoretical permeability coefficients are assigned to the corresponding grid nodes using in-situ permeability experimental data and spatial interpolation algorithms to construct the initial permeability coefficient matrix. The initial pollutant concentration field data is constructed by using actual concentration data collected from groundwater monitoring wells and the definite solution condition assignment method. Combining head boundary data and Darcy's law, the initial three-dimensional seepage velocity field vector of the global grid nodes at the initial moment is calculated based on the initial permeability coefficient matrix; Based on the local feature edge length of each node in the spatial grid node coordinate set and the seepage velocity modulus of the corresponding node in the initial three-dimensional seepage velocity field vector, the ratio of the local feature edge length to the seepage velocity modulus of each node is calculated, and the minimum value of the ratio is taken as the initial time step.

[0008] Optionally, the calculation of the penetration warning level of the node includes: The product of the absolute value of the concentration fluctuation and the ratio of the permeability coefficient is used as the original early warning indicator; The original early warning indicators are standardized to eliminate differences in different dimensions and magnitudes, thereby obtaining the degree of penetration early warning. The permeability warning level is used to characterize the potential impact weight of the pollutant accumulation intensity caused by the sudden change in the permeability coefficient of the current grid node on the permeability stability of the barrier wall. The permeability warning level will be used as an input parameter for subsequent penetration coefficient calculation.

[0009] Optionally, the calculation of the penetration coefficient of the node includes: Calculate the projection component of the seepage velocity vector onto the unit normal vector, which points from the outside to the inside of the barrier wall; The ratio of the projection component to the seepage velocity modulus is directionally filtered using a maximum value function to eliminate water flow interference that is parallel to or away from the barrier wall, thus obtaining the directional weight. The penetration warning level is multiplied by the directional weight to obtain the penetration coefficient; The penetration coefficient is used to quantify the intensity of the positive compressive force exerted by the pollutant-carrying water flow on the barrier wall. The calculation result of the penetration coefficient will be used to extract the global maximum value to drive the time step update.

[0010] Optionally, updating the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration period includes: The deviation term is obtained by subtracting the global maximum value from the preset penetration coefficient safety threshold. The deviation term is input into the hyperbolic tangent function, and the S-shaped saturation characteristic of the hyperbolic tangent function is used to transform the linear deviation into a nonlinear smoothing coefficient with upper and lower limits. The updated time step is obtained by multiplying the initial time step by the nonlinear smoothing coefficient.

[0011] Optionally, the step of using the time step of the current iteration period as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration includes: The time step of the current iteration cycle is injected into the time integration module of the transient partial differential equation numerical solution system; Based on the time integration step, the stiffness matrix and mass matrix of the global grid nodes are discretized and assembled in time, and the pollutant concentration field data and three-dimensional seepage velocity field vector at the current moment are updated. The updated pollutant concentration field data and the three-dimensional seepage velocity field vector are used as inputs for the next iteration cycle. The steps of calculating the seepage warning level, calculating the penetration coefficient, and updating the time step are executed cyclically until the cumulative simulation time reaches the preset engineering service cycle, and the simulation analysis results are output.

[0012] To achieve the above objectives, a second aspect of this application provides a numerical simulation analysis system for pollutant migration in geotechnical barrier walls, comprising: The parameter initialization module is used to obtain the initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment. The initial physical parameters include the spatial grid node coordinate set, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector. Based on the spatial grid node coordinate set, spatial discretization grid division is performed to obtain global grid nodes, and the initial time step is determined by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector. The warning level calculation module is used to extract the pollutant concentration values ​​of any grid node at the current time and the previous time during the iterative process of solving transient partial differential equations, calculate the absolute value of its concentration fluctuation, and combine the permeability coefficient of the node with the ratio of the permeability coefficient of the rock and soil barrier wall material to calculate the permeability warning level of the node. The penetration coefficient calculation module is used to take the penetration warning level as input, combine the dot product projection of the current seepage velocity vector of the node and the unit normal vector of the nearest barrier wall surface, and calculate the penetration coefficient of the node. The step size adaptive update module is used to extract the global maximum value of the penetration coefficient of all grid nodes within a preset update cycle, input the global maximum value into a preset hyperbolic tangent function to generate a nonlinear smoothing coefficient, and update the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle. The simulation solution module is used to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration by using the time step of the current iteration cycle as the time integration step, until the cumulative simulation time reaches the preset engineering service cycle, and output the simulation analysis results.

