Agricultural machine-paddy field coupling simulation method based on discrete element secondary development

Abstract

The invention relates to the technical field of coupling simulation, and discloses an agricultural machinery-paddy field coupling simulation method based on discrete element secondary development. The method comprises the following steps: constructing a soil bin model and an agricultural machinery model; establishing a soil bin shrinking two-phase flow model, and importing the model into discrete element software to obtain soil particle and moisture content distribution; the particle bonding model is modified through secondary development of the dynamic link library, moisture content distribution is added, and a modified dynamic link library file is obtained and imported into discrete element software; the agricultural machine model and the soil bin model are both imported into multi-body dynamics software, motion parameters and contact attributes of the agricultural machine model are set, and liquid resistance, the motion state of the agricultural machine and stress data of soil particles are applied to the agricultural machine model; and the multi-body dynamics software is coupled with the discrete element software. According to the method, the soil non-uniform moisture content distribution characteristic, the free water surface fluid resistance effect and the agricultural machinery-soil dynamic interaction mechanism are reserved, and the modeling efficiency and precision of agricultural machinery operation process simulation in the paddy field environment are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of coupled simulation, and particularly to a method for simulating the coupling of agricultural machinery and paddy fields based on secondary development of discrete element method. Background Art

[0002] In the process of agricultural modernization, the efficient application of agricultural machinery is crucial for improving agricultural production efficiency. However, when agricultural machinery is in actual operation, its interaction with the soil is extremely complex. Different soil properties, such as moisture content and depth, will significantly affect the operation performance and energy consumption of agricultural machinery. Traditional agricultural machinery design and testing often rely on actual field tests. This method is not only costly and time-consuming, but also greatly affected by natural environmental factors, making it difficult to comprehensively and accurately explore the interaction mechanism between agricultural machinery and the soil. With the rapid development of computer technology and simulation technology, it has become possible to study the interaction between agricultural machinery and the soil through virtual modeling and simulation, and the operation performance of agricultural machinery in complex paddy field environments can be optimized at a relatively low cost.

[0003] However, there is an extreme lack of methods for the interaction between agricultural machinery and paddy field models. The existing methods mainly focus on the construction of the paddy field soil model itself, without considering the role of agricultural machinery. Due to the limitations of the existing technology, the liquid mechanics simulation software can only achieve real-time coupling with soil particles, and the computational fluid dynamics simulation software can currently only reflect the pushing effect of agricultural machinery on the liquid, but cannot reflect the resistance effect of the liquid on agricultural machinery. Therefore, in order to achieve the simultaneous coupling of agricultural machinery - water - soil, Jiang Yingxing et al. directly created particles much smaller than soil particles in the discrete element software to simulate water. This method is very difficult to solve and calculate, and these small particles have too much difference from the properties of real fluids and cannot reflect the role of water as a typical fluid. In addition, there are also many defects in the existing paddy field soil modeling technology. On the one hand, it is necessary to directly couple the complete soil model with the liquid for simulation to obtain data, and this method is very slow in solving and calculating. On the other hand, the existing modeling methods regard the paddy field soil model as a uniform whole, and the setting of the bonding strength at different depths and different moisture contents of the generated paddy field soil model is the same. It does not consider the different effects of air and paddy field depth on the bonding strength in the paddy field, nor does it consider the resistance effect of the free water surface commonly existing in the paddy field on agricultural machinery. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned deficiencies existing in the prior art, and provide a method for simulating the coupling of agricultural machinery and paddy fields based on secondary development of discrete element method.

