Modeling method for movement of water body in soil particles based on discrete elements

Abstract

The invention discloses a discrete element-based modeling method for movement of a water body in soil particles, which comprises the following steps of: scanning the contour of water in soil in a container through three-dimensional X-rays by using an electronic computed tomography scanner to obtain cross-sectional image data of a water mass and surrounding soil; reconstructing a three-dimensional structure of the whole water mass based on the cross-sectional image data, and performing optimization processing on the three-dimensional structure; constructing a water mass-soil particle complex model; setting a movement mode of breaking the water clusters into water particles, solving movement behaviors of the water cluster-soil particle complex model, analyzing stress and movement conditions of the water particles and the soil particles, and forming a final state of the water cluster-soil particle complex model after movement; and comparing the formed final state with the actual soil condition, and adjusting the parameters of the moisture mass-soil particle complex model according to the difference. According to the method, the simulation accuracy and calculation efficiency of the moisture groups and the moisture particles in the soil can be considered at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional modeling of soil complexes, and in particular to a modeling method of water movement in soil particles based on discrete elements. Background Art

[0002] With the continuous advancement of science and technology and the increasing demands in the engineering field, higher requirements are placed on the accuracy and efficiency of inter-particle motion simulation. This problem becomes increasingly prominent, especially when dealing with particles of different sizes and properties.

[0003] In real-world soil environments, the process of water entering the soil has unique physical mechanisms. Due to surface tension, water does not enter the soil in a dispersed form, but first exists in aggregated clusters. As external factors, such as soil particles, impact the surface of the water clusters, the clusters break apart, transforming into mobile water that enters the soil interior. However, existing simulation technologies have limitations when simulating the behavior of water in soil.

[0004] Currently, there are two main types of discrete element methods commonly used: the contact model method with cohesive forces and the coupling of EDEM and CFD software. The contact model method with cohesive forces simulates cohesive behavior by decomposing particles into cohesive sub-particles, which can realistically reproduce the spatial occupancy and stress distribution of particles to a certain extent. However, because the particles are generated as single particles, it is difficult to accurately describe the actual existence of water clusters in the soil and cannot effectively reflect the role of water clusters, thus affecting the accuracy of the simulation results.

[0005] The coupling principle between EDEM and CFD software, through bidirectional coupling, can effectively reflect the influence of water flow on particle motion and is suitable for simulating medium- to large-scale soil particle and water bodies. However, this method has the disadvantage that its preset fluid interaction model cannot accurately reflect the specific behavior of water particles in soil particle motion. In addition, the computational complexity is large, resulting in low computational efficiency, making it difficult to meet the requirements of engineering applications with high computational efficiency.

[0006] In summary, the main problem with existing simulation technologies is the difficulty in achieving a balanced balance between accuracy and computational efficiency for both water clusters and water particles. The contact model method with cohesive forces suffers from limitations in particle generation, which limits simulation accuracy and fails to effectively capture the effects of water clusters. While the EDEM coupled with CFD software can capture the effects of water flow, its pre-defined fluid interaction model makes it difficult to accurately capture the motion of water particles, and its computational efficiency is low.

[0007] Therefore, developing a simulation technology that can simultaneously take into account the accuracy and computational efficiency of simulating water groups and water particles in the soil is of great significance for the research and application of related fields such as soil moisture transport. Summary of the Invention

[0008] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a modeling method for the movement of water in soil particles based on discrete elements, which can simultaneously take into account the accuracy and computational efficiency of simulating water groups and water particles in soil.

[0009] To achieve the above objectives, the technical solutions provided by the present invention are:

[0010] A discrete element-based modeling method for water movement in soil particles includes:

[0011] S1. Using a computerized tomography scanner, a three-dimensional X-ray is used to scan the contour of water in the soil in the container to obtain tomographic image data of water clusters and the surrounding soil;

[0012] S2. Importing the scanned tomographic image data of the water clusters and their surrounding soil into a computer, reconstructing the three-dimensional structure of the entire water clusters and performing optimization processing on the structure;

[0013] S3, constructing a water cluster-soil particle complex model;

[0014] S4. Setting a motion mode for water clusters to break into water particles, solving the motion behavior of the water cluster-soil particle complex model, analyzing the forces and motion of the water particles and soil particles, and forming the final state of the water cluster-soil particle complex model after motion;

[0015] S5. Compare the final state of the formed water cluster-soil particle complex model after movement with the actual soil condition, and adjust the parameters of the water cluster-soil particle complex model according to the difference.

[0016] Furthermore, the process of step S1 includes:

[0017] S1-1. Based on the actual planting conditions, place soil with a high moisture content in a container and drip water onto the soil surface until it forms a clumping mass. Then, cover it with a layer of soil particles and secure the container on the scanner sample stage.

