A method for generating and processing multi-microparameter EDEM models

Abstract

This invention provides a method for generating and processing multi-microscopic parameter models of EDEM, comprising: (1) first constructing an impact penetration simulation model; (2) reading the initial HDF5 file generated by the impact penetration simulation model, adjusting the contact parameters and generating a new simulation model; (3) generating a batch running and calculation .bat script file through the Python code of the Python software, running the new simulation model in batches, obtaining the simulation results for each time step using the EDEMpy tool library, and performing secondary processing on the obtained data and plotting comparison curves of each set of simulation results; (4) integrating the code file .py generated by the Python software into the Gui interface and packaging it into an .exe program file. This invention can realize the simultaneous automatic generation and running of a large number of models with different parameters and automatic secondary processing and comparison of data, which can effectively solve the problem that EDEM lacks automated multi-parameter optimization tools when carrying out multi-parameter optimization work.

Description

Technical Field

[0001] This invention relates to the field of discrete element simulation technology, specifically to a method for generating and processing EDEM multi-microparameter models. Background Technology

[0002] Discrete Element Method (DEM) is a numerical simulation method used to simulate and analyze particulate matter, powder flow, and interparticle interactions. It treats particles as discrete objects and accurately simulates their motion and behavior under different operating conditions by calculating the mechanical interactions between particles (such as collisions, friction, and adhesion), thereby revealing the macro- and micro-level relationships within the particulate system. This method is widely used in civil engineering, mining, chemical engineering, food processing, and pharmaceuticals, especially in the design and optimization of equipment and processes involving particulate matter, providing highly intuitive and detailed simulation results.

[0003] Currently, commonly used discrete element method (DEM) simulation software mainly includes PFC and EDEM. PFC, primarily command-flow based, excels in particle mechanics simulation, making it particularly suitable for geotechnical engineering and mining. While PFC offers high accuracy in handling particle interactions and mechanical properties, its computational performance is heavily dependent on hardware configuration, and it may encounter computational efficiency bottlenecks in large-scale particle system simulations. In contrast, EDEM boasts greater user-friendliness and a more efficient computational engine, supporting seamless integration with other engineering simulation software (such as CFD and FEM). It can more efficiently handle complex particle-fluid interactions and is suitable for multi-field coupling analysis. Furthermore, thanks to its powerful parallel computing and cloud computing support, EDEM demonstrates significant computational advantages in large-scale simulations, becoming an important tool in the field of particulate material processing. Its functionality and performance are difficult for other DEM software to replace.

[0004] While existing EDEMs offer fast and user-friendly workflows and rich data extraction capabilities, they still face challenges when optimizing multiple parameters, especially in scenarios requiring simultaneous adjustment of several parameters to match simulation results with experimental data. First, EDEMs lack automated tools for multi-parameter optimization. Their built-in optimization functions are typically only suitable for single-parameter or relatively simple optimization tasks. When multiple parameters are involved, manual adjustment and multiple trials are often required, which not only cumbersome the workflow but also easily introduces human error. Second, although EDEMs support data extraction, the interface and operation can become quite complex when performing complex multi-parameter optimizations, especially when extensive parameter adjustments, secondary data processing, and result comparisons are needed, significantly increasing the difficulty and complexity of the operation.

[0005] Currently, developing software based on the EDEM platform that integrates three automated functions—multi-parameter optimization, secondary data processing, and result comparison—remains a gap that urgently needs to be filled. Summary of the Invention

[0006] To address the unresolved issues mentioned in the background section regarding the inability of EDEM software to simultaneously and automatically generate and run large batches of models with different parameters, as well as to automatically perform secondary data processing and comparison when conducting optimization work with multiple sets of parameters, this invention proposes a method for generating and processing multi-microscopic parameter models in EDEM. This method is logically conceived and integrates a graphical user interface and post-processing functions on the existing EDEM platform. It not only satisfies functions such as automated batch adjustment of contact parameters and generation and running of simulation examples, but also simultaneously satisfies the secondary processing and correction of data such as cone tip resistance and acceleration in impact penetration simulation models. Furthermore, it outputs the processed results as graphs for easy result verification.

