EDEM-based element particle modeling method and system

Abstract

The invention relates to an EDEM-based element particle modeling method and system, and the method comprises the steps: carrying out the modeling and geometric analysis of a to-be-modeled material, and obtaining the geometric data of particles; storing the particle geometric data in a data analysis library; exporting the particle geometric data from the data analysis library to a coupling model to obtain a meta-particle model; and performing simulation analysis on to-be-analyzed particles through the element particle model to obtain an analysis result. According to the method, a computer numerical simulation calculation technology is utilized, and the element particle modeling efficiency, accuracy and robustness of the stalks or the spherical solid manure are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural crop numerical simulation, and in particular to an EDEM-based elementary particle modeling method and system. Background Art

[0002] At present, in the field of scientific research, it is often necessary to study the harvesting performance or crushing performance of machinery in the study of crop stem (pole) harvesting or solid manure crushing and spreading. The vibration of the machinery during the harvesting process and the wear and tear with the soil or the crushing of manure will also cause damage and aging of the corresponding machinery, thereby reducing the service life of the machinery and poor harvesting or crushing performance. In view of the above problems, for agricultural crops, it is necessary to study the mechanical mechanism of the corresponding materials. In the study of mechanical mechanism, the rapid development of computer numerical simulation technology has provided an important opportunity. The use of computer simulation can not only obtain data and physical changes intuitively, but also save a lot of manpower, material costs and time.

[0003] Therefore, there is an urgent need in this field to design a method for rapid particle modeling of agricultural materials to study the mechanical mechanisms. Summary of the invention

[0004] The present invention provides an EDEM-based meta-particle modeling method and system to solve the defects of the prior art.

[0005] The present invention provides a particle modeling method based on EDEM, comprising: S1: Model the material to be modeled and perform geometric analysis to obtain particle geometry data; S2: storing the particle geometry data in a data analysis library; S3: exporting the particle geometry data from the data analysis library to the coupling model to obtain a meta-particle model; S4: Perform simulation analysis on the particles to be analyzed by using the meta-particle model to obtain analysis results.

[0006] According to an EDEM-based elementary particle modeling method provided by the present invention, the materials to be modeled in step S1 include stalk particles and solid manure ball particles.

[0007] According to an EDEM-based elementary particle modeling method provided by the present invention, in step S1, when the material to be modeled is a stalk-type particle, the stalk-type particle is annularly modeled, and the corresponding particle geometric data includes particle coordinates, the number of annular particles, the number of annular rings, and the diameter of the annular ring; When the material to be modeled is solid manure spherical particles, spherical modeling is performed on the solid manure spherical particles, and the corresponding particle geometric data includes particle coordinates, spherical radius, spherical particle density, and spherical particle number.

[0008] According to the EDEM-based meta-particle modeling method provided by the present invention, the data analysis library in step S2 is a pandas library.

[0009] According to an EDEM-based particle modeling method provided by the present invention, step S3 further comprises: S31: exporting particle geometry data from the storage list in the pandas library through the to_excel method; S32: Copy the exported particle geometry data to the meta-particle of the coupling model to obtain the meta-particle model.

[0010] According to the EDEM-based particle modeling method provided by the present invention, the coupling model in step S3 is an EDEM model.

[0011] According to an EDEM-based particle modeling method provided by the present invention, step S4 further comprises: S41: bonding and configuring mechanical parameters for the elementary particle model; S42: Based on the elementary particle model and the mechanical parameters, physical contact analysis is performed on the particles to be analyzed to obtain analysis results.

[0012] According to an EDEM-based particle modeling method provided by the present invention, the mechanical parameters in step S41 include: Normal stiffness per unit area, Normal range, Tangential stiffness per unit area, Tangential range, Critical normal stress, Critical tangential stress, Bonded disk scaling.

[0013] According to an EDEM-based particle modeling method provided by the present invention, the physical contact analysis of the particles to be analyzed in step S42 specifically includes: The particle force and particle torque are updated and analyzed according to the time step. The expression of the update analysis is:

[0014]

[0015]

[0016] in, is the particle normal force, is the particle tangential force, is the particle normal torque, is the particle tangential torque, is the particle normal velocity, is the particle tangential velocity, is the particle normal angular velocity, is the particle tangential angular velocity, is the particle normal stiffness, is the particle shear stiffness, is the radius of the cylindrical bond between particles, is the time step; When the normal shear stress and the tangential shear stress exceed the preset threshold, it is determined that the bonding is broken. The expressions of the normal shear stress and the tangential shear stress are:

[0017]

[0018] in, is the maximum normal shear stress, is the maximum value of tangential shear stress.