[0018] S1-2. Scan the water mass and its surrounding soil: Select the scanning mode according to the actual situation, set the scanner voltage and current, rotation step, and number of shots, and set the tomographic interval according to the required observation accuracy. Use the scanner to scan the soil and water mass to ensure that the water mass and its surrounding soil are covered, including the top, bottom, and sides. Finally, obtain all tomographic images of the water mass and its surrounding soil.

[0019] Furthermore, in step S2, the process of reconstructing the three-dimensional structure of the entire water cluster and optimizing it includes:

[0020] S2-1, reconstructing the tomographic image data of the water clusters and the surrounding soil by a back-projection method to obtain a three-dimensional structural image of the water clusters and the surrounding soil;

[0021] S2-2. Separate the sample: Use the grayscale value interval tool to segment the water clusters and soil particles based on their density ranges, and form a three-dimensional structural image of the entire water cluster.

[0022] S2-3. Extract sample data: Extract various physical parameters of water clusters as needed, including length along the X, Y, and Z directions, relative position coordinates, and relative density;

[0023] S2-4. Process sample data: Use a triangular mesh to represent the three-dimensional surface of the water clusters, and then use the non-local mean algorithm to reduce the noise of the surface to achieve a smooth state.

[0024] Furthermore, the process of step S3 includes:

[0025] S3-1. Import the three-dimensional graph of the entire water cluster reconstructed in step S2, fill the graph using the multi-particle model in the discrete element software, and modify the coordinates and radius parameters of each particle so that the particles cover the interior of the graph;

[0026] S3-2. Use the single particle model to construct water molecule particles with a small radius and set the water molecule particle contact parameters as required;

[0027] S3-3. Use the discrete element API interface to access the particle replacement program and set the program parameters, including the number of replacement particles, coordinates, and replacement time;

[0028] S3-4. Use a single particle model to construct soil particles with a large radius, set up an interaction model between water molecule particles and soil particles, and generate a water cluster-soil particle complex model.

[0029] Furthermore, in step S4, solving the motion behavior of the water cluster-soil particle complex model includes:

[0030] The generation time of each particle is adjusted so that soil particles are generated first, and after forming a particle bed, large water cluster particles are generated, and then a layer of soil particles is generated to cover the surface. Finally, the water cluster particles are replaced by water molecule particles through replacement.

[0031] Furthermore, the scanning mode includes an eccentric rotation scanning mode and a concentric rotation scanning mode.

[0032] Furthermore, the process of particle replacement includes:

[0033] The original particles are instantly pulled out of their original positions with a huge force, and new particles are instantly generated in their original positions. This process is not reflected in the subsequent chart results.

[0034] Furthermore, the interaction model between the water molecule particles and the soil particles adopts a spring-damper model, a Hertz-Mindlin model, a Cundal l-Strack model in DEM, a JKR contact model or a viscoelastic model.

[0035] Furthermore, when comparing the final state of the formed water cluster-soil particle complex model after movement with the actual soil conditions, it includes measuring whether the depth and radius of the soil depression at the water cluster location are similar to the actual situation.

[0036] Compared with the existing technology, the principles and advantages of this technical solution are as follows:

[0037] 1. Existing 3D scanners can capture the physical parameters of water clusters, but the shape of water clusters in soil differs from that in normal conditions, and scanners cannot penetrate the soil to independently capture this shape data. This technical solution, however, uses a computed tomography scanner to scan the contours of the water in the soil within a container using 3D X-rays, acquiring tomographic image data of the water clusters and the surrounding soil. This scanned tomographic image data is then imported into a computer to reconstruct the entire 3D structure of the water clusters. This technical solution significantly improves the efficiency and quality of water cluster detection and reduces the physical deviations caused by the modeling process.

[0038] 2. Conventional modeling, in which water particles are generated alongside soil particles or the bonding force between particles due to water is directly represented using a cohesive model, fails to accurately reflect the actual process of water entering the soil. This technical solution, however, uses a simulation method that replaces water clusters with water particles. This approach accesses a replacement program through the discrete element software API and assigns motion states to each particle based on actual conditions, ensuring accuracy during the simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1This is a principle flow chart of a discrete element-based modeling method for water movement in soil particles according to the present invention;

[0041] Figure 2 Schematic diagram of water clusters generated in soil particles during simulation;

[0042] Figure 3 Schematic diagram of water clusters being instantly replaced by water particles;

[0043] Figure 4 Schematic diagram of the movement of replaced water particles between soil particles;

[0044] Figure 5 Schematic diagram of the distribution of water molecules moving in soil particles. DETAILED DESCRIPTION

[0045] The present invention will be further described below in conjunction with specific embodiments:

[0046] like Figure 1 As shown, the modeling method of water movement in soil particles based on discrete elements described in this embodiment includes the following steps:

[0047] S1. Using a computerized tomography scanner, a three-dimensional X-ray is used to scan the contour of water in the soil in the container to obtain tomographic image data of water clusters and the surrounding soil;

[0048] This step specifically includes:

[0049] S1-1. Based on the actual planting conditions, place soil with a high moisture content in a container and use a burette to drop approximately 5 ml of water onto the soil surface until it forms a clumping mass. Cover the soil with a layer of soil particles approximately 2 mm thick and secure the container to the scanner sample stage.