[0013] To achieve the above objectives, a third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the numerical simulation analysis method for the migration of pollutants in a soil-rock barrier wall as provided in the preceding embodiments.

[0014] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the numerical simulation analysis method for the migration of pollutants in a soil-rock barrier wall as provided in the preceding embodiments.

[0015] To achieve the above objectives, the fifth aspect of this application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a numerical simulation analysis method for the migration of pollutants in a soil and rock barrier wall as provided in the preceding embodiments.

[0016] This application discloses a numerical simulation analysis method for pollutant migration in a soil-rock barrier wall. The method includes obtaining initial physical parameters of the soil-rock barrier wall and surrounding groundwater environment; spatially discretizing the grid based on the coordinate set of spatial grid nodes to obtain global grid nodes; and determining the initial time step by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector. During the iterative process of solving the transient partial differential equations, for any grid node at the current time, the pollutant concentration values ​​of that node at the current time and the previous time are extracted, the absolute value of its concentration fluctuation is calculated, and the permeability warning level of that node is calculated by combining the ratio of the permeability coefficient of that node to the permeability coefficient of the soil-rock barrier wall material. The permeability warning level is then used as... Using the current seepage velocity vector of a node as input, the dot product projection of the unit normal vector of the nearest barrier wall surface is used to calculate the penetration coefficient of that node. The global maximum value of the penetration coefficient for all grid nodes within a preset update cycle is extracted. This global maximum value is then input into a preset hyperbolic tangent function to generate a nonlinear smoothing coefficient. The initial time step is updated based on this nonlinear smoothing coefficient to obtain the time step for the current iteration cycle. The time step of the current iteration cycle is used as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration until the cumulative simulation time reaches the preset engineering service cycle, at which point the simulation analysis results are output. Technical effect: By calculating the ratio of the absolute value of concentration fluctuation to the relative permeability coefficient of grid nodes, the degree of seepage warning is obtained. The penetration coefficient is then calculated by combining the dot product projection of the seepage velocity vector and the unit normal vector of the barrier wall surface. Finally, the global maximum value is extracted based on this penetration coefficient, and the time step of the solver is adaptively updated using the hyperbolic tangent function. This solution solves the technical problem that traditional algorithms misjudge when encountering extremely low permeability barriers due to "physical accumulation illusion" or "parallel flow of high-concentration water", which leads to the time step being shortened meaninglessly. It avoids the waste of computing power in long-cycle simulations and prevents matrix oscillation and distortion caused by inappropriate time span. Attached Figure Description

[0017] Figure 1 A flowchart illustrating a numerical simulation analysis method for pollutant migration in a soil-rock barrier wall, provided in an embodiment of this application; Figure 2 This is a structural block diagram of a numerical simulation analysis system for pollutant migration in a soil and rock barrier wall, provided in an embodiment of this application. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0019] Explanation of key terms: Target data: refers to the initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment, including the set of spatial grid node coordinates, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector.

[0020] Training samples: No machine learning training samples are used in the numerical simulation scenario of this application. The corresponding data objects are the initial pollutant concentration field data and water head boundary data constructed by in-situ monitoring and boundary condition assignment.

[0021] Feature vector: In this application, it is a set of physical features consisting of the local feature edge length, seepage velocity modulus and permeability coefficient ratio of each grid node.

[0022] Model input: refers to the current iteration cycle time step of the time integration module input to the transient partial differential equation numerical solution system, as well as the assembled stiffness matrix and mass matrix.

[0023] Reasoning results: refers to the simulation analysis results output after the finite element solver drives the coupled control equations to solve iteratively, including the evolution of pollutant concentration field and seepage velocity field distribution throughout the entire cycle.

[0024] Prompt information: In this application, the corresponding preset penetration coefficient safety threshold and preset protection ratio are used to constrain the time step update boundary.

[0025] Constraint information: refers to the physical conservation constraints of the coupled control equations of groundwater flow and pollutant migration, as well as the upper and lower limit truncation constraints during the time step update process.

[0026] Multimodal data: In this application, the corresponding data are spatial geometric boundary data, in-situ permeability experimental data, actual concentration data collected from groundwater monitoring wells, and head boundary data, etc., which are multi-source heterogeneous physical monitoring data.