[0019] The present invention also provides an EDEM-based particle modeling system, comprising: Geometric analysis module: used to model the material to be modeled and perform geometric analysis to obtain particle geometry data; Storage module: used for storing the particle geometry data into a data analysis library; Modeling module: used for exporting the particle geometry data from the data analysis library to the coupling model to obtain a meta-particle model; Mechanical analysis module: used to simulate and analyze the particles to be analyzed through the elementary particle model to obtain analysis results.

[0020] The present invention provides a meta-particle modeling method set system based on EDEM. By performing specific geometric modeling on different types of particles (such as stalk particles and solid manure ball particles), the actual shape and characteristics of the particles can be more accurately reflected, thereby improving the accuracy of simulation analysis. At the same time, a data analysis library (such as pandas library) is used to store and export particle geometry data, which simplifies the data processing process and improves modeling efficiency. Secondly, the present invention can easily realize the construction of a meta-particle model by importing particle geometry data into a coupling model (such as an EDEM model), thereby providing a basis for subsequent physical contact analysis. The EDEM-based modeling method makes simulation analysis more flexible and can adapt to different fields. In the simulation and analysis stage, the present invention configures mechanical parameters by bonding and performs physical contact analysis based on the meta-particle model, so as to more accurately simulate the interaction and dynamic behavior between particles. In particular, by updating the analysis expression and determining the conditions under which the bonding is broken, the present invention can more finely capture the mechanical changes and interaction processes between particles, thereby improving the accuracy and reliability of the simulation analysis. The meta-particle modeling method of the present invention is not only applicable to stalk particles and solid manure ball particles, but can also be extended to other types of particle modeling and analysis according to actual needs. The versatility and scalability of the present invention make the present invention have broad application prospects in agriculture, environmental protection, engineering and other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A schematic diagram of a process flow of a particle modeling method based on EDEM provided in an embodiment of the present invention; Figure 2 A schematic diagram of the structure of a meta-particle modeling system based on EDEM provided in an embodiment of the present invention; Figure 3 A schematic diagram of a meta-particle model for modeling stalk particles provided in an embodiment of the present invention; Figure 4 A schematic diagram of a meta-particle model for modeling solid manure spherical particles provided in an embodiment of the present invention.

[0023] Reference numerals: 100. Geometric analysis module; 200. Storage module; 300. Modeling module; 400. Mechanical analysis module. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments, and they should not be understood as limitations on the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0025] The embodiments of the present invention are described below with reference to the accompanying drawings.

[0026] like Figure 1 As shown, the present invention provides a particle modeling method based on EDEM, comprising: S1: Model the material to be modeled and perform geometric analysis to obtain particle geometry data.

[0027] The materials to be modeled in step S1 include stalk particles and solid manure pellets.

[0028] In step S1, when the material to be modeled is stalk-like particles, the stalk-like particles are modeled in a ring shape, and the corresponding particle geometric data include particle coordinates, the number of ring particles, the number of rings, and the diameter of the ring.

[0029] Furthermore, when the material to be modeled is a stalk-like particle, an annular modeling is required. Since the stalk-like particle is long and may have a node structure, it is simplified into a model composed of multiple rings, such as Figure 3 The figure shows a 3-ring 30-layer particle model of a stem. Figure 3 The left picture is the front view of the elementary particle model. Figure 3 The picture on the right is a top view of the elementary particle model.

[0030] Based on ring modeling, the particle geometric data collected are: particle coordinates: the position of each ring (or the entire particle) in the simulation space; number of ring particles: the number of rings in the model, reflecting the thickness or complexity of the stem; number of rings: the number of rings that each stem particle is composed of, reflecting the length or segmentation of the stem; ring diameter: the diameter of each ring, reflecting the thickness of the stem.

[0031] The specific geometric analysis method after modeling the stem (rod)-like particles is as follows.

