Stirring device multi-body multi-field coupling dynamics modeling simulation method and system

Abstract

The disclosure provides a stirring device multi-body multi-field coupling dynamics modeling simulation method and system, relates to the technical field of modeling simulation, and comprises the following steps: obtaining structure information, operation condition information and to-be-stirred material information of a target stirring device; based on the structure information and the operation condition information, performing multi-body dynamics modeling on the target stirring device to obtain a stirring device multi-body dynamics model; according to calibrated to-be-stirred material information, building a multi-body multi-field coupling simulation environment; and using the multi-body multi-field coupling simulation environment and the stirring device multi-body dynamics model, performing multi-body multi-field coupling simulation on the target stirring device to obtain simulation data; the present application does not need to perform grid division on fluid slurry domains and bulk particle domains, can greatly improve the calculation efficiency, can also monitor the stirring effect of the stirring device in real time, and can analyze the stirring effect of the stirring device.

Description

Technical Field

[0001] This disclosure relates to the field of modeling and simulation technology, specifically to a method and system for modeling and simulating the multibody multifield coupled dynamics of a stirring device. Background Technology

[0002] Agitators agitate fluid slurries (such as cement slurry) by rotating blades or other structures, causing them to flow, shear, or turbulently. This allows the slurry to interact with bulk particles (such as soil) to achieve mixing, heat transfer, or suspension. Agitators are widely used in chemical synthesis, mineral processing, pharmaceutical granulation, food mixing, and environmental sludge treatment. Optimizing the design of agitator structures and construction processes to achieve more uniform mixing results is of great research significance.

[0003] Taking cement mixing piles as an example, cement mixing piles, as a type of mixing device, are a construction method used to reinforce the foundation at a construction site. They use mixing machinery to mix the soil and grout beneath the foundation. After the grout and soil have fully reacted and solidified, individual piles are formed, thereby strengthening the foundation. The structure, rotation, and feed speed of the mixing device, among other construction process parameters, directly affect the quality of cement mixing pile formation. Therefore, optimizing the structure and process of cement mixing piles is of great significance.

[0004] Numerical simulation of cement mixing piles is conducted to analyze their mechanical behavior and fluid-structure interaction in reinforcing soft soil foundations, thereby optimizing design parameters and improving mixing efficiency. By modeling and simulating the dynamic phenomena during cement mixing, the performance characteristics of cement mixing piles under different working conditions can be analyzed in depth. The distribution characteristics of cement slurry mixed with soil during the mixing process can be analyzed, providing a basis for optimizing the structure and construction technology of cement mixing piles. Real-time and efficient monitoring of grouting and mixing effects is possible, and the simulation results can be used to improve the structure of mixing equipment and optimize the mixing process.

[0005] The cement mixing process involves three material properties: cement mixing piles (i.e., rigid structures), cement slurry (i.e., liquid), and soil (i.e., loose particles). This falls under the category of fluid-structure interaction numerical simulation. Currently, most analyses of this type use the CFD (Computational Fluid Dynamics)-DEM (Discrete Element Method) approach. This method treats the fluid as a continuous medium, requiring mesh generation and solution of its computational space. For cement mixing fluid-structure simulation, accurately generating fluid meshes is challenging, especially given the involvement of fluid motion boundaries or free interfaces. Therefore, traditional meshing methods present certain difficulties. To obtain accurate calculation results, high quality and quantity of mesh generation are crucial. A large number of fluid meshes and particles increases computation time, reduces simulation efficiency, and the quality of mesh generation directly impacts the calculation results.

[0006] Therefore, existing technologies cannot guarantee computational efficiency while accurately dividing the fluid domain mesh, affecting the performance and accuracy of numerical simulations of mixing devices, including cement mixers, for pile mixing. Summary of the Invention