[0005] The purpose of the present invention is achieved through the following technical solutions: The method for simulating the coupling of agricultural machinery and paddy fields based on secondary development of discrete element method includes the following steps:

[0006] S1. Build a soil bin model and an agricultural machinery model using 3D modeling software;

[0007] S2. Establish a reduced-scale two-phase flow model of the soil bin using computational fluid dynamics software;

[0008] S3. Import the reduced-scale two-phase flow model of the soil bin in step S2 into the discrete element software to generate soil particles, and solve them coupledly to obtain the moisture content distribution;

[0009] S4. Based on the software development kit of the discrete element software, modify the particle bonding model through secondary development of the dynamic link library, add the influence of the moisture content distribution in step S3 to the particle bonding model, obtain the modified dynamic link library file, and import the modified dynamic link library file into the discrete element software;

[0010] S5. Import both the agricultural machinery model and the soil bin model in step S1 into the multibody dynamics software, set the weight of the agricultural machinery model, the motion parameters of the agricultural machinery model, and the contact properties between the tires and the soil particles, and apply the liquid resistance, the motion state of the agricultural machinery, and the force data of the soil particles in step S3 to the agricultural machinery model;

[0011] S6. Couple the discrete element software in step S4 with the multibody dynamics software in step S5 to complete the interactive simulation.

[0012] A better choice is that the tire model of the agricultural machinery model in step S1 has tread details.

[0013] A better choice is that the modeling process of the soil bin model in step S1 is as follows: Define the dimensions of the agricultural machinery placement area and the boundary range of the soil generation area in the 3D modeling software. The height of the ground where the agricultural machinery placement area is located matches the depth of the soil generation area, and the agricultural machinery placement area is connected to the soil generation area.

[0014] A better choice is that step S2 includes the following steps:

[0015] S201. Reduce the length and width of the soil bin model according to a preset ratio, and keep the depth of the soil bin model unchanged to obtain a length-width reduced model;

[0016] S202. Define the length-width reduced model as a multiphase flow model, define the infiltration velocity of the water flow, the densities of water and air, the viscosity parameters of water and air, the initial positions occupied by the water phase and the air phase, set the multiphase flow solver to simulate the liquid infiltration process, and obtain and export the reduced-scale two-phase flow model of the soil bin.

[0017] A better choice is that the inherent property parameters of the soil particles in step S3 include density, elastic modulus, and Poisson's ratio, and set the restitution coefficient, dynamic friction coefficient, and static friction coefficient between soil particles.

[0018] A better choice is that step S4 includes the following steps:

[0019] S41. Perform secondary development on the header file to obtain a secondary development file;

[0020] S42. Perform secondary development on the source file to obtain a secondary development source file;

[0021] S43. Generate a modified dynamic link library file from the secondary development header file in step S41 and the secondary development source file in step S42, and import the modified dynamic link library file into the discrete element software.

[0022] A more optimal choice is that step S41 includes the following steps:

[0023] S411. Locate the end of the class definition, and add a container for storing the depth-water content correspondence relationship in the private area of the class definition;

[0024] S412. Define a method for obtaining the water content according to the depth of the container, and at the same time define a linear interpolation method for obtaining the depth and its variable definition to obtain a secondary development header file.

[0025] A more optimal choice is that step S42 includes the following steps:

[0026] S421. Based on the original SDK code provided by the discrete element software, first insert the water content distribution in step S3;

[0027] S422. Then define a linear interpolation method for feedback the water content according to the depth;

[0028] S423. Finally, insert the formula for the water content and depth affecting the particle bonding model to obtain a secondary development source file.

[0029] A more optimal choice is that the calculation formula for the liquid resistance F in step S5 is

[0030]

[0031] where ρ is the density of free water, C d is the resistance coefficient of free water, A is the cross-sectional area of the tire model, and v is the relative velocity of free water and the tire model.

[0032] The present invention has the following advantages and beneficial effects compared with the prior art:

[0033] The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development of the present invention retains the characteristics of non-uniform water content distribution in the soil, the fluid resistance effect of the free water surface, and the dynamic interaction mechanism between agricultural machinery and soil, and significantly improves the modeling efficiency and accuracy of the simulation of the agricultural machinery operation process in the paddy field environment. Description of the Drawings

[0034] Figure 1 It is a schematic flow chart of the agricultural machinery-paddy field coupling simulation method based on the secondary development of the discrete element method in the present invention;

[0035] Figure 2 It is a schematic process diagram of the secondary development of the original SDK of the discrete element software for the agricultural machinery-paddy field coupling simulation method based on the secondary development of the discrete element method in the present invention;