[0007] To address the aforementioned technical problems, this invention provides a method for generating and processing EDEM multi-microparameter models, which mainly includes the following steps:

[0008] (1) First, construct an impact penetration simulation model with the same dimensions as the indoor impact penetration test;

[0009] (2) Read the initial HDF5 file generated by the impact penetration simulation model constructed in step (1) above using the EDEMpy tool library of the Python software, adjust the contact parameters and generate a new simulation model.

[0010] (3) Generate a batch running and calculation .bat script file using the Python code of the Python software, run the new simulation model generated in step (2) in batch, use the EDEMpy tool library to obtain the simulation results of each time step, and perform secondary processing on the obtained data and draw the comparison curves of each group of simulation results.

[0011] (4) Integrate the code file .py generated by the Python software into the GUI interface and package it into an .exe program file to realize the three automated functions of multi-parameter optimization, secondary data processing and result comparison.

[0012] The method for generating and processing multi-microparameter EDEM models, wherein the specific process of step (1) in constructing the basic impact penetration simulation model is as follows:

[0013] (1.1) Based on the indoor impact penetration test, create particulate materials and set the intrinsic parameters of particulate materials;

[0014] (1.2) Import the geometric model generated by the external modeling software into the EDEM software to generate cylinders that are consistent with the externally generated geometric model, and use them to generate particles. Use the particle factory function built into the EDEM software to generate particles layer by layer.

[0015] (1.3) Stress relief removes the unbalanced forces between particles, bringing the particles into a state of equilibrium;

[0016] (1.4) Import the impact penetration geometric model into the EDEM software to generate the basic impact penetration simulation model "edem-base.dem" so as to carry out impact penetration simulation tests.

[0017] The method for generating and processing EDEM multi-micro-parameter models, wherein the specific process of step (2) is as follows: the EDEMpy tool library serves as the Python API interface for the EDEM software. Through the Python software and the Python library developed for EDEM, the HDF5 file generated by the EDEM software simulation is accessed to adjust and read the data of the particle or impact penetration probe. Then, the initial HDF5 file generated by the impact penetration simulation model in step (1) is read through the EDEM tool library of the Python software, and the parent folder where the basic impact penetration simulation model is located is copied in the same directory to generate the required number of sets of identical folders. Each folder represents a model file, and the micro-parameters of the particle and geometry of the simulation model in each model file are adjusted respectively to generate multiple sets of new simulation models in batches.

[0018] The method for generating and processing multi-microparameter EDEM models, wherein step (3) is specifically as follows:

[0019] (3.1) Generate batch calculation .bat files using Python code in Python software for batch running of the new simulation models generated in step (2);

[0020] (3.2) The attitude transformation matrix of the penetrator can be directly obtained through the EDEMpy tool library, and the cone tip drag, axial acceleration, tilt angle and effective penetration depth can be quickly obtained by coordinate transformation;

[0021] (3.3) The results of the new simulation model generated in step (3.1) above are output as a .CSV file using the Python script code of the Python software. Time history curves of cone tip resistance, axial acceleration and vertical penetration depth are plotted and compared with the results of the impact penetration test.

[0022] The method for generating and processing multi-microparameter EDEM models, wherein the process for obtaining the attitude transformation matrix in step (3.2) is as follows:

[0023] ① First, import the simulation results (.h5 files) of each model folder from the EDEMpy tool library h5py;

[0024] ②Then, the orientation matrix of the penetrator is read directly using Python code:

[0025]

[0026] Where G represents global coordinates; b represents carrier coordinates; X G Y G Z G These represent the vector magnitudes in the X, Y, and Z directions in the global coordinate system, respectively; X b Y b Z b These represent the vector magnitudes in the X, Y, and Z directions in the global coordinate system, respectively.