[0050] S1-2. Scan the water mass and its surrounding soil: Select a scanning mode (including eccentric rotation scanning mode and concentric rotation scanning mode) based on actual conditions, set the scanner voltage and current, rotation step, and number of shots, and set the slice interval based on the required observation accuracy. Use the scanner to scan the soil and water mass, ensuring coverage of the water mass and its surrounding soil, including the top, bottom, and sides, to ultimately obtain complete tomographic images of the water mass and its surrounding soil.

[0051] S2. Importing the scanned tomographic image data of the water clusters and their surrounding soil into a computer, reconstructing the three-dimensional structure of the entire water clusters and performing optimization processing on the structure;

[0052] This step requires processing the original image data to remove interference and irrelevant parts in the soil to obtain the three-dimensional structure of the entire water cluster. It includes the following specific steps:

[0053] S2-1, reconstructing the tomographic image data of the water clusters and the surrounding soil by a back-projection method to obtain a three-dimensional structural image of the water clusters and the surrounding soil;

[0054] S2-2. Separate the sample: Use the grayscale value interval tool to segment the water clusters and soil particles based on their density ranges, and form a three-dimensional structural image of the entire water cluster.

[0055] S2-3. Extract sample data: Extract various physical parameters of water clusters as needed, including length along the X, Y, and Z directions, relative position coordinates, and relative density;

[0056] S2-4. Process sample data: Use a triangular mesh to represent the three-dimensional surface of the water clusters, and then use the non-local mean algorithm to reduce the noise of the surface to achieve a smooth state.

[0057] S3. Construct a water cluster-soil particle complex model. The construction process includes:

[0058] S3-1. Import the three-dimensional graph of the entire water cluster reconstructed in step S2, fill the graph using the multi-particle model in the discrete element software, and modify the coordinates and radius parameters of each particle so that the particles cover the interior of the graph;

[0059] S3-2. Use the single particle model to construct water molecule particles with a small radius and set the water molecule particle contact parameters as required;

[0060] S3-3. Use the discrete element API interface to access the particle replacement program and set the program parameters, including the number of replacement particles, coordinates, and replacement time;

[0061] The particle replacement process includes:

[0062] The original particles are instantly pulled out of their original positions with a huge force, and new particles are instantly generated in their original positions. This process is not reflected in the subsequent chart results.

[0063] S3-4. Use a single particle model to construct soil particles with a large radius, and set up an interaction model between water molecule particles and soil particles. Specifically, a spring-damper model is used to generate a water cluster-soil particle complex model.

[0064] S4. Setting a motion mode for water clusters to break into water particles, solving the motion behavior of the water cluster-soil particle complex model, analyzing the forces and motion of the water particles and soil particles, and forming the final state of the water cluster-soil particle complex model after motion;

[0065] In this step, the motion behavior of the water cluster-soil particle complex model is solved, including:

[0066] The generation time of each particle is adjusted so that soil particles are generated first, and after forming a particle bed, large water cluster particles are generated, and then a layer of soil particles is generated to cover the surface. Finally, the water cluster particles are replaced by water molecule particles through replacement.

[0067] The analyzed forces and motion conditions of the water particles and soil particles include the motion states of the water particles and soil particles, such as speed, direction, and force state.

[0068] S5. Compare the final state of the formed water cluster-soil particle complex model after movement with the actual soil condition, and adjust the parameters of the water cluster-soil particle complex model according to the difference.

[0069] When comparing the final state of the formed water cluster-soil particle complex model after movement with the actual soil conditions, it is necessary to measure whether the depth and radius of the soil depression at the water cluster location are similar to the actual situation.

[0070] Existing 3D scanners can capture the physical parameters of water clusters, but the shape of water clusters in soil differs from that in normal conditions, and scanners cannot penetrate the soil to independently capture this shape data. The present invention uses a computed tomography scanner to scan the contours of water in the soil within a container using 3D X-rays, acquiring tomographic image data of the water clusters and the surrounding soil. This scanned tomographic image data is then imported into a computer to reconstruct the entire 3D structure of the water clusters. This invention significantly improves the efficiency and quality of water cluster detection and reduces the physical deviations caused by the modeling process.

[0071] Furthermore, conventional modeling, which treats water particles as part of soil particles or directly uses a bonding model to represent the bonding forces between particles due to water, fails to accurately reflect the actual process of water entering the soil. This simulation method, which uses water particles to replace water clusters, accesses a replacement program through the discrete element software API and assigns each particle a motion state based on actual conditions, ensuring accuracy during the simulation.