[0007] To address the aforementioned issues, this disclosure proposes a multi-body, multi-field coupled dynamic modeling and simulation method and system for mixing devices. This method eliminates the need for meshing the fluid domain, significantly improving computational efficiency while enabling real-time monitoring of the mixing effect of the mixing piles. It also allows for analysis of the mixing effect of the mixing device, thereby determining the optimal drill bit structure and construction process.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions: Multibody multifield coupled dynamics modeling and simulation methods for stirring devices include: The structural information, operating condition information, and material information of the target mixing device are obtained. The target mixing device adopts a multi-body structure composed of several rigid bodies. The operating condition information includes construction process parameters for the rotation and movement of the mixing device. The material information includes physical property parameters of fluid slurry and granular particles. Based on structural information and operating condition information, a multibody dynamics model of the target mixing device is performed to obtain the multibody dynamics model of the mixing device. Based on the calibrated information of the material to be stirred, a multi-body, multi-field coupled simulation environment is built. Using a multibody multifield coupled simulation environment and a multibody dynamics model of the stirring device, multibody multifield coupled simulation of the target stirring device is performed to obtain simulation data. The construction of the multi-body multi-field coupled simulation environment includes building a fluid slurry model and a granular particle model. The fluid slurry model is constructed based on the semi-implicit moving particle method, which divides the fluid into particles and uses discrete particles to solve the nonlinear Navier-Stokes equations to simulate the mixing process of fluid slurry by a stirring device.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions: A multi-body, multi-field coupled dynamics modeling and simulation system for a stirring device includes: The information acquisition module is configured to acquire structural information, operating condition information and material information of the target mixing device. The target mixing device adopts a multi-body structure composed of several rigid bodies. The operating condition information includes construction process parameters for the rotation and movement of the mixing device. The material information includes physical property parameters of fluid slurry and granular particles. The model building module is configured to: perform multibody dynamics modeling on the target mixing device based on structural information and operating condition information, and obtain the multibody dynamics model of the mixing device. The environment setup module is configured to: build a multi-body, multi-field coupled simulation environment based on the calibrated information of the material to be stirred; The coupled simulation module is configured to: use the multibody multifield coupled simulation environment and the multibody dynamics model of the stirring device to perform multibody multifield coupled simulation on the target stirring device and obtain simulation data; The construction of the multi-body multi-field coupled simulation environment includes building a fluid slurry model and a granular particle model. The fluid slurry model is constructed based on the semi-implicit moving particle method, which divides the fluid into particles and uses discrete particles to solve the nonlinear Navier-Stokes equations to simulate the mixing process of fluid slurry by a stirring device.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions: A computer program product includes a computer program that, when executed by a processor, implements the multibody multifield coupled dynamics modeling and simulation method for the stirring device.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions: A non-transitory computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement the multi-body multi-field coupled dynamics modeling and simulation method for the stirring device.

[0012] According to some embodiments, the present disclosure adopts the following technical solutions: An electronic device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the multi-body multi-field coupled dynamics modeling and simulation method for the stirring device.

[0013] Compared with the prior art, the beneficial effects of this disclosure are as follows: This invention uses a semi-implicit moving particle method to model the fluid of slurry, dividing the fluid into particles for computation. This avoids meshing the fluid domain and eliminates the need to predefine meshes in areas where the fluid may reach, making it suitable for simulating the slurry spraying process of a mixing device.

[0014] This invention performs multibody dynamics modeling on a stirring device composed of several rigid bodies, and adds rotational and feed constraints as well as hinge constraints, which better reflects the actual working conditions of the stirring device and improves the accuracy of the modeling.

[0015] Considering the interaction of multiple bodies and multiple fields in multi-body multi-field coupled dynamic modeling and simulation scenarios, this invention provides a calibration sequence and method for the physical property parameters of fluid slurry and granular particles, ensuring the accuracy of the parameters used for modeling, thereby improving the accuracy of modeling.

[0016] This invention provides a method for evaluating the mixing effect of a mixing device. It uses simulation results to calculate the mixing ratio of bulk particles and slurry particles, and evaluates the mixing effect based on the mixing ratio, thereby improving the accuracy of the evaluation. Attached Figure Description

[0017] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0018] Figure 1 This is a flowchart of the method in Example 1. Figure 2 This is a structural diagram of a cement mixing pile in Example 1. Figure 3 This is a schematic diagram of the cement slurry static dripping test results in Example 1.

[0019] Figure 4 This is a schematic diagram of the cement slurry slippage test results in Example 1.