[0032] Mathematical theoretical formula of angle increment: Angle increment This can be deduced by considering the distribution density of particles on the ring. If we regard the particles on the ring as continuously distributed, then the distribution density of the particles is It can be expressed as:

[0033] in, is the particle distribution density, is the angle increment, i.e. the angular interval between adjacent particles.

[0034] The total angle of the ring By integrating, we can get the total number of particles, expressed as:

[0035] in, is the total number of particles counted, which is a constant, so it can be calculated , the specific expression is:

[0036] Using the above formula, we can calculate the angle that each particle should occupy on the ring, based on the number of particles.

[0037] Calculate the X and Y coordinates of the particle: The position of the particle on the ring can be described by the parameterization of the ring. If we consider a circle with a radius of The parameterization of the ring can be expressed as:

[0038] in, are the angular coordinates on the ring, is the axial position of the ring. The position of the particle can be determined by the above parameterization, which can be converted into a coordinate calculation formula, expressed as:

[0039]

[0040] Here, trigonometric functions are used to calculate the position of each particle on the ring. is the radius of the ring.

[0041] Calculating the circumference of a ring: specific From 0 to , then the circumference of the ring is:

[0042] in, The circumference of the ring being calculated.

[0043] When the material to be modeled is solid manure spherical particles, spherical modeling is performed on the solid manure spherical particles, and the corresponding particle geometric data includes particle coordinates, spherical radius, spherical particle density, and spherical particle number.

[0044] Furthermore, when the material to be modeled is solid manure spherical particles, spherical modeling is performed. Since the solid manure spherical particles are close to spherical in shape, they are simplified into a spherical model, such as Figure 4 As shown, it is a particle model of spherical manure with a center coordinate of 1, a radius of 10, and a density of 20. Figure 4 The left picture is the front view of the meta-particle model. Figure 3 The picture on the right is a top view of the elementary particle model.

[0045] Based on the spherical model, the particle geometric data collected are: particle coordinates: the position of each spherical particle in the simulation space; spherical radius: the radius of the spherical particle, reflecting the size of the particle; spherical particle density: the number of spherical particles per unit volume, reflecting the packing density of the particles; spherical particle number: the total number of spherical particles used in the simulation, which affects the accuracy and calculation amount of the simulation.

[0046] The specific solid manure spherical element particle modeling and geometric analysis method are as follows.

[0047] The standard equation of a sphere: Let the center of the sphere be , the radius is , then the standard equation of the sphere is:

[0048] in, For any point in space, is the Euclidean norm.

[0049] The parametric equation of the sphere is: The parametric equation of the sphere can be expressed by the spherical coordinate system, and the conversion relationship between the spherical coordinate system and the Cartesian coordinate system can be expressed as:

[0050] in, is the polar angle, is the azimuth, is a point on the unit sphere and the value of the corresponding coordinate point is expressed as:

[0051] in, , .

[0052] S2: storing the particle geometry data into a data analysis library.

[0053] Wherein, the data analysis library in step S2 is the pandas library.

[0054] After step S1, the particle data obtained in step S1, whether it is stalk-type particles or solid manure ball-type particles, are stored in the pandas library and then added to a list. The stored data includes all the above-mentioned particle geometry data.

[0055] S3: Exporting the particle geometry data from the data analysis library to the coupling model to obtain a meta-particle model.

[0056] Wherein, step S3 further comprises: S31: Export the particle geometry data from the storage list of the pandas library through the to_excel method.

[0057] In pandas, the aforementioned particle geometry data is stored in DataFrame or Series objects, which can be regarded as abstractions of tabular data. Therefore, in step S31, the to_excel method is used to export the data of the DataFrame or Series object to an Excel file. Through this method, the particle geometry data can be saved in Excel format, which is convenient for subsequent data exchange and import.

[0058] S32: Copy the exported particle geometry data to the meta-particle of the coupling model to obtain a meta-particle model.

[0059] In step S32, after completing the data replication, the coupling model constructs one or more meta-particles according to the imported particle geometry data. These meta-particles together constitute a meta-particle model. The obtained model can be used for subsequent simulation analysis to study the behavior of the particle system.

[0060] Specifically, in steps S31 to S32, the particle data is first exported to an Excel file using the to_exce1 method of the pandas library, and then the exported X, Y, and Z data are copied to the X, Y, and Z coordinate values ​​under Meta-Particle of EDEM, thereby generating the constructed stalk (rod) meta-particle model or spherical solid manure meta-particle model.