[0036] Figure 3 It is a schematic diagram of the combination of the agricultural machinery model and the soil bin model for the agricultural machinery-paddy field coupling simulation method based on the secondary development of the discrete element method in the present invention;

[0037] Figure 4 It is a schematic diagram of the water phase and the air phase for the agricultural machinery-paddy field coupling simulation method based on the secondary development of the discrete element method in the present invention;

[0038] Markings of each component in the attached drawings: 1 - vehicle body model; 2 - front wheel model; 3 - rear wheel model; 4 - agricultural machinery placement area; 5 - soil generation area; 6 - water phase range; 7 - air phase range. Detailed implementation mode

[0039] The invention object of the present invention will be further described in detail below in conjunction with the attached drawings and specific embodiments. The embodiments cannot be elaborated one by one here, but the implementation modes of the present invention are not limited to the following embodiments.

[0040] The agricultural machinery-paddy field coupling simulation method based on the secondary development of the discrete element method in this embodiment includes the following steps:

[0041] S1. Use 3D modeling software to construct a soil bin model and an agricultural machinery model, and both the soil bin model and the agricultural machinery model are exported as Parasolid XT files.

[0042] The agricultural machinery model includes a vehicle body model 1 and four tire models. The four tire models include two front wheel models 2 and two rear wheel models 3. The soil bin model includes an agricultural machinery placement area 4 and a soil generation area 5. The two front wheel models 2 and the two rear wheel models 3 both retain the tire details, and the tread details are used to accurately implement the interactive simulation of the paddy field soil model, and are assembled with the soil bin model and exported as Parasolid XT files. The two front wheel models 2 are respectively installed on the front two sides of the vehicle body model 1, and the two rear wheel models 3 are respectively installed on the rear two sides of the vehicle body model 1. The vehicle body model 1 is appropriately simplified. The vehicle body model 1 is placed in the agricultural machinery placement area 4. The length, width and height of the agricultural machinery placement area 4 are 3000mm * 3000mm * 700mm. The agricultural machinery placement area 4 and the soil generation area 5 are connected front and back. The two front wheel models 2 face the soil generation area 5, with a length, width and depth of 3000mm * 5000mm * 700mm and a wall thickness of 100mm.

[0043] The modeling process of the soil bin model in step S1 is as follows: Define the size of the agricultural machinery placement area 4 and the boundary range of the soil generation area 5 in the 3D modeling software. The height of the ground where the agricultural machinery placement area 4 is located matches the depth of the soil generation area 5, and the agricultural machinery placement area 4 is connected to the soil generation area 5.

[0044] S2. Establish a reduced soil bin two-phase flow model using computational fluid dynamics software. The modeling process of the reduced soil bin two-phase flow model in step S2 includes the following steps:

[0045] S201. Reduce the length and width of the soil bin model according to a preset ratio, and keep the depth of the soil bin model unchanged to obtain a reduced length and width model. Define the length, width, and depth of the soil as 30 mm * 30 mm * 700 mm.

[0046] S202. Define the reduced length and width model as a multiphase flow model (VOF, Volume of Fluid), the infiltration velocity of water is 0.5 m / s, the density of water and air, the viscosity parameters of water and air, and the initial occupied positions of the water phase and the air phase. Set the multiphase flow solver to simulate the liquid infiltration process, obtain the reduced soil bin two-phase flow model, and export it.

[0047] S3. Import the reduced soil bin two-phase flow model in step S2 into the discrete element software, set a soil container that coincides with the reduced soil bin two-phase flow model, the generation position of the particle factory is 600 mm, and generate soil particles. Set the density (4500 kg / m 3 ) and specific heat capacity (4200 J / (Kg*K)) of the imported soil particles in the interface of the computational fluid dynamics analysis software, the surface tension coefficient of the water phase is 0.005, set a solver suitable for two-phase operation, set the range of the air phase (the height from the bottom layer is 600 mm) and the range of the water phase (the position area 100 mm above the soil layer). After the simulation solution is completed, export the moisture content distribution. The types of soil particles include single spherical structure types and double spherical structure types. Among them, the single spherical structure type of soil particles includes two different diameters, which are 1 mm and 0.8 mm; the double spherical structure type of soil particles is composed of two spheres with a diameter of 1 mm, and the major axis diameter of the combined double-sphere particles is 1.5 mm. The inherent property parameters of the soil particles include density, elastic modulus, and Poisson's ratio. Set the restitution coefficient, dynamic friction coefficient, and static friction coefficient between the soil particles, and generate the soil particles to cover the soil generation area 5.