[0020] Figure 5 This is a schematic diagram of the cement slurry slippage simulation calibration in Example 1.

[0021] Figure 6 This is a schematic diagram of the soil accumulation angle experiment results in Example 1.

[0022] Figure 7 This is a schematic diagram of the soil accumulation angle simulation calibration in Example 1.

[0023] Figure 8 This is a calibration flowchart for Example 1.

[0024] Figure 9 This is a schematic diagram of the cement mixing pile simulation model of Example 1.

[0025] Figure 10 This is a schematic diagram of the simulation results of cement mixing piles in Example 1.

[0026] Wherein, 1: drill rod, 2: drill bit, 3: first mixing blade, 4: first spray nozzle, 5: second spray nozzle, 6: second mixing blade. Detailed Implementation

[0027] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0028] Example 1 One embodiment of this disclosure provides a multi-body, multi-field coupled dynamic modeling and simulation method for a mixing device. This method significantly improves computational efficiency, enables real-time monitoring of the mixing effect of the mixing pile, and allows for analysis of the mixing effect of the mixing device, thereby determining the optimal drill bit structure and construction process.

[0029] There are many types of mixing devices involving multibody and multifield coupling, including cement mixing piles, bio-fermentation tank mixers, and food mixers. This embodiment takes a cement mixing pile as an example, using Particleworks and RecurDyn software for co-simulation. Particleworks is an MPS-based computational fluid dynamics software, and RecurDyn is a computational multibody dynamics (MFBD) software capable of co-simulating with the Particleworks particle solver. Of course, those skilled in the art can choose appropriate modeling software based on their own circumstances and needs, and are not limited to the above example. The following is an example... Figure 1 The steps shown are as follows: Step S1: Obtain the structural information, operating condition information, and material information of the target mixing device. The target mixing device adopts a multi-body structure composed of several rigid bodies. The operating condition information includes the construction process parameters for the rotation and movement of the mixing device. The material information includes the physical property parameters of the fluid slurry and the granular particles.

[0030] Furthermore, the structural information is represented by a three-dimensional geometric model of the target mixing device; wherein, the rigid body in the three-dimensional geometric model includes a drill rod, a drill bit, mixing blades, and a spray nozzle, a cylindrical pair is provided between the drill rod and the ground, the drill bit is fixed to the lower end of the drill rod, the drill bit is provided with hinged mixing blades, and the spray nozzle is arranged on the drill bit.

[0031] Specifically, the cement mixing pile (i.e., the target mixing device) consists of a drill rod 1, a drill bit 2, mixing blades, etc., such as Figure 2 As shown, the cement mixing pile has a rotating motion along the axis and a downward feeding motion. Therefore, a cylindrical pair shown in red is set between the drill rod 1 and the ground. The drill bit 2 is fixed at the lower end of the drill rod 1 and can rotate along the axis with the drill rod 1.

[0032] Two similar mixing blades are arranged on the drill bit 2: a rigidly connected first mixing blade 3 and a hinged second mixing blade 6. A set of first mixing blades 3 is fixed at the lower end of the drill bit 2, with a certain angle of inclination to the horizontal plane. A first nozzle 4 is arranged at the end of the first mixing blade 3 for spraying cement slurry (i.e., grout). Cutting blades are arranged on both sides of the first nozzle 4, and the cutting blades are longer than the nozzle 4, which are used to cut the soil clods during the mixing process to create a spraying space for the first nozzle 4. Above the first mixing blade 3, a second nozzle 5 is arranged on the side wall of the drill bit 2 so that the cement slurry is sprayed evenly in the radial direction of the mixing pile. The drill bit is equipped with two sets of hinged mixing blades, which are spaced a certain distance along the axial direction. Each set consists of two second mixing blades 6, which are arranged at 180° intervals along the circumference.

[0033] Based on the above structure, a three-dimensional geometric model is constructed according to the geometric parameters of the cement mixing pile. The geometric parameters include the position of the spray nozzle, the size of the spray nozzle, the blade length, the inclination angle, etc.

[0034] Step S2: Based on structural information and operating condition information, perform multibody dynamics modeling on the target mixing device to obtain the multibody dynamics model of the mixing device. The specific steps are as follows: Step S2-1: Import the three-dimensional geometric model of the target stirring device into the multibody dynamics software.