[0061] Wherein, the coupling model in step S3 is an EDEM model.

[0062] S4: Perform simulation analysis on the particles to be analyzed by using the meta-particle model to obtain analysis results.

[0063] Wherein, step S4 further comprises: S41: configuring mechanical parameters for bonding the meta-particle model.

[0064] Wherein, the mechanical parameters in step S41 include: Normal stiffness per unit area, normal range, tangential stiffness per unit area, tangential range, critical normal stress, critical tangential stress, bonding disk scale. The specific parameters, corresponding units, and physical meanings are shown in Table 1.

[0065] Table 1 List of mechanical parameters of bonding configuration

[0066] S42: Based on the elementary particle model and the mechanical parameters, physical contact analysis is performed on the particles to be analyzed to obtain analysis results.

[0067] The physical contact analysis of the particles to be analyzed in step S42 specifically includes: The particle force and particle torque are updated and analyzed according to the time step. The expression of the update analysis is:

[0068]

[0069]

[0070] in, is the particle normal force, is the particle tangential force, is the particle normal torque, is the particle tangential torque, is the particle normal velocity, is the particle tangential velocity, is the particle normal angular velocity, is the particle tangential angular velocity, is the particle normal stiffness, is the particle shear stiffness, is the radius of the cylindrical bond between particles, is the time step.

[0071] After bonding, the force and torque on the particle are set to zero and are adjusted gradually in each time step. The adjustment expression is shown in the above formula. is the radius of the "glue", that is, the radius of the cylindrical bond between particles, and is set to the radius of the smallest particle in the contact pair multiplied by the Bonded Disk Scale value you set.

[0072] For normal and shear stiffness, if the Normal or TangentialRange value is set to 0 N / m³, a stiffness value is assigned according to the bond configuration value, otherwise the bond is assigned a value randomly distributed between the Stiffness value + or –range value. This provides a linear distribution of bond stiffness values ​​for a given material.

[0073] When the normal shear stress and the tangential shear stress exceed the preset threshold, it is determined that the bonding is broken. The expressions of the normal shear stress and the tangential shear stress are:

[0074]

[0075] in, is the maximum normal shear stress, is the maximum value of tangential shear stress.

[0076] The bond forces / torques described above are in addition to the BaseContactModel. Since the bonds involved in the model can act when the particles are no longer in physical contact, the contact radius should be set higher than the actual radius of the sphere. The obtained model can only be used between particles.

[0077] like Figure 2 As shown, the present invention also provides an EDEM-based particle modeling system, comprising: Geometric analysis module 100: used to model the material to be modeled and perform geometric analysis to obtain particle geometric data; Storage module 200: used to store the particle geometry data into a data analysis library; Modeling module 300: used to export the particle geometry data from the data analysis library to the coupling model to obtain a meta-particle model; Mechanical analysis module 400: used to perform simulation analysis on the particles to be analyzed through the elementary particle model to obtain analysis results.

[0078] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0079] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0080] Specifically in the embodiment, according to the stem (rod) to be studied, the number of radial layers and axial layers of the ring and the diameter are determined to determine the bonding degree, and the three-dimensional coordinate point data of the particles are generated. The data is exported to the library, and the material name and particle radius value in the meta-particle can be modified arbitrarily. The modified value copy the name, X, Y, Z axis and radius value to EDEM for pre-processing material modeling and then to meta-particle method modeling to complete the modeling.

[0081] In the application software corresponding to the embodiment, the number of rings (AddRing), spacing along the Z axis (Layer Spacing Z), the number of layers along the Z axis (Layer Count along Z), the starting coordinate point of the Z axis (Start Z), the number of ring particles (Ring Particle Count), the ring diameter (Ring Diameter) and other related parameters can be added through the Python program function.

[0082] According to the solid manure to be studied, determine the coordinates of the sphere center. Generate the three-dimensional coordinate point data of the particles, export the data to the library, the material name and particle radius value in the meta-particle can be modified arbitrarily, and the modified value copy the name, X, Y, Z axis and radius value to the EDEM pre-processing material modeling and then to the meta-particle method modeling to complete the modeling.

[0083] In the application software corresponding to the embodiment, through the Python program function, relevant parameters such as center point X (Center X), center point Y (Center Y), center point Z (Center Z), spherical radius (Radius), density / number of points (Density / number of points) can be added.