[0027] Edge device / server / terminal: refers to the electronic device that performs the method of this application, which may be set up in an engineering monitoring terminal, server or high-performance computing cluster.

[0028] Business object / controlled object: refers to the rock and soil barrier wall and the surrounding groundwater environment. The method of this application uses numerical calculation to simulate the migration process of pollutants and evaluate the seepage prevention effect.

[0029] Current methods for finite element analysis include: S1: Collect site geometry and hydrogeological data, divide the space into grids, and store the initial permeability coefficient matrix, concentration field data, seepage velocity field vector and initial time step. S2: Calculate the permeability warning level of any node at any given time based on the permeability coefficient of each grid node; S3: Calculate the penetration coefficient of any grid node at any time by combining the penetration warning level and the water flow direction of the grid node; S4: Adaptive time step update based on penetration coefficient; S5: Perform numerical simulation analysis based on the updated time step; Existing technologies for dealing with extremely low-permeability barrier walls typically employ static meshes and fixed time steps. When contaminant accumulation occurs at the interface between high-permeability soil and the low-permeability barrier wall, traditional algorithms directly map the large concentration changes as diffusion instability indicators, mechanically reducing the time step. This approach fails to eliminate the physical accumulation artifacts caused by differences in interfacial permeability, nor does it filter out interference from parallel water flows. This results in the solver performing a large number of invalid matrix iterations during safe periods, and during abrupt changes, it is prone to pathological oscillations due to excessively large time steps, ultimately leading to wasted computational resources and distorted simulation results.

[0030] Example 1 refer to Figure 1 This embodiment provides a numerical simulation analysis method for pollutant migration in a soil-rock barrier wall, addressing the technical problem in the background art where existing algorithms, after capturing large concentration changes outside the barrier wall, misinterpret them as drastic pollutant diffusion, leading to a reduction in the time step, wasted computing power, and matrix oscillation. This method can be executed by a processor, which can be located on a terminal or server. The execution process of this method is as follows: Step S101: Obtain the initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment. The initial physical parameters include the spatial grid node coordinate set, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector.

[0031] In one embodiment of this application, in the seepage prevention project of the soil-rock barrier wall, the site exhibits strong spatial heterogeneity: the external natural aquifer (such as a gravel layer) has large pores, fast groundwater flow velocity, and extremely high permeability coefficient; while the internal soil-rock barrier wall material is dense, the flow velocity is almost stagnant, and the permeability coefficient is extremely low. Therefore, this application collects and initializes geographic hydrological data to ensure the accuracy of subsequent calculation results.

[0032] In an optional embodiment of this application, the initial physical parameters of the soil-rock barrier wall and the surrounding groundwater environment are obtained, and the initial time step is determined by combining the initial permeability coefficient matrix with the initial three-dimensional seepage velocity field vector, including: The three-dimensional geometric boundary data of the site is obtained, and the continuous spatial domain composed of the barrier wall and natural soil is divided using the finite element preprocessing algorithm to obtain the set of coordinates of the spatial grid nodes. The theoretical permeability coefficients are assigned to the corresponding grid nodes using in-situ permeability experimental data and spatial interpolation algorithms to construct the initial permeability coefficient matrix. The initial pollutant concentration field data was constructed by combining actual concentration data collected from groundwater monitoring wells with the boundary condition assignment method. Combining head boundary data and Darcy's law, the initial three-dimensional seepage velocity field vector of the global grid nodes at the initial moment is calculated based on the initial permeability coefficient matrix; Based on the local feature edge length of each node in the spatial grid node coordinate set, and the seepage velocity modulus of the corresponding node in the initial three-dimensional seepage velocity field vector, the ratio of the local feature edge length of each node to the seepage velocity modulus is calculated, and the minimum value of the ratio is taken as the initial time step.