[0027] The method for generating and processing multi-microparameter EDEM models, wherein the solution process for the cone tip resistance in step (3.2) is as follows:

[0028] ① First obtain the action vector

[0029] Extracting the action vector from the simulation:

[0030]

[0031] Among them, A x A y A z These represent the magnitudes of the force vectors in the x, y, and z directions in the global coordinate system, respectively; A represents the force vector acting on the penetrator.

[0032] ② Obtain the local Z-axis direction

[0033] Extract the third column from the transformation matrix of the geometric object as the Z-axis direction vector:

[0034]

[0035] Among them, z x z y z z These represent the magnitudes of the acceleration vectors in the x, y, and z directions in global coordinates, respectively; z_axis represents the axial acceleration of the penetrator.

[0036] ③ Normalize the Z-axis direction vector

[0037] Calculate the vector magnitude:

[0038]

[0039] Normalization yields a unit vector:

[0040]

[0041] ④ Calculate the dot product to obtain the axial cone tip resistance.

[0042] Projecting vector A onto a unit vector:

[0043]

[0044] The method for generating and processing multi-microparameter EDEM models, wherein the solution process for the axial acceleration in step (3.2) is as follows:

[0045] ① Obtain the velocity vector

[0046] Extract the velocity vectors of the geometry at the current time step and the next time step from the simulation:

[0047]

[0048] Among them, V now V next These represent the velocity vector at the current time step and the velocity vector at the next adjacent time step, respectively. These represent the magnitudes of the global coordinates x, y, and z in the current time step, respectively. These represent the magnitudes of the global coordinates x, y, and z in the current time step, respectively.

[0049] ② Calculate the time difference

[0050] Calculate the time difference between the current time step and the next time step:

[0051] Δt = time_next - time_now;

[0052] Where Δt represents the time difference between the current time step and the next time step; time_next represents the time represented by the next adjacent time step; and time_now represents the time represented by the current time step.

[0053] ③ Calculate the acceleration vector

[0054] Dividing the change in velocity by the time difference yields the acceleration vector:

[0055]

[0056] ④ Obtain the local Z-axis direction vector

[0057] Extract the third column from the transformation matrix of the geometry, representing the local Z-axis direction vector:

[0058]

[0059] ⑤ Normalize the Z-axis vector

[0060] Calculate the magnitude of the Z-axis direction vector:

[0061]

[0062] The normalized unit vector:

[0063]

[0064] ⑥ Calculate the component of acceleration in the Z-axis direction.

[0065] Calculate the projection using the dot product formula:

[0066]

[0067] The method for generating and processing multi-microparameter EDEM models, wherein the process of solving the tilt angle in step (3.2) is as follows:

[0068] ① Extracting the local Z-axis vector of the geometry

[0069] Extract the third column from the geometry_transformMatrix of the geometry:

[0070]

[0071] ② Define the ground normal vector

[0072] The ground normal vector is fixed as follows:

[0073]

[0074] ③ Calculate the vector dot product

[0075] The dot product result is:

[0076] dot_product=z_axis·ground_normal=z z ;

[0077] ④ Calculate the modulus of the Z-axis of the geometric body

[0078] Formula for calculating vector magnitude:

[0079]

[0080] ⑤ Calculate the cosine value

[0081] Substituting the dot product and magnitude into the cosine formula:

[0082]

[0083] ⑥ Calculate the included angle (in radians)

[0084] Using the inverse cosine function:

[0085] θ = arccos(cosθ);

[0086] ⑦ Radius to Angle

[0087] Finally converted to angle units:

[0088]

[0089] The method for generating and processing multi-microparameter EDEM models, wherein the solution process for the effective penetration depth in step (3.2) is as follows:

[0090] ① Obtain the coordinate data of the vertices of the geometric solid.

[0091] Extract the list of Z coordinates of vertices from the geometric data at the current time:

[0092] ZCoords = [Z1, Z2, ..., Z n ];

[0093] ② Find the minimum value

[0094] Use the minimum value function to operate on the list:

[0095] min_z = min(ZCoords).