[0048] S4. Using the development toolkit based on the discrete element software, add the moisture content distribution in step S3 to the dynamic link library (DLL, Dynamic Link Library) using the integrated development environment software to obtain the modified particle bonding model (i.e., the dynamic link library file), and then import the modified particle bonding model into the discrete element software using the application programming interface (API, Application Programming Interface). Step S4 includes the following steps:

[0049] Specifically, step S4 includes the following steps:

[0050] S41. Perform secondary development on the header file to obtain the secondary development file. Specifically, step S41 includes the following steps:

[0051] S411. Locate the end of the class definition and add a container for storing the depth - moisture content correspondence in the private area of the class definition;

[0052] S412. Define a method for obtaining the moisture content according to the depth of the container, and at the same time define the linear interpolation method for obtaining the depth and its variable definition to obtain the secondary development header file.

[0053] S42. Perform secondary development on the source file to obtain the secondary development source file; step S42 includes the following steps:

[0054] S421. Based on the original SDK (Software Development Kit) code provided by the discrete element software, first insert the moisture content distribution in step S3;

[0055] S422. Then define the linear interpolation method for feedbacking the moisture content according to the depth;

[0056] S423. Finally, insert the formula for the moisture content and depth affecting the particle bonding model, that is, insert the code that can obtain the average depth according to the depth between two adjacent soil particles after the normal force calculation code in the original SDK code, which can obtain the moisture content according to the depth, and at the same time define the depth influence coefficient (such as increasing the viscosity by 10% per 10 cm of depth), the moisture content influence coefficient (such as increasing the viscosity by 10% per 10% of moisture content), and comprehensively adjust the friction coefficient (original friction coefficient × depth influence coefficient × moisture content influence coefficient) and import the comprehensively adjusted friction coefficient into the tangential force calculation formula of the original SDK code to obtain the secondary development source file.

[0057] S43. Generate the modified dynamic link library file from the secondary development header file in step S41 and the secondary development source file in step S42, and import the modified dynamic link library file into the discrete element software.

[0058] S5. Import both the agricultural machinery model and the soil bin model from Step S1 into the multi-body dynamics software. Set the weight of the agricultural machinery model, the motion parameters of the agricultural machinery model, and the contact properties between the tires and soil particles. Apply the liquid resistance, the motion state of the agricultural machinery, and the force data of the soil particles in Step S3 to the agricultural machinery model.

[0059] The specific steps of applying the liquid resistance, the motion state of the agricultural machinery, and the force data of the soil particles in Step S3 to the agricultural machinery model in Step S5 are as follows:

[0060] S501. Define the motion parameters of the tire model of the agricultural machinery model and the contact mechanical properties with soil particles (including the weight of the agricultural machinery model, the rotational speed or torque of the tires, and the physical contact between the tires and the ground and soil particles) in the multi-body dynamics software.

[0061] S502. Construct a resistance model based on the hydrodynamic characteristics of the free water surface. Apply the liquid resistance calculated by the formula of the free water surface resistance F ( where ρ is the density of free water, C d is the resistance coefficient of free water, A is the cross-sectional area of the tire model, and v is the relative velocity between the free water and the tire model) to the agricultural machinery model by transmitting the motion state of the agricultural machinery and the force data of the soil particles in real time through the coupling interface.

[0062] S6. Couple the multi-body dynamics software in Step S4 and the multi-body dynamics software in Step S5, set the solution scheme for solving, and use the coupling to mutually call and transfer the real-time calculation results between the multi-body dynamics and the discrete element simulation software, thereby completing the interactive simulation.

[0063] The above specific implementation manners are the preferred embodiments of the present invention and cannot limit the present invention. Any other changes or other equivalent replacement methods made without departing from the technical solution of the present invention are included in the protection scope of the present invention.