[0033] Specifically, the process of obtaining the initial physical parameters of the soil-rock barrier wall and the surrounding groundwater environment may include the following steps: 1. Spatial geometric modeling: The processor can use the three-dimensional geometric boundary data obtained from on-site geological surveys and topographic mapping, and the existing finite element preprocessing software and spatial discretization mesh generation algorithm (such as Delaunay tetrahedron partitioning) to partition the continuous spatial domain composed of the barrier wall and natural soil, and obtain the set of spatial coordinates of all mesh nodes. 2. Obtain the initial permeability coefficient matrix: The processor can use an in-situ double-ring water injection test instrument and a permeameter to set up sampling points in the natural aquifer and the soil-rock barrier wall to collect the theoretical permeability coefficients of each soil layer; and use a spatial interpolation algorithm to assign the theoretical permeability coefficients to the corresponding grid nodes to obtain the global initial permeability coefficient matrix. 3. Acquire initial pollutant concentration field data: The processor can use groundwater quality monitoring sensors, which are placed in monitoring wells around the pollution source, to collect the actual concentration data of the pollution source; based on the actual concentration data, the processor assigns values ​​to the remaining nodes using the boundary condition assignment method to obtain the pollutant concentration field data of the entire region. 4. Obtain the initial three-dimensional seepage velocity field vector: The processor can use the groundwater level monitoring wells and pore water pressure gauges deployed on site to collect the actual head boundary data (water level and water pressure) of key nodes in the site; combined with the permeability coefficient matrix obtained above, the processor can use a finite element solver (based on Darcy's law) to calculate the three-dimensional seepage velocity field vector of the global grid nodes at the initial moment. 5. Calculate the initial time step: The processor can obtain the local feature edge length corresponding to any node in the global grid (for any node, the minimum length of the geometric edge directly connected to the node is taken as the local feature edge length of the node); calculate the seepage velocity vector magnitude of the node; and take the ratio of the seepage velocity vector magnitude to the local feature edge length as the initial time step of the node.

[0034] Step S102: Based on the set of spatial grid node coordinates, perform spatial discretization grid division to obtain global grid nodes, and combine the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector to determine the initial time step.

[0035] Furthermore, obtain the local feature edge length corresponding to any node in the global grid (for any node, take the minimum length of the geometric edge directly connected to the node as the local feature edge length of the node); calculate the seepage velocity vector magnitude of the node; and take the ratio of the seepage velocity vector magnitude to the local feature edge length as the initial time step of the node.

[0036] Step S103: In the iterative process of solving the transient partial differential equation, for any grid node at the current moment, extract the pollutant concentration values ​​of the node at the current moment and the previous moment, calculate the absolute value of its concentration fluctuation, and combine the permeability coefficient of the node with the ratio of the permeability coefficient of the rock and soil barrier wall material to calculate the permeability warning level of the node.

[0037] It should be noted that when groundwater carrying contaminants impacts a barrier wall with extremely low permeability, the fluid is instantly blocked. The contaminants cannot immediately penetrate the wall, leading to severe contaminant accumulation on the water-facing side of the barrier. This causes a surge in contaminant concentration on the outer side of the wall, resulting in a huge absolute concentration change. Traditional methods, upon detecting this huge absolute concentration change, incorrectly determine that the system is in a state of severe diffusion instability, drastically shortening the time step. This results in the computer wasting significant computing power trying to solve for the almost stationary contaminants blocked outside the wall. Therefore, this invention analyzes the permeability coefficient of each grid node to determine the permeability warning level of any node at any given time.

[0038] In an optional embodiment of this application, the penetration warning level of the node is calculated, including: The product of the absolute value of the concentration fluctuation and the ratio of the permeability coefficient is used as the original early warning indicator; The original early warning indicator was standardized to eliminate differences in different dimensions and magnitudes, thus obtaining the degree of penetration warning. The permeability warning level is used to characterize the potential impact weight of the pollutant accumulation intensity caused by the sudden change in the permeability coefficient of the current grid node on the permeability stability of the barrier wall. The permeability warning level will be used as the input parameter for subsequent penetration coefficient calculation.

[0039] Specifically, the calculation formula for the penetration warning level of any node at any given time is as follows: ; In the formula, Indicates the first The grid node at the ... The level of early warning for infiltration at any given moment; Indicates the first The grid node at the ... The pollutant concentration value at any given time; Indicates the first The grid node at the ... The pollutant concentration value at any given time; The permeability coefficient of the soil-rock barrier wall material; Indicates the first The permeability coefficient of each grid node; Indicates the absolute value symbol; Denotes the standard normalization function, where, For example, to preset a minimum constant, To avoid the denominator being 0.