[0035] Specifically, the three-dimensional geometric model obtained in step S1 is imported into the RecurDyn dynamics software.

[0036] Step S2-2: In the multibody dynamics software, based on the connection relationship of each rigid body in the three-dimensional geometric model, set the rotation and feed constraints of the cylindrical pair and the hinge constraints of the stirring blades to establish the motion constraint relationship of the target stirring device.

[0037] Based on the cylindrical pair set between drill rod 1 and the ground, rotation and feed constraints are added to constrain its two movements, making them conform to the actual working conditions of the mixing device.

[0038] The stirring blades of the stirring device are hinged to the drill bit, and can rotate around the hinge position to form a contact relationship with the drill bit sidewall based on Hertzian contact theory. A contact model between the stirring blades and the drill bit is set to constrain the range of motion of the stirring blades.

[0039] The mixing operation includes various working conditions such as the forward movement speed, rotation speed, and reverse rotation stroke and speed. In this embodiment, the drill pipe feed speed is 75-100 cm / min and the rotation speed is 30-60 rpm. Within this range, based on construction requirements, a combination of feed speed and rotation speed is selected. The function equation is used to define the driving force of the rotation and feed speed of the cylindrical pair. The feed speed and rotation speed are independent variables. By modifying the relationship between the feed speed and rotation speed and time, a multi-condition operation mode is defined.

[0040] Step S3: Based on the calibrated information of the material to be stirred, build a multi-body multi-field coupled simulation environment.

[0041] The construction of the multi-body, multi-field coupled simulation environment includes building a slurry model and a granular particle model. The methods for building the two models include: (1) Calibrate the physical property parameters of the slurry and construct the slurry model.

[0042] Based on the semi-implicit method of moving particles, particle discrete continuum mechanics is used to divide the fluid into particles to simulate the grouting process of mixing piles. This involves constructing fluid particle objects to simulate the grout, whose physical parameters include the intrinsic parameters of the grout, the grout-steel contact coefficient, and the grout-soil contact coefficient. The intrinsic parameters of the grout include density, surface tension coefficient, and kinematic viscosity. The grout-steel contact coefficient includes the slip coefficient and contact angle with the steel. The grout-soil contact coefficient includes the grout-soil slip coefficient. The calibration method is as follows: First, define the diameter of fluid slurry particles. The slurry density can be measured by the mass-volume method, the kinematic viscosity can be directly measured by a viscometer, and the surface tension coefficient can be directly measured by a surface tension meter. Then, the slip coefficient and contact angle between the grout and steel (i.e., the cement mixing pile with multi-body structure) were obtained by calibrating the grout-steel plate slip test and the grout-steel plate static drip test, respectively. Finally, the slurry-soil slip coefficient can be obtained through slurry-soil slip test.

[0043] Specifically, this embodiment calibrates the slurry-steel contact angle and slurry-steel slip coefficient based on slurry-steel static dripping and slurry-steel slipping experiments. Seven groups of slurries with water-cement ratios ranging from 0.6 to 1.2 were prepared. Since slurry temperature changes significantly affect its adhesion properties, the prepared slurries were heated to 20 degrees Celsius in a water bath. After heating, the kinematic viscosity and surface tension coefficient of the slurry were measured using a viscometer and a surface tension coefficient meter. The measurement results are shown in Tables 1 and 2.

[0044] Table 1. Experimental results of cement slurry kinematic viscosity determination

[0045] Table 2. Experimental results of surface tension coefficient determination of pure water and cement slurry

[0046] A cement slurry-steel static drip test was conducted. Using a dropper, 1 ml of cement slurry was drawn and steadily dripped onto the steel plate surface. The contact angle was measured within 50-70 seconds to avoid the influence of droplet diffusion or solidification reaction on the measurement results. This test was used to calibrate the cement slurry-steel contact angle. Figure 3 Table 3 shows the static dripping test results of cement grout with a water-cement ratio of 0.6.