[0072] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, any changes made based on the shape and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A modeling method for water movement in soil particles based on discrete elements, characterized in that: include: S1. Using a computerized tomography scanner, a three-dimensional X-ray is used to scan the contour of water in the soil in the container to obtain tomographic image data of water clusters and the surrounding soil; S2. Importing the scanned tomographic image data of the water clusters and their surrounding soil into a computer, reconstructing the three-dimensional structure of the entire water clusters and performing optimization processing on the structure; S3, constructing a water cluster-soil particle complex model; S4. Setting a motion mode for water clusters to break into water particles, solving the motion behavior of the water cluster-soil particle complex model, analyzing the forces and motion of the water particles and soil particles, and forming the final state of the water cluster-soil particle complex model after motion; S5. Compare the final state of the formed water cluster-soil particle complex model after movement with the actual soil condition, and adjust the parameters of the water cluster-soil particle complex model according to the difference.

2. The modeling method of water movement in soil particles based on discrete elements according to claim 1 is characterized in that: The process of step S1 includes: S1-1. Based on the actual planting conditions, place soil with a high moisture content in a container and drip water onto the soil surface until it forms a clumping mass. Then, cover it with a layer of soil particles and secure the container on the scanner sample stage. S1-2. Scan the water mass and its surrounding soil: Select the scanning mode according to the actual situation, set the scanner voltage and current, rotation step, and number of shots, and set the tomographic interval according to the required observation accuracy. Use the scanner to scan the soil and water mass to ensure that the water mass and its surrounding soil are covered, including the top, bottom, and sides. Finally, obtain all tomographic images of the water mass and its surrounding soil.

3. The modeling method of water movement in soil particles based on discrete elements according to claim 1 is characterized in that: In step S2, the process of reconstructing the three-dimensional structure of the entire water cluster and optimizing it includes: S2-1. Reconstructing the tomographic image data of the water clusters and the surrounding soil by a back-projection method to obtain a three-dimensional structural image of the water clusters and the surrounding soil; S2-2. Separate the sample: Use the grayscale value interval tool to segment the water clusters and soil particles based on their density ranges, and form a three-dimensional structural image of the entire water cluster. S2-3. Extract sample data: Extract various physical parameters of water clusters as needed, including length along the X, Y, and Z directions, relative position coordinates, and relative density; S2-4. Process sample data: Use a triangular mesh to represent the three-dimensional graphic surface of water clusters, and then use the non-local mean algorithm to reduce the noise of the graphic surface to achieve a smooth state.

4. The modeling method of water movement in soil particles based on discrete elements according to claim 1 is characterized in that: The process of step S3 includes: S3-1. Import the three-dimensional graph of the entire water cluster reconstructed in step S2, fill the graph using the multi-particle model in the discrete element software, and modify the coordinates and radius parameters of each particle so that the particles cover the interior of the graph; S3-2. Use the single particle model to construct water molecule particles with a small radius and set the water molecule particle contact parameters as required; S3-3. Use the discrete element API interface to access the particle replacement program and set the program parameters, including the number of replacement particles, coordinates, and replacement time; S3-4. Use a single particle model to construct soil particles with a large radius, set up an interaction model between water molecule particles and soil particles, and generate a water cluster-soil particle complex model.

5. The modeling method of water movement in soil particles based on discrete elements according to claim 1 is characterized in that: In step S4, the motion behavior of the water cluster-soil particle complex model is solved, including: The generation time of each particle is adjusted so that soil particles are generated first, and after forming a particle bed, large water cluster particles are generated, and then a layer of soil particles is generated to cover the surface. Finally, the water cluster particles are replaced by water molecule particles through replacement.

6. The modeling method of water movement in soil particles based on discrete elements according to claim 2 is characterized in that: The scanning mode includes an eccentric rotation scanning mode and a concentric rotation scanning mode.

7. The modeling method of water movement in soil particles based on discrete elements according to claim 4 is characterized in that: The particle replacement process includes: The original particles are instantly pulled out of their original positions with a huge force, and new particles are instantly generated in their original positions. This process is not reflected in the subsequent chart results.

8. The modeling method of water movement in soil particles based on discrete elements according to claim 4 or 7, characterized in that: The interaction model between the water molecule particles and the soil particles adopts a spring-damper model, a Hertz-Mindlin model, a Cundal l-Strack model in DEM, a JKR contact model or a viscoelastic model.

9. The modeling method of water movement in soil particles based on discrete elements according to claim 1 is characterized in that: When comparing the final state of the formed water cluster-soil particle complex model after movement with the actual soil conditions, it is necessary to measure whether the depth and radius of the soil depression at the water cluster location are similar to the actual situation.

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