[0096] The method for generating and processing multi-microparameter EDEM models, wherein step (4) is specifically as follows:

[0097] (4.1) First, design the graphical user interface (GUI) using QtDesigner, generate the corresponding .ui file, and use PyQt5 to convert it into Python code to realize the interaction between the user and the program;

[0098] (4.2) Then, PyInstaller is used to package the entire Python program into an independent EXE executable file. Users only need to run the EXE file to directly execute batch processing tasks without installing the Python environment or dependent libraries.

[0099] By adopting the above technical solution, the present invention has the following beneficial effects:

[0100] The proposed method for generating and processing multi-microparameter EDEM models is well-conceived and can achieve batch generation and secondary data processing of multi-microparameter EDEM models. It can effectively solve the problems of low efficiency in batch adjustment of model parameters and generation of EDEM models, as well as cumbersome secondary data processing, and greatly reduce the time and manpower costs required for EDEM simulation.

[0101] This invention integrates a graphical user interface and post-processing functions on the existing EDEM platform, which not only satisfies functions such as automated batch adjustment of contact parameters and generation and running of calculation examples, but also satisfies secondary processing and correction of data such as cone tip resistance and acceleration in the impact penetration simulation model, and outputs the processed results as curves for easy result verification. Attached Figure Description

[0102] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0103] Figure 1 This is a flowchart illustrating the implementation of the EDEM multi-microparameter model generation and processing method of the present invention.

[0104] Figure 2 This is a schematic diagram of the impact penetration simulation model involved in the EDEM multi-microparameter model generation and processing method of the present invention;

[0105] Figure 3 This is a schematic diagram illustrating the principle of obtaining the cone tip resistance of impact penetration in the EDEM multi-microparameter model generation and processing method of the present invention.

[0106] Figure 4 This is a visualization interface diagram of the EDEM multi-microparameter model generation and processing method of the present invention;

[0107] Figure 5 This is a result diagram of the EDEM multi-microparameter model generation and processing method of the present invention;

[0108] Figure 6 This is a comparison chart of the output results involved in the EDEM multi-microparameter model generation and processing method of the present invention;

[0109] Figure 7 This is a flowchart illustrating the operation of the EDEM software involved in the EDEM multi-microparameter model generation and processing method of the present invention. Detailed Implementation

[0110] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0111] The present invention will be further explained below with reference to specific embodiments.

[0112] like Figure 1 As shown in this embodiment, a method for generating and processing EDEM multi-microparameter models is provided. First, a basic impact penetration simulation model is constructed. Then, the initial HDF5 file generated by the simulation model is read using the EDEMpy tool library in Python software. The contact parameters are adjusted, and a new simulation model is generated. The model is then run in batches using .bat files generated by Python code. EDEMpy is used to obtain the simulation results for each time step, and the acquired data undergoes secondary processing (such as cone tip drag, axial acceleration, etc.) and comparative curves of each set of simulation results are plotted. Finally, the above script files are integrated into the GUI interface, realizing a unified automation of multi-parameter optimization, secondary data processing, and result comparison.

[0113] The method for generating and processing EDEM multi-microparameter models of the present invention specifically includes the following steps:

[0114] S100, Construction of the Basic Model

[0115] Taking impact penetration simulation as an example: First, based on indoor impact penetration tests, granular materials are created and their intrinsic parameters are set. Then, the geometric model generated by external modeling software (such as CAD, etc.) (built by software such as CAD / Solidworks) is imported into EDEM software to generate cylinders consistent with the externally generated geometric model. The granulation factory function built into EDEM software is then used to generate particles layer by layer. Second, since the rapidly generated particles may overlap, contact forces will occur, causing the particles to be non-static. Stress release is used to remove the unbalanced forces between particles, ensuring that the particle velocity, contact force, etc., are constant, placing the particles in equilibrium and not affecting subsequent penetration tests. Finally, after generating the particles, the impact penetration geometric model is imported into EDEM software to conduct impact penetration simulation tests. Figure 2 As shown, an external 3D penetrator model is imported to generate a basic impact penetration simulation model "edem-base.dem".