[0040] The permeability warning level refers to the permeability warning level of any grid node based on the permeability coefficient of the barrier wall. The larger the value, the closer the grid node is to the barrier wall and the larger the fluctuation of the permeability coefficient, indicating a higher warning level. The smaller the value, the farther the grid node is from the barrier wall or the smaller the fluctuation of the permeability coefficient, indicating a lower warning level.

[0041] This indicates the volatility of pollutants at that grid node; the larger the value, the greater the volatility, and the smaller the value, the smaller the volatility. This represents the ratio of the current grid node's permeability coefficient to the barrier wall. The closer the value is to 1, the closer the current grid node is to the barrier wall; conversely, the farther away it is, the farther away it is from the barrier wall. If the distance to the barrier wall is large or small, it has no effect on the permeability of the barrier wall, regardless of whether the grid node's fluctuation is large or small. Only when the distance to the barrier wall is large and the fluctuation is large is it determined that the permeability coefficient of the barrier wall is affected.

[0042] At this point, the calculation of the penetration warning level of any grid node at any given time is complete.

[0043] Step S104: Using the degree of infiltration warning as input, and combining the dot product projection of the current infiltration velocity vector of the node and the unit normal vector of the nearest barrier wall surface, the penetration coefficient of the node is calculated.

[0044] It is understandable that groundwater flow is not stagnant but directional. Due to the hydraulic gradient of groundwater and the distribution of surrounding pumping wells, groundwater carrying high concentrations of pollutants can flow in multiple directions, such as parallel to the barrier wall, flowing away from the barrier wall, and not always perpendicularly impacting the barrier wall. Parallel flow does not exert positive compressive force on the barrier wall; that is, as long as the groundwater carrying pollutants does not exert a direct impact force on the barrier wall, even if the concentration of pollutants outside the barrier wall is extremely high, it does not pose a threat to the barrier wall. However, when the system encounters parallel flow with high concentrations, the seepage warning level remains high. Therefore, this application calculates the penetration coefficient of any node by analyzing the flow direction and the seepage warning level.

[0045] In an optional embodiment of this application, the penetration coefficient of the node is calculated, including: Calculate the projection component of the seepage velocity vector onto the unit normal vector, which points from the outside to the inside of the barrier wall; The ratio of the projection component to the seepage velocity modulus is used to perform directional filtering by taking the maximum value function to eliminate water flow interference that is parallel to or away from the barrier wall, and the directional weight is obtained. The penetration warning level is multiplied by the directional weight to obtain the penetration coefficient; The penetration coefficient is used to quantify the intensity of the positive compressive force exerted by the pollutant-carrying water flow on the barrier wall. The calculation result of the penetration coefficient will be used to extract the global maximum value to drive the time step update.

[0046] Specifically, in one embodiment, for any grid node, the value of the grid node at the 1st... seepage velocity vector at time t And calculate its modulus. Get the unit normal vector (pointing from outside the wall to inside the wall) of the barrier wall surface closest to this grid node. Calculate the grid node at the th The penetration coefficient at time t is calculated using the following formula: ; In the formula, Indicates the first The grid node at the ... Penetration coefficient at any given moment; Indicates the first The grid node at the ... The level of early warning for infiltration at any given moment; Indicates the first The grid node at the ... The seepage velocity vector at any given time; Indicates the distance to the first The unit normal vector of the nearest barrier wall surface to each grid node; Indicates the first The grid node at the ... The magnitude of the seepage velocity vector at time t; This represents the function that takes the maximum value, where, For example, to preset a minimum constant, To avoid the denominator being 0.

[0047] in, Indicates the first The seepage velocity component that causes positive compression of the barrier wall surface by the groundwater flow field at any given time; through calculation and The ratio of the vectors is used to achieve the purpose of dimensionless processing, that is, to represent the vectors. and The cosine of the included angle; by utilizing The function is set to zero if there is a water flow parallel to or away from the barrier wall, and the penetration coefficient is further set to 0.

[0048] This completes the step of calculating the penetration coefficient of groundwater flow relative to the barrier wall at any given time for any grid node.

[0049] Step S105: Extract the global maximum value of the penetration coefficient of all grid nodes within the preset update cycle, input the global maximum value into the preset hyperbolic tangent function to generate a nonlinear smoothing coefficient, and update the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle.