Claims

1. A simulation method for coupling agricultural machinery and paddy fields based on secondary development of discrete element method, characterized in that: It includes the following steps: S1. Use 3D modeling software to construct a soil bin model and an agricultural machinery model; S2. Use computational fluid dynamics software to establish a reduced-scale two-phase flow model of the soil bin; S3. Import the reduced-scale two-phase flow model of the soil bin in step S2 into the discrete element software to generate soil particles, and solve them coupledly to obtain the moisture content distribution; S4. Based on the software development kit of the discrete element software, modify the particle bonding model through secondary development of the dynamic link library, add the influence of the moisture content distribution in step S3 to the particle bonding model, obtain the modified dynamic link library file, and import the modified dynamic link library file into the discrete element software; S5. Import both the agricultural machinery model and the soil bin model in step S1 into the multibody dynamics software, set the weight of the agricultural machinery model, the motion parameters of the agricultural machinery model, and the contact properties between the tires and the soil particles, and apply the liquid resistance, the motion state of the agricultural machinery, and the force data of the soil particles in step S3 to the agricultural machinery model; S6. Couple the discrete element software in step S4 with the multibody dynamics software in step S5 to complete the interactive simulation.

2. The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development according to claim 1, wherein: The tire model of the agricultural machinery model in step S1 has tread details.

3. The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development according to claim 1, wherein: The modeling process of the soil bin model in step S1 is as follows: Define the size of the agricultural machinery placement area and the boundary range of the soil generation area in the 3D modeling software. The height of the ground where the agricultural machinery placement area is located matches the depth of the soil generation area, and the agricultural machinery placement area is connected to the soil generation area.

4. The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development according to claim 1, characterized in that: Step S2 includes the following steps: S201. Reduce the length and width of the soil bin model according to a preset ratio, and keep the depth of the soil bin model unchanged to obtain a reduced-length-and-width model; S202. Define the reduced-length-and-width model as a multiphase flow model, define the infiltration velocity of the water flow, the densities of water and air, the viscous parameters of water and air, and the initial positions occupied by the water phase and the air phase, set the multiphase flow solver to simulate the liquid infiltration process, and obtain and export the reduced-scale two-phase flow model of the soil bin.

5. The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development according to claim 1, characterized in that: The inherent property parameters of the soil particles in step S3 include density, elastic modulus, and Poisson's ratio. Set the restitution coefficient, dynamic friction coefficient, and static friction coefficient between the soil particles.

6. The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development according to claim 1, characterized in that: Step S4 includes the following steps: S41. Conduct secondary development on the header file to obtain a secondary development file; S42. Conduct secondary development on the source file to obtain a secondary development source file; S43. Generate a modified dynamic link library file from the secondary development header file in step S41 and the secondary development source file in step S42, and import the modified dynamic link library file into the discrete element software.

7. The method for simulating the coupling of agricultural machinery and paddy fields based on secondary development of discrete element according to claim 6, wherein: Step S41 includes the following steps: S411. Find the end of the class definition, and add a container for storing the depth-moisture content correspondence relationship in the private area of the class definition; S412. Define the method for obtaining the moisture content according to the depth of the container, and at the same time define the linear interpolation method for obtaining the depth and its variable definition to obtain the secondary development header file.

8. The agricultural machinery-paddy field coupling simulation method based on discrete element secondary development according to claim 6, characterized in that: Step S42 includes the following steps: S421. Based on the original SDK code provided by the discrete element software, first insert the moisture content distribution in step S3; S422. Then define the linear interpolation method for feedbacking the moisture content according to the depth. S423. Finally, insert the formula of the particle bonding model affected by moisture content and depth to obtain the secondary development source file.

9. The method for simulating the coupling of agricultural machinery and paddy fields based on discrete element secondary development according to claim 1, wherein: The calculation formula of the liquid resistance F in step S5 is where ρ is the density of free water, C d is the drag coefficient of free water, A is the cross-sectional area of the tire model, and v is the relative velocity between the free water and the tire model.

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