[0047] Table 3 Results of static drip test of cement grout

[0048] A cement slurry-steel slip test was conducted. 1 ml of cement slurry was drawn using a dropper and steadily dripped onto a steel plate inclined at a 25° angle. The maximum distance the slurry could slide down was measured to calibrate the cement slurry-steel slip coefficient. The experimental phenomena are as follows: Figure 4 As shown in Table 4, the results of the cement slurry-steel slip test with different water-cement ratios are presented.

[0049] Table 4 Results of Cement Grout Slip Test

[0050] Based on the experimental results of cement slurry, a fluid property object was established, and a simulation model with the same cement slurry-steel slip test device was built for calibration. Seven sets of velocity boundaries were set, corresponding to seven sets of cement slurry with different water-cement ratios. The velocity boundaries could spray cement slurry particles outward at the set speed to simulate the process of cement slurry dripping from the dropper in the cement slurry-steel slip test. In the model, an inclined plate at a 25° angle to the horizontal plane was set below the seven sets of velocity boundaries to simulate the steel plate in the slip test. Cement slurry particles were sprayed out from the velocity boundaries, and the distance that the cement slurry particles slid off the steel plate in the model was measured. Based on this cement slurry-steel slip simulation model and experimental results, the cement slurry-steel slip coefficient was calibrated. The calibration results are as follows: Figure 5 As shown.

[0051] Using cement grout with a water-cement ratio of 0.6 as the research object, and based on the calibration results, the physical density of cement grout with a water-cement ratio of 0.6 was set at 1750 kg / m³. 3 The kinematic viscosity is 1.37 × 10⁻⁶. -4 m 3The surface tension coefficient is 0.068 N / m. The slip coefficient between the cement slurry and soil particles is set to 15, and the slip coefficient between the cement slurry and the mixing device is set to 5. The contact angle is set to 22.28°. Based on these calibration results, a cement slurry model is established. Based on the MPS governing equations, the pressure term of the cement slurry particles is calculated implicitly, while the viscosity is calculated explicitly. The surface tension model is the CSF (Continuum Surface Force) model. Based on the model size and computational efficiency in this embodiment, the diameter of the cement slurry particles is set to 6 mm.

[0052] The cement slurry model is constructed based on the calibrated intrinsic parameters of cement slurry, the cement slurry-steel contact coefficient, and the cement slurry-soil granular particle contact coefficient. Using the semi-implicit moving particle method and particle discrete continuum mechanics, the fluid is divided into particles. The mass conservation equation and momentum conservation equation in the semi-implicit moving particle method are used to control the spraying process. The nonlinear Navier-Stokes equations are solved using discrete particles to simulate the mixing process of the fluid slurry in the mixing device. A pressure boundary is set at the spray port of the mixing device, and the pressure boundary can spray cement slurry particles outward according to the set pressure.

[0053] (2) Calibrate the physical property parameters of soil granules and construct a soil granule model.

[0054] The physical properties of soil particles are used to simulate soil particle size distribution. These physical properties include intrinsic soil parameters, soil particle-soil particle contact coefficients, soil particle-steel contact coefficients, and cement slurry-soil particle contact coefficients. The intrinsic soil particle parameters include soil density, Young's modulus, and Poisson's ratio. The soil particle-soil particle contact coefficients include adhesion coefficients and contact force coefficients. The soil particle-steel contact coefficients include static friction coefficients and dynamic friction coefficients. The cement slurry-soil particle contact coefficients include the cement slurry-soil slip coefficient. The calibration method is as follows: First, define the particle diameter of the granular material. The density can be measured by the mass-volume method, and Young's modulus and Poisson's ratio can be measured by shear tests. Then, the soil particle-soil particle adhesion coefficient and contact force coefficient can be obtained by soil angle of repose test; Secondly, the static and dynamic friction coefficients between soil particles and steel can be obtained through soil-steel slip tests. Finally, the slip coefficient of cement grout-soil granules can be obtained by cement grout-soil slip test.