[0050] Understandably, the time step is a core driving parameter for transient solutions to partial differential equations, essentially representing the sampling interval for the computer to capture continuous physical processes. Since computers cannot analyze continuous event flows, they need to be discretized into multiple independent time spans. Within each tiny time span, the solver assembles the finite element matrix of the global mesh based on linearization assumptions. Due to the long service life of the soil-rock barrier, during its service, water carrying pollutants may exhibit various behaviors, such as sweeping across the wall in a parallel motion, moving away from the wall, or impacting the wall at a large angle. If the numerical solver consistently uses a fixed time step throughout the entire simulation cycle, the following two scenarios will occur: Scenario 1: In order to accurately capture the details of mutations during high-risk periods, it is necessary to set an extremely small time step. This will cause the computer to perform a large number of meaningless matrix iterations during a long safe period, resulting in a significant waste of computing power. Scenario 2: If a large time step is set to improve the solution speed, when encountering a direct impact from pollutants, the excessive time span will cause fluid particles to penetrate the mesh instantly in a single iteration, causing violent oscillations in the iteration matrix and distorting the simulation results.

[0051] Therefore, this application analyzes the changes in the penetration coefficient to adaptively update the time step: when the system determines that the threat is low, the system can increase the time step to simulate and analyze the safe time period at a higher computing speed; when the system determines that the threat is high, the system can decrease the time step to perform simulation and analysis with a smaller time step.

[0052] In an optional embodiment of this application, updating the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle includes: The deviation term is obtained by subtracting the global maximum value from the preset penetration coefficient safety threshold. The deviation term is input into the hyperbolic tangent function, and the S-shaped saturation characteristic of the hyperbolic tangent function is used to transform the linear deviation into a nonlinear smoothing coefficient with upper and lower limits. Multiply the initial time step by the nonlinear smoothing coefficient to obtain the updated time step.

[0053] In this embodiment, the preset empirical value for updating the time step is updated once per hour. For any time when the time step needs to be updated, the maximum value of the penetration coefficient of all grid nodes in all sampling moments after the last update step is obtained.

[0054] The formula for calculating the time step of any update is as follows: ; In the formula, Indicates the first The time step after the next update; Indicates the initial time step; Indicates the first The global maximum value of the penetration coefficient of all grid nodes at the sampling time after the next update time step; For example, the preset hyperparameter represents the safe threshold for the penetration coefficient. The personnel responsible for implementation can be adjusted according to the specific implementation situation; This represents the hyperbolic tangent function, used to transform the linear difference of the input into a non-linear smoothing coefficient with upper and lower bounds.

[0055] Among them, when the system is in a safe period (i.e., the maximum penetration coefficient is below the threshold), When the deviation term is negative, then... It must be greater than 1, meaning that the time step is increased to quickly cross the safe period; When the system faces a threat (i.e., the maximum penetration coefficient exceeds the threshold), When the deviation term is positive, then... A value greater than 0 and less than 1 indicates the system's contraction time step.

[0056] Step S106: Use the time step of the current iteration cycle as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration until the cumulative simulation time reaches the preset engineering service cycle, and output the simulation analysis results.

[0057] In one embodiment of this application, the updated time step obtained above is used as the time integration step of the transient partial differential equation numerical solution system; the groundwater flow and pollutant migration coupled control equations are iteratively solved based on the time integration step using the existing finite element solution algorithm; until the cumulative simulation time of the system reaches the preset engineering service cycle; all datasets are extracted and output to complete the numerical simulation analysis.

[0058] In an optional embodiment of this application, the time step of the current iteration cycle is used as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration, including: Inject the time step of the current iteration cycle into the time integration module of the transient partial differential equation numerical solution system; Based on this time integration step, the stiffness matrix and mass matrix of the global grid nodes are discretized and assembled in time, and the pollutant concentration field data and three-dimensional seepage velocity field vector at the current moment are updated. The updated pollutant concentration field data and the three-dimensional seepage velocity field vector are used as inputs for the next iteration cycle. The steps of calculating the seepage warning level, calculating the penetration coefficient and updating the time step are executed cyclically until the cumulative simulation time reaches the preset engineering service cycle, and the simulation analysis results are output.

[0059] Example 2 refer to Figure 2 This embodiment provides a numerical simulation analysis system 1000 for the migration of pollutants in a rock and soil barrier wall to solve the same technical problem as the method embodiment. The system 1000 may include the following modules: parameter initialization module 1001, early warning level calculation module 1002, penetration coefficient calculation module 1003, step size adaptive update module 1004, and simulation solution module 1005.