[0116] S200, Batch Generation and Operation of Models with Different Contact Parameters

[0117] The EDEMpy tool library, serving as the Python API interface for the EDEM software, allows access to the HDF5 files generated by EDEM simulations via Python software and Python libraries developed specifically for EDEM. This enables the adjustment and reading of data from particles or impact penetration testers, including intrinsic particle parameters and contact parameters. Furthermore, the EDEM tool library in the Python software reads the initial HDF5 file generated from the impact penetration simulation model in step S100. It then copies the parent folder containing the basic impact penetration simulation model (the folder containing the .dem files in the parent directory of the current directory) to the same directory, generating multiple sets of identical folders. Each folder represents one model file. The microscopic parameters of interest (coefficient of restitution, static friction coefficient, dynamic friction coefficient, and JKR free surface energy) for the particles and geometry in each model file are adjusted; these parameters can vary between sets. Simultaneously, a batch calculation .bat file is generated to batch generate multiple new simulation models.

[0118] S300. Secondary data processing and result comparison

[0119] The dynamic response characteristics of the impact penetration test are mainly characterized by the time history curves of tip resistance and axial acceleration. EDEM software can only export the basic force, velocity, and displacement components of the penetrometer (in the global coordinate system). When the penetrometer penetrates the soil at an initial inclination angle, it cannot obtain characteristic parameters such as axial acceleration and tip resistance. Therefore, a batch execution and calculation .bat script file is generated using Python code to batch run the new simulation model generated in step S200. The simulation results for each time step are obtained using the EDEMpy tool library. The acquired data is then processed further, and comparison curves of each set of simulation results (time history curves of tip resistance, axial acceleration, and vertical penetration depth) are plotted. The specific process is as follows:

[0120] S310. First, use the Python code in the Python software to generate a .bat script file for batch execution and calculation, and run the new simulation model generated in step S200 in batches.

[0121] S320, and then directly obtain the attitude transformation matrix of the penetrator through the EDEMpy tool library, and quickly obtain the results such as cone tip drag, axial acceleration, tilt angle and effective penetration depth by coordinate transformation;

[0122] The process for obtaining the attitude transformation matrix described above is as follows:

[0123] ① First, import the simulation results (.h5 files) of each model folder from the EDEMpy tool library h5py;

[0124] ②Then, the orientation matrix of the penetrator is read directly using Python code:

[0125]

[0126] Where G represents global coordinates; b represents carrier coordinates; X G Y G Z G These represent the vector magnitudes in the X, Y, and Z directions in the global coordinate system, respectively; X b Y b Z b These represent the vector magnitudes in the X, Y, and Z directions in the global coordinate system, respectively.

[0127] like Figure 3 As shown, the solution process for the cone tip resistance is as follows:

[0128] ① First obtain the action vector

[0129] Extracting the action vector from the simulation:

[0130]

[0131] Among them, A x A y A z These represent the magnitudes of the force vectors in the x, y, and z directions in the global coordinate system, respectively; A represents the force vector acting on the penetrator.

[0132] ② Obtain the local Z-axis direction

[0133] Extract the third column from the transformation matrix of the geometric object as the Z-axis direction vector:

[0134]

[0135] Among them, z x z y z z These represent the magnitudes of the acceleration vectors in the x, y, and z directions in global coordinates, respectively; z_axis represents the axial acceleration of the penetrator.

[0136] ③ Normalize the Z-axis direction vector

[0137] Calculate the vector magnitude:

[0138]

[0139] Normalization yields a unit vector:

[0140]

[0141] ④ Calculate the dot product to obtain the axial cone tip resistance.

[0142] Projecting vector A onto a unit vector:

[0143]

[0144] The solution process for the above axial acceleration is as follows:

[0145] ① Obtain the velocity vector

[0146] Extract the velocity vectors of the geometry at the current time step and the next time step from the simulation:

[0147]

[0148] Among them, V now V next These represent the velocity vector at the current time step and the velocity vector at the next adjacent time step, respectively. These represent the magnitudes of the global coordinates x, y, and z in the current time step, respectively. These represent the magnitudes of the global coordinates x, y, and z in the current time step, respectively.