[0055] Specifically, this embodiment calibrates the adhesion and contact force coefficients between soil particles based on the soil angle of repose experiment. Soil was dried in a constant temperature oven at 105 degrees Celsius for 8 hours, and then a soil sample with a moisture content of 25% was prepared. The soil angle of repose experiment was then performed to calibrate the liquid bridge force and van der Waals force coefficients between particles. To improve measurement accuracy, the angle of repose experiment is usually repeated multiple times and the average value is taken. The angles of repose measured in 7 sets of experiments were 39.01°, 37.55°, 35.24°, 37.80°, 39.62°, 35.53°, and 37.30°, respectively. The calculated average angle of repose was 37.44°. The experimental phenomena are as follows: Figure 6 As shown.

[0056] Based on the soil angle of repose experiment, a particle attribute object was established, and a simulation model with the same angle of repose experimental setup was built for calibration. The calibration results are as follows: Figure 7 As shown. In the particle properties, based on the calibrated intrinsic parameters of soil granular particles, soil granular particle-soil granular particle contact parameters, soil granular particle-steel contact parameters, and cement grout-soil granular particle contact parameters, a soil granular particle model is constructed based on the Hertzian contact model, considering the contact effects between particles. Simultaneously, to consider the interparticle forces that bind the soil granular particles together, van der Waals force and liquid bridge force models are used to establish the adhesion forces between soil granular particles, thus establishing the soil granular particle model. The density is set to 2660 kg / m³. 3 The Young's modulus is 0.03 GPa, Poisson's ratio is 0.36, surface roughness is set to 2 mm, interparticle restitution coefficient is set to 0.5, elastic modulus is set to 500, shape factor is set to 2, contact angle parameter in interparticle liquid bridging force is set to 30°, dimensionless volume is set to 2, and adjustment factor in van der Waals force is set to 1000. Soil granular particle diameters are set to 8, 9, and 10 mm, with proportions of 30%, 40%, and 30%, respectively.

[0057] In summary, the parameter composition and calibration process of the cement slurry and soil granular particle models are as follows: Figure 8 As shown.

[0058] Step S4: Using a multibody multifield coupled simulation environment and a multibody dynamics model of the stirring device, perform multibody multifield coupled simulation on the target stirring device to obtain simulation data.

[0059] After configuring the Particleworks-RecurDyn co-simulation environment, generate a wall file from the dynamic model created in RecurDyn and import it into Particleworks. Set a pressure boundary at the nozzle of the mixing device to spray cement slurry particles. The maximum mixing diameter of the mixing device is 800mm. To generate soil loose particles and avoid wall effects during mixing, place a cylindrical container with an inner diameter of 1200mm below the mixing device. The model is as follows. Figure 9 As shown.

[0060] After the parameters of cement slurry and soil granules were calibrated, preprocessing was performed based on the current model to generate an initial particle swarm. The co-simulation function with Particleworks was then enabled in RecurDyn, with the simulation time set to 75 seconds and the step size to 0.005 seconds. Simulation calculations were then performed, yielding the following results: Figure 10 The simulation results are as described.

[0061] This embodiment conducts a multi-body, multi-field coupled dynamics simulation of the stirring device. The specific steps are as follows: Set the physical properties of the mixing device wall model, and set the pressure boundary at the nozzle position to spray fluid particles to simulate the process of the mixing device spraying cement slurry. Based on actual engineering needs, set multiple operating parameters for the mixing device, including different rotation and feed speeds and shotcrete pressures; Dynamic simulation of the mixing device under multiple working conditions was carried out. By setting the rotation and feed drive of the mixing device, as well as the grouting pressure on the pressure boundary, the multi-physics dynamic simulation of the mixing device was controlled to complete the mixing process, and the simulation results of the mixing pile were obtained.

[0062] Step S5: After the simulation is completed, the simulation data is analyzed to evaluate the stirring effect of the target stirring device.

[0063] The probe function in Particleworks can be used to analyze the mixing effect of cement slurry particles and soil particles. By setting several detection areas on the mixed pile, the probe function can calculate the number of cement slurry particles and soil particles and the proportion of the mixture composition within the set areas. By comparing the proportions of cement slurry particles and soil particles in several detection areas and between different areas, the mixing effect of the mixing pile can be analyzed, which serves as the basis for judging the mixing effect of the mixing pile. The mixing effect in a certain example is shown in Table 5. Among them, there is a large difference in the mixing ratio of soil particles and cement slurry particles between areas 1 and 5. The proportion of cement slurry particles in area 1 is 53.28%, which is significantly less than the proportion of cement slurry particles in area 5 (73.21%). This indicates that the distribution of mixed particles is uneven between areas 1 and 5.