[0084] The present invention provides a meta-particle modeling method and system based on EDEM, and provides a method for rapid meta-particle modeling based on EDEM. The present invention is aimed at studying the physical and mechanical mechanisms of agricultural crops and crop manure, and the technology developed for the bending, shearing, compression, tension or crushing of stalks (rods) or spherical solid manure. It makes full use of computer numerical simulation technology, improves the efficiency, accuracy and robustness of meta-particle modeling of stalks (rods) or spherical solid manure, and frees the modeling of both from cumbersome and profound API interface programming technology, providing important solutions for scientific researchers and scholars. The results of the embodiment show that the efficiency of meta-particle modeling is greatly improved by adopting the method provided by the present invention. Basically, the entire modeling process can be completed within 10 seconds each time, and the accuracy of the meta-particle model is maintained at about 99%, with extremely high efficiency and accuracy.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A particle modeling method based on EDEM, characterized in that: include: S1: Model the material to be modeled and perform geometric analysis to obtain particle geometry data; S2: storing the particle geometry data in a data analysis library; S3: exporting the particle geometry data from the data analysis library to the coupling model to obtain a meta-particle model; S4: Perform simulation analysis on the particles to be analyzed by using the meta-particle model to obtain analysis results.

2. The EDEM-based particle modeling method according to claim 1, characterized in that: The materials to be modeled in step S1 include stalk particles and solid manure pellets.

3. The EDEM-based particle modeling method according to claim 2, characterized in that: In step S1, when the material to be modeled is a stalk particle, a ring modeling is performed on the stalk particle, and the corresponding particle geometric data includes particle coordinates, the number of ring particles, the number of rings, and the diameter of the ring; When the material to be modeled is solid manure spherical particles, spherical modeling is performed on the solid manure spherical particles, and the corresponding particle geometric data includes particle coordinates, spherical radius, spherical particle density, and spherical particle number.

4. The EDEM-based particle modeling method according to claim 1, characterized in that: The data analysis library in step S2 is the pandas library.

5. The EDEM-based particle modeling method according to claim 4, characterized in that: Step S3 further comprises: S31: exporting particle geometry data from the storage list in the pandas library through the to_excel method; S32: Copy the exported particle geometry data to the meta-particle of the coupling model to obtain a meta-particle model.

6. The EDEM-based particle modeling method according to claim 1, characterized in that: The coupling model in step S3 is an EDEM model.

7. The EDEM-based particle modeling method according to claim 1, characterized in that: Step S4 further comprises: S41: bonding and configuring mechanical parameters for the elementary particle model; S42: Based on the elementary particle model and the mechanical parameters, physical contact analysis is performed on the particles to be analyzed to obtain analysis results.

8. The EDEM-based particle modeling method according to claim 7, characterized in that: The mechanical parameters in step S41 include: Normal stiffness per unit area, Normal range, Tangential stiffness per unit area, Tangential range, Critical normal stress, Critical tangential stress, Bonded disk scaling.

9. The EDEM-based particle modeling method according to claim 7, characterized in that: The physical contact analysis of the particles to be analyzed in step S42 specifically includes: The particle force and particle torque are updated and analyzed according to the time step. The expression of the update analysis is: in, is the particle normal force, is the particle tangential force, is the particle normal torque, is the particle tangential torque, is the particle normal velocity, is the particle tangential velocity, is the particle normal angular velocity, is the particle tangential angular velocity, is the particle normal stiffness, is the particle shear stiffness, is the radius of the cylindrical bond between particles, is the time step; When the normal shear stress and the tangential shear stress exceed the preset threshold, it is determined that the bonding is broken. The expressions of the normal shear stress and the tangential shear stress are: in, is the maximum normal shear stress, is the maximum value of tangential shear stress.

10. A meta-particle modeling system based on EDEM, characterized in that: include: Geometric analysis module: used to model the material to be modeled and perform geometric analysis to obtain particle geometry data; Storage module: used for storing the particle geometry data into a data analysis library; Modeling module: used for exporting the particle geometry data from the data analysis library to the coupling model to obtain a meta-particle model; Mechanical analysis module: used to simulate and analyze the particles to be analyzed through the elementary particle model to obtain analysis results.

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