[0149] ② Calculate the time difference

[0150] Calculate the time difference between the current time step and the next time step:

[0151] Δt = time_next - time_now;

[0152] Where Δt represents the time difference between the current time step and the next time step; time_next represents the time represented by the next adjacent time step; and time_now represents the time represented by the current time step.

[0153] ③ Calculate the acceleration vector

[0154] Dividing the change in velocity by the time difference yields the acceleration vector:

[0155]

[0156] ④ Obtain the local Z-axis direction vector

[0157] Extract the third column from the transformation matrix of the geometry, representing the local Z-axis direction vector:

[0158] ⑤ Normalize the Z-axis vector

[0159] Calculate the magnitude of the Z-axis direction vector:

[0160]

[0161] The normalized unit vector:

[0162]

[0163] ⑥ Calculate the component of acceleration in the Z-axis direction.

[0164] Calculate the projection using the dot product formula:

[0165]

[0166] The process of solving for the tilt angle described above is as follows:

[0167] ① Extracting the local Z-axis vector of the geometry

[0168] Extract the third column from the geometry_transformMatrix of the geometry:

[0169] ② Define the ground normal vector

[0170] The ground normal vector is fixed as follows:

[0171]

[0172] ③ Calculate the vector dot product

[0173] The dot product result is:

[0174] dot_product=z_axis·ground_normal=z z ④ Formula for calculating the magnitude of the Z-axis vector of a geometric object:

[0175]

[0176] ⑤ Calculate the cosine value

[0177] Substituting the dot product and magnitude into the cosine formula:

[0178]

[0179] ⑥ Calculate the included angle (in radians)

[0180] Using the inverse cosine function:

[0181] θ = arccos(cosθ);

[0182] ⑦ Radius to Angle

[0183] Finally converted to angle units:

[0184]

[0185] The process for determining the effective penetration depth described above is as follows:

[0186] ① Obtain the coordinate data of the vertices of the geometry. Extract a list of the Z coordinates of the vertices from the geometric data at the current time:

[0187] ZCoords = [Z1, Z2, ..., Z n ];

[0188] ② Find the minimum value

[0189] Use the minimum value function to operate on the list:

[0190] min_z = min(ZCoords).

[0191] S330. Using Python script code in Python software, output the results of the new simulation model generated in step S310 as a .CSV file, plot the time history curves of cone tip resistance, axial acceleration and vertical penetration depth, and compare the time history curves with the results of the impact penetration test in the laboratory.

[0192] The S400, with its visual interface developed using Qt Designer and PyQt5, offers a convenient operating method, particularly suitable for non-technical users. First, a graphical user interface (GUI) is designed using Qt Designer, generating a corresponding .ui file. Then, PyQt5 is used to convert this GUI into Python code, enabling user interaction with the program. Through a simple and intuitive interface, users can easily input parameters, trigger batch processing operations, and view task progress in real time. Subsequently, PyInstaller is used to package the entire Python program into a standalone EXE executable file. Users only need to run this EXE file to directly execute batch processing tasks without installing a Python environment or dependent libraries. Figure 4 As shown. By providing a user-friendly visual interface and a standalone EXE file, this allows non-technical users to use complex batch processing tools without barriers, greatly improving the application's usability and ease of use.

[0193] The results of this invention:

[0194] Taking the impact penetration simulation test as an example, the software automatically generates and runs the simulation model by inputting parameters through a visual interface.

[0195] The acquired data undergoes secondary processing (such as noise reduction and coordinate system transformation) and comparative curves of each group of simulation results are plotted and output. The final simulation results and curves are located in the parameter_calibration folder. Figure 5 As shown (this is only one simulation).