[0064] Table 5. Mixing effect of cement slurry particles and soil bulk particles

[0065] Example 2 One embodiment of this disclosure provides a multi-body, multi-field coupled dynamics modeling and simulation system for a stirring device, including: The information acquisition module is configured to acquire structural information, operating condition information and material information of the target mixing device. The target mixing device adopts a multi-body structure composed of several rigid bodies. The operating condition information includes construction process parameters for the rotation and movement of the mixing device. The material information includes physical property parameters of fluid slurry and granular particles. The model building module is configured to: perform multibody dynamics modeling on the target mixing device based on structural information and operating condition information, and obtain the multibody dynamics model of the mixing device. The environment setup module is configured to: build a multi-body, multi-field coupled simulation environment based on the calibrated information of the material to be stirred; The coupled simulation module is configured to: use the multibody multifield coupled simulation environment and the multibody dynamics model of the stirring device to perform multibody multifield coupled simulation on the target stirring device and obtain simulation data; The construction of the multi-body multi-field coupled simulation environment includes building a fluid slurry model and a granular particle model. The fluid slurry model is constructed based on the semi-implicit moving particle method, which divides the fluid into particles and uses discrete particles to solve the nonlinear Navier-Stokes equations to simulate the mixing process of fluid slurry by a stirring device.

[0066] Example 3 One embodiment of this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the multibody multifield coupled dynamics modeling and simulation method for the stirring device.

[0067] Example 4 One embodiment of this disclosure provides a non-transitory computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, they implement the multi-body multi-field coupled dynamics modeling and simulation method for the stirring device.

[0068] Example 5 One embodiment of this disclosure provides an electronic device, including a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to implement the multi-body multi-field coupled dynamics modeling and simulation method for the stirring device.

[0069] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0070] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0071] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A multi-body, multi-field coupled dynamic modeling and simulation method for a stirring device, characterized in that, include: The structural information, operating condition information, and material information of the target mixing device are obtained. The target mixing device adopts a multi-body structure composed of several rigid bodies. The operating condition information includes construction process parameters for the rotation and movement of the mixing device. The material information includes physical property parameters of fluid slurry and granular particles. Based on structural information and operating condition information, a multibody dynamics model of the target mixing device is performed to obtain the multibody dynamics model of the mixing device. Based on the calibrated information of the material to be stirred, a multi-body, multi-field coupled simulation environment is built. Using a multibody multifield coupled simulation environment and a multibody dynamics model of the stirring device, multibody multifield coupled simulation of the target stirring device is performed to obtain simulation data. The construction of the multi-body, multi-field coupled simulation environment includes building a fluid slurry model and a granular particle model. The fluid slurry model is built based on the semi-implicit moving particle method, which divides the fluid into particles and uses discrete particles to solve the nonlinear Navier-Stokes equations to simulate the mixing process of the fluid slurry in the stirring device. The granular particle model is built based on the calibrated intrinsic parameters of the granular particles, the contact coefficient between granular particles, the contact coefficient between granular particles and multi-body structures, and the contact coefficient between fluid slurry and granular particles. Based on the Hertzian contact model, the particle domain is divided into particles, and discrete particles are used to solve the contact forces between particles. Based on the van der Waals force and liquid bridge force models, an adhesion force model between granular particles is established.

2. The multi-body, multi-field coupled dynamics modeling and simulation method for a stirring device as described in claim 1, characterized in that, The structural information is represented by a three-dimensional geometric model of the target stirring device; The rigid body in the three-dimensional geometric model includes a drill rod, a drill bit, a stirring blade, and a spray nozzle. A cylindrical pair is set between the drill rod and the ground. The drill bit is fixed to the lower end of the drill rod. A hinged stirring blade is set on the drill bit, and the spray nozzle is arranged on the drill bit.