[0060] The parameter initialization module 1001 is used to obtain the initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment. The initial physical parameters include the spatial grid node coordinate set, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector. Based on the spatial grid node coordinate set, spatial discretization grid division is performed to obtain global grid nodes, and the initial time step is determined by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector.

[0061] The warning level calculation module 1002 is used to extract the pollutant concentration values ​​of any grid node at the current time and the previous time during the iterative process of solving transient partial differential equations, calculate the absolute value of its concentration fluctuation, and calculate the permeability warning level of the node by combining the ratio of the permeability coefficient of the node to the permeability coefficient of the rock and soil barrier wall material.

[0062] The penetration coefficient calculation module 1003 is used to take the degree of penetration warning as input, and calculate the penetration coefficient of the node by combining the dot product projection of the current seepage velocity vector of the node and the unit normal vector of the nearest barrier wall surface.

[0063] The step size adaptive update module 1004 is used to extract the global maximum value of the penetration coefficient of all grid nodes within a preset update cycle, input the global maximum value into a preset hyperbolic tangent function to generate a nonlinear smoothing coefficient, and update the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle.

[0064] The simulation solution module 1005 is used as the time step of the current iteration cycle as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration until the cumulative simulation time reaches the preset engineering service cycle, and outputs the simulation analysis results.

[0065] It is understood that this embodiment is the system authority corresponding to the method authority, and therefore this embodiment has all the technical effects of the method embodiment, which will not be repeated here.

[0066] Example 3 This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the numerical simulation analysis method for the migration of pollutants in a soil-rock barrier wall as provided in the previous embodiment.

[0067] The fourth embodiment of this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the numerical simulation analysis method for the migration of pollutants in a soil-rock barrier wall as provided in the preceding embodiments.

[0068] The fifth embodiment of this application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the numerical simulation analysis method for the migration of pollutants in a soil and rock barrier wall as provided in the previous embodiments.

[0069] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A numerical simulation analysis method for pollutant migration in a rock and soil barrier wall, characterized in that, include: The initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment are obtained. The initial physical parameters include the spatial grid node coordinate set, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector. Based on the set of spatial grid node coordinates, spatial discretization grid division is performed to obtain global grid nodes, and the initial time step is determined by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector. In the iterative process of solving transient partial differential equations, for any grid node at the current moment, the pollutant concentration values ​​of the node at the current moment and the previous moment are extracted, the absolute value of its concentration fluctuation is calculated, and the permeability coefficient of the node is combined with the ratio of the permeability coefficient of the rock and soil barrier wall material to calculate the permeability warning level of the node. Using the degree of infiltration warning as input, and combining the dot product projection of the current infiltration velocity vector of the node with the unit normal vector of the nearest barrier wall surface, the penetration coefficient of the node is calculated. Extract the global maximum value of the penetration coefficient of all grid nodes within a preset update cycle, input the global maximum value into a preset hyperbolic tangent function to generate a nonlinear smoothing coefficient, and update the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle; The time step of the current iteration cycle is used as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration until the cumulative simulation time reaches the preset engineering service cycle, and the simulation analysis results are output.

2. The method as described in claim 1, characterized in that, The process of obtaining the initial physical parameters of the soil-rock barrier wall and the surrounding groundwater environment, and determining the initial time step by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector, includes: The three-dimensional geometric boundary data of the site is obtained, and the continuous spatial domain composed of the barrier wall and natural soil is divided using the finite element preprocessing algorithm to obtain the set of coordinates of the spatial grid nodes. The theoretical permeability coefficients are assigned to the corresponding grid nodes using in-situ permeability experimental data and spatial interpolation algorithms to construct the initial permeability coefficient matrix. The initial pollutant concentration field data is constructed by using actual concentration data collected from groundwater monitoring wells and the definite solution condition assignment method. Combining head boundary data and Darcy's law, the initial three-dimensional seepage velocity field vector of the global grid nodes at the initial moment is calculated based on the initial permeability coefficient matrix; Based on the local feature edge length of each node in the spatial grid node coordinate set and the seepage velocity modulus of the corresponding node in the initial three-dimensional seepage velocity field vector, the ratio of the local feature edge length to the seepage velocity modulus of each node is calculated, and the minimum value of the ratio is taken as the initial time step.