[0196] Manual EDEM simulations were performed using the same impact penetration simulation model, penetration velocity, and micro-parameters (coefficient of restitution, static friction coefficient, dynamic friction coefficient, etc.). The output cone tip penetration resistance, acceleration, and penetration depth were compared to determine the accuracy of the simulation process using the multi-micro-parameter model batch generation and secondary processing software based on the EDEM platform. The comparison results are as follows: Figure 6 As shown, the simulation results of the software are almost identical to those of the manual simulation, indicating the accuracy of the software simulation.

[0197] like Figure 7 As shown, the operation flow of the EDEM software in the EDEM multi-microparameter model generation and processing method of the present invention is as follows:

[0198] (1) Select and enter the installation location of the EDEM software on your computer;

[0199] (2) Select the basic simulation model to be operated;

[0200] (3) Enter the number of simulation models to be run in batches, click confirm, and the software will copy the same number of model folders.

[0201] (4) Enter the modified values ​​of the parameters of interest for each simulation model in sequence, and click modify to make changes;

[0202] (5) Modify the settings such as the total solution time (set as needed), and click run deck to run multiple simulation models;

[0203] (6) The simulation model will be displayed in real time in the lower right corner of the EDEM software. After the simulation is completed, click result to perform secondary data processing and output the results of the generated model. The output results are in the corresponding model folder.

[0204] (7) Simulation complete.

[0205] The method for generating and processing multi-micro-parameter models of EDEM in this invention can simultaneously and automatically generate and run a large number of models with different parameters, as well as automatically perform secondary data processing and comparison. It can effectively solve the problem that EDEM lacks automated multi-parameter optimization tools when performing optimization work on multiple sets of parameters.

[0206] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating and processing EDEM multi-microparameter models, characterized in that... This includes the following steps: (1) First, construct an impact penetration simulation model with the same dimensions as the indoor impact penetration test; (2) Using the EDEMpy utility library in Python software, read the initial HDF5 file generated from the impact penetration simulation model constructed in step (1) above, adjust the contact parameters, and generate a new simulation model; the specific process is as follows: The EDEMpy tool library serves as the Python API interface for the EDEM software. Through the Python software and a Python library developed specifically for EDEM, it accesses the HDF5 files generated by the EDEM software simulation to adjust and read data from the particle or impact penetration tester. Then, it uses the EDEM tool library of the Python software to read the initial HDF5 file generated by the impact penetration simulation model in step (1), and copies the parent folder containing the impact penetration simulation model to the same directory to generate the required number of identical folders. Each folder represents one model file. The micro-parameters of the particles and geometry in each model file are adjusted to generate multiple new simulation models in batches. (3) Generate a batch execution and calculation .bat script file using Python code in Python software, batch run the new simulation model generated in step (2), use the EDEMpy tool library to obtain the simulation results for each time step, perform secondary processing on the obtained data, and plot the comparison curves of each group of simulation results; the specific process is as follows: (3.1) Generate batch calculation .bat files using Python code in Python software for batch running of the new simulation models generated in step (2); (3.2) The attitude transformation matrix of the penetrator can be directly obtained through the EDEMpy tool library, and the cone tip drag, axial acceleration, tilt angle and effective penetration depth can be quickly obtained by coordinate transformation; (3.3) The results of the new simulation model generated in step (3.1) are output as a .CSV file using Python script code in Python software. Time history curves of cone tip drag, axial acceleration and vertical penetration depth are plotted, and the time history curves are compared with the results of the impact penetration test in the laboratory. (4) Integrate the code file .py generated by the Python software into the GUI interface and package it into an .exe program file to realize the three automated functions of multi-parameter optimization, secondary data processing and result comparison.

2. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that, The specific process of constructing the impact penetration simulation model in step (1) is as follows: (1.1) Based on the indoor impact penetration test, create particulate materials and set the intrinsic parameters of particulate materials; (1.2) Import the geometric model generated by the external modeling software into the EDEM software to generate cylinders that are consistent with the externally generated geometric model, and use them to generate particles. Use the particle factory function built into the EDEM software to generate particles layer by layer. (1.3) Stress relief is used to remove the unbalanced forces between particles, so that the particles are in equilibrium. (1.4) Import the impact penetration geometric model into the EDEM software and generate the impact penetration simulation model "edem-base.dem" so as to carry out impact penetration simulation test.

3. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that... The process for obtaining the attitude transformation matrix in step (3.2) is as follows: ① First, import the simulation results of each model folder from the EDEMpy tool library h5py; ②Then, the orientation matrix of the penetrator is read directly using Python code: Orientation matrix= = ; Where G represents global coordinates; b represents carrier coordinates; These represent the vector magnitudes in the X, Y, and Z directions in the global coordinate system, respectively. These represent the vector magnitudes in the X, Y, and Z directions in the global coordinate system, respectively.

4. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that... The solution process for the cone tip resistance in step (3.2) is as follows: ① First obtain the action vector Extracting the action vector from the simulation: ； in, Representing global coordinates The magnitude of the force vector in the direction; A represents the force vector acting on the penetrator; ② Obtain the local Z-axis direction Extract the third column from the transformation matrix of the geometric object as the Z-axis direction vector: ； in, Representing global coordinates The magnitude of the acceleration vector in the direction; z_axis represents the axial acceleration of the penetrator; ③ Normalize the Z-axis direction vector Calculate the vector magnitude: ； Normalization yields a unit vector: ； ④ Calculate the dot product to obtain the axial cone tip resistance. Projecting vector A onto a unit vector: 。 5. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that... The process of solving for the axial acceleration in step (3.2) is as follows: ① Obtain the velocity vector Extract the velocity vectors of the geometry at the current time step and the next time step from the simulation: ； in, These represent the velocity vector at the current time step and the velocity vector at the next adjacent time step, respectively. These represent the magnitudes of the global coordinates x, y, and z in the current time step, respectively. These represent the magnitudes of the global coordinates x, y, and z in the current time step, respectively. ② Calculate the time difference Calculate the time difference between the current time step and the next time step: ； in, The time difference between the current time step and the next time step is represented by `time_next`; the time of the next adjacent time step is represented by `time_now`; and the time of the current time step is represented by `time_now`. ③ Calculate the acceleration vector Dividing the change in velocity by the time difference yields the acceleration vector: ； ④ Obtain the local Z-axis direction vector Extract the third column from the transformation matrix of the geometry, representing the local Z-axis direction vector: ； ⑤ Normalize the Z-axis vector Calculate the magnitude of the Z-axis direction vector: ； The normalized unit vector: ； ⑥ Calculate the component of acceleration in the Z-axis direction. Calculate the projection using the dot product formula: 。 6. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that... The process of solving for the tilt angle in step (3.2) is as follows: ① Extracting the local Z-axis vector of the geometry Extract the third column from the geometry_transformMatrix of the geometry: ； ② Define the ground normal vector The ground normal vector is fixed as follows: ； ③ Calculate the vector dot product The dot product result is: ； ④ Calculate the modulus of the Z-axis of the geometric body Formula for calculating vector magnitude: ； ⑤ Calculate the cosine value Substituting the dot product and magnitude into the cosine formula: ； ⑥ Calculate the included angle Using the inverse cosine function: ； ⑦ Radius to Angle Finally converted to angle units: 。 7. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that... The process for determining the effective penetration depth in step (3.2) is as follows: ① Obtain the coordinate data of the vertices of the geometric solid. Extract the list of Z coordinates of vertices from the geometric data at the current time: ； ② Find the minimum value Use the minimum value function to operate on the list: 。 8. The method for generating and processing EDEM multi-microparameter models as described in claim 1, characterized in that, The specific process of step (4) is as follows: (4.1) First, design the graphical user interface (GUI) using Qt Designer, generate the corresponding .ui file, and use PyQt5 to convert it into Python code to realize the interaction between the user and the program; (4.2) Then, PyInstaller is used to package the entire Python program into an independent EXE executable file. Users only need to run the EXE file, that is, they do not need to install the Python environment or dependent libraries, and can directly execute batch processing tasks.

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