3. The multi-body, multi-field coupled dynamics modeling and simulation method for a stirring device as described in claim 2, characterized in that, The specific steps for multibody dynamics modeling are as follows: Import the three-dimensional geometric model of the target stirring device into the multibody dynamics software; In multibody dynamics software, based on the connection relationships of each rigid body in the three-dimensional geometric model, the relationship between the drill rod and the ground is defined using cylindrical joints, and the rotation and movement drive constraints of the cylindrical joints are defined using function expressions to simulate the rotation and movement construction process of the mixing device; the hinge constraints between the mixing blades and the drill bit are defined using rotary joints to establish the motion constraint relationship of the target mixing device.

4. The multi-body, multi-field coupled dynamics modeling and simulation method for a stirring device as described in claim 1, characterized in that, The physical property parameters of the fluid slurry include the intrinsic parameters of the fluid slurry, the fluid slurry-multibody structure contact coefficient, and the fluid slurry-granular particle contact coefficient. The intrinsic parameters of the fluid slurry include density, surface tension coefficient, and kinematic viscosity; the fluid slurry-multibody structure contact coefficient includes the slip coefficient and contact angle between the fluid slurry and the multibody structure; and the fluid slurry-granular particle contact coefficient includes the fluid slurry-granular particle slip coefficient.

5. The multi-body multi-field coupled dynamic modeling and simulation method for a stirring device as described in claim 1, characterized in that, The calibration method for the physical property parameters of the fluid slurry is as follows: First, define the particle diameter of the fluid slurry, and measure the density, surface tension coefficient, and kinematic viscosity of the fluid slurry; Then, the slip coefficient and contact angle between the fluid slurry and the multibody structure were obtained by fluid slurry-multibody structure slip test and fluid slurry-multibody structure static drop test, respectively. Finally, the fluid slurry-particle slip coefficient was obtained through fluid slurry-particle slippage experiments.

6. The multi-body, multi-field coupled dynamics modeling and simulation method for a stirring device as described in claim 1, characterized in that, The fluid slurry model is constructed based on the calibrated intrinsic parameters of the fluid slurry, the fluid slurry-multibody structure contact coefficient, and the fluid slurry-granular particle contact coefficient. The fluid slurry model is established using the semi-implicit moving particle method, and the mass conservation equation and momentum conservation equation in the semi-implicit moving particle method are used to control the slurry spraying process.

7. The multi-body, multi-field coupled dynamic modeling and simulation method for a stirring device as described in claim 1, characterized in that, The physical property parameters of the granular particles include the intrinsic parameters of the granular particles, the contact coefficient between granular particles, the contact coefficient between granular particles and multi-body structures, and the contact coefficient between slurry fluid and granular particles. Among them, the intrinsic parameters of granular particles include particle density, Young's modulus, and Poisson's ratio; the granular particle-granular particle contact coefficient includes adhesion coefficient and contact force coefficient; the granular particle-multibody structure contact coefficient includes static friction coefficient and dynamic friction coefficient; and the fluid slurry-granular particle contact coefficient includes fluid slurry-granular particle slip coefficient.

8. The multi-body, multi-field coupled dynamics modeling and simulation method for a stirring device as described in claim 7, characterized in that, The method for calibrating the physical property parameters of the granular particles is as follows: First, define the particle diameter of the granular material, and measure the particle density, Young's modulus, and Poisson's ratio. Then, the adhesion coefficient and contact force coefficient between granular particles were obtained through experiments on the angle of repose of granular particles. Secondly, the static and dynamic friction coefficients of the granular-multibody structure were obtained by calibrating the granular-multibody structure slip test. Finally, the fluid slurry-particle slip coefficient was obtained by calibrating the fluid slurry-particle slip test.

9. The multi-body, multi-field coupled dynamics modeling and simulation method for a stirring device as described in claim 1, characterized in that, This also includes analyzing simulation data to evaluate the mixing effect of the target mixing device, specifically: Within the mixing range of the mixing pile, several testing areas are set up, and the shape, size, and location of the testing areas are determined to ensure the rationality of the analysis results. The number and mixing ratio of fluid slurry particles and bulk particles within the detection area are calculated and used as an evaluation index for the mixing effect. By comparing the mixing ratio of fluid slurry particles and granular particles in different detection areas, the mixing effect of the mixing pile under multiple working conditions is analyzed.

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