3. The method as described in claim 1, characterized in that, The calculation of the penetration warning level of the node includes: The product of the absolute value of the concentration fluctuation and the ratio of the permeability coefficient is used as the original early warning indicator; The original early warning indicators are standardized to eliminate differences in different dimensions and magnitudes, thereby obtaining the degree of penetration early warning. The permeability warning level is used to characterize the potential impact weight of the pollutant accumulation intensity caused by the sudden change in the permeability coefficient of the current grid node on the permeability stability of the barrier wall. The permeability warning level will be used as an input parameter for subsequent penetration coefficient calculation.

4. The method as described in claim 1, characterized in that, The calculation of the penetration coefficient of the node includes: Calculate the projection component of the seepage velocity vector onto the unit normal vector, which points from the outside to the inside of the barrier wall; The ratio of the projection component to the seepage velocity modulus is directionally filtered using a maximum value function to eliminate water flow interference that is parallel to or away from the barrier wall, thus obtaining the directional weight. The penetration warning level is multiplied by the directional weight to obtain the penetration coefficient; The penetration coefficient is used to quantify the intensity of the positive compressive force exerted by the pollutant-carrying water flow on the barrier wall. The calculation result of the penetration coefficient will be used to extract the global maximum value to drive the time step update.

5. The method as described in claim 1, characterized in that, The step of updating the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle includes: The deviation term is obtained by subtracting the global maximum value from the preset penetration coefficient safety threshold. The deviation term is input into the hyperbolic tangent function, and the S-shaped saturation characteristic of the hyperbolic tangent function is used to transform the linear deviation into a nonlinear smoothing coefficient with upper and lower limits. The updated time step is obtained by multiplying the initial time step by the nonlinear smoothing coefficient.

6. The method as described in claim 1, characterized in that, The step of using the time step of the current iteration cycle as the time integration step to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration includes: The time step of the current iteration cycle is injected into the time integration module of the transient partial differential equation numerical solution system; Based on the time integration step, the stiffness matrix and mass matrix of the global grid nodes are discretized and assembled in time, and the pollutant concentration field data and three-dimensional seepage velocity field vector at the current moment are updated. The updated pollutant concentration field data and the three-dimensional seepage velocity field vector are used as inputs for the next iteration cycle. The steps of calculating the seepage warning level, calculating the penetration coefficient, and updating the time step are executed cyclically until the cumulative simulation time reaches the preset engineering service cycle, and the simulation analysis results are output.

7. A numerical simulation analysis system for pollutant migration in a soil-rock barrier wall, characterized in that, include: The parameter initialization module is used to obtain the initial physical parameters of the rock and soil barrier wall and the surrounding groundwater environment. The initial physical parameters include the spatial grid node coordinate set, the initial permeability coefficient matrix, the initial pollutant concentration field data, and the initial three-dimensional seepage velocity field vector. Based on the spatial grid node coordinate set, spatial discretization grid division is performed to obtain global grid nodes, and the initial time step is determined by combining the initial permeability coefficient matrix and the initial three-dimensional seepage velocity field vector. The warning level calculation module is used to extract the pollutant concentration values ​​of any grid node at the current time and the previous time during the iterative process of solving transient partial differential equations, calculate the absolute value of its concentration fluctuation, and combine the permeability coefficient of the node with the ratio of the permeability coefficient of the rock and soil barrier wall material to calculate the permeability warning level of the node. The penetration coefficient calculation module is used to take the penetration warning level as input, combine the dot product projection of the current seepage velocity vector of the node and the unit normal vector of the nearest barrier wall surface, and calculate the penetration coefficient of the node. The step size adaptive update module is used to extract the global maximum value of the penetration coefficient of all grid nodes within a preset update cycle, input the global maximum value into a preset hyperbolic tangent function to generate a nonlinear smoothing coefficient, and update the initial time step based on the nonlinear smoothing coefficient to obtain the time step of the current iteration cycle. The simulation solution module is used to drive the finite element solver to perform matrix assembly and iterative solution of the coupled control equations of groundwater flow and pollutant migration by using the time step of the current iteration cycle as the time integration step, until the cumulative simulation time reaches the preset engineering service cycle, and output the simulation analysis results.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, the method as described in any one of claims 1 to 6 is implemented.

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