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

Abstract

The invention provides a stirring device multi-body multi-field coupling dynamics modeling simulation method and system, and relates to the technical field of modeling simulation, and the method comprises the steps: obtaining the 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 dynamic modeling on the target stirring device to obtain a stirring device multi-body dynamic model; building a multi-body multi-field coupling simulation environment according to the calibrated information of the materials to be stirred; performing multi-body multi-field coupling simulation on the target stirring device by using the multi-body multi-field coupling simulation environment and the stirring device multi-body dynamic model to obtain simulation data; according to the method, grid division does not need to be carried out on a fluid slurry domain and a discrete particle domain, the calculation efficiency is greatly improved, meanwhile, the stirring effect of the stirring device can be monitored in real time, and meanwhile the stirring effect of the stirring device is analyzed.

Description

Technical Field

[0001] The present disclosure relates to the technical field of modeling and simulation, and in particular to a method and system for modeling and simulating the multi-body and multi-field coupled dynamics of a stirring device. Background Art

[0002] A stirring device disturbs a fluid slurry (such as cement slurry) through rotating blades or other structures, causing it to flow, shear or turbulent, thereby interacting with bulk particles (such as soil) to achieve purposes such as mixing, heat transfer or suspension. It is widely used in scenarios such as chemical synthesis, mineral processing, pharmaceutical granulation, food mixing and environmental sludge treatment. How to optimize the design of the stirring device structure and construction process to achieve a more uniform stirring effect is of great research significance.

[0003] Take cement mixing piles, for example. As a mixing device, cement mixing piles are used to reinforce foundations at construction sites. They use a mixing mechanism to mix the soil and slurry beneath the foundation. Once the slurry and soil have fully reacted and solidified, they form individual piles, strengthening the foundation. Construction process parameters such as the mixing device's structure, rotation, and feed speed directly impact the quality of the cement mixing piles. Therefore, optimizing the structure and process of cement mixing piles is crucial.

[0004] Numerical simulation of cement mixing piles analyzes their mechanical behavior and fluid-solid coupling in reinforcing soft soil foundations, thereby optimizing design parameters and improving mixing efficiency. By modeling and simulating the dynamic phenomena during cement mixing through numerical simulation, we can deeply analyze the performance characteristics of cement mixing piles under different working conditions and the distribution characteristics of the cement slurry and soil mixture during the mixing process. This provides a basis for optimizing the structure and construction process of cement mixing piles. It can also monitor the spraying conditions and mixing effects of the mixing process in real time and efficiently. Simulation results can also be used to improve the structure of mixing equipment and optimize the mixing process.

[0005] The cement mixing process involves three physical properties: the cement mixing pile (i.e., a rigid structure), cement slurry (i.e., slurry), and soil (i.e., discrete particles). This involves fluid-solid coupling numerical simulation. Currently, most such analyses utilize CFD (Computational Fluid Dynamics)-DEM (Discrete Element Method) methods. These methods treat the fluid as a continuous medium and require meshing and solving the computational space. Accurately meshing the fluid is challenging for cement mixing fluid-solid simulations, as they involve fluid motion boundaries or free interfaces. Therefore, using traditional meshing methods presents certain challenges. Obtaining accurate results requires high mesh quality and quantity. A large number of fluid meshes and particles increases computational time, reduces simulation efficiency, and the quality of the meshing can also affect the results.

[0006] Therefore, existing technologies cannot guarantee computational efficiency while accurately dividing the fluid domain grid, which affects the performance and accuracy of numerical simulation of pile mixing of mixing devices including cement mixers. Summary of the Invention

[0007] In order to solve the above problems, the present disclosure proposes a multi-body and multi-field coupled dynamic modeling and simulation method and system for a stirring device, which does not require meshing of the fluid domain. While greatly improving the calculation efficiency, it can also monitor the stirring effect of the mixing pile in real time and analyze the stirring effect of the stirring device at the same time, so as to determine the optimal drill bit structure and construction process.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions: The multi-body multi-field coupled dynamic modeling and simulation method of the stirring device includes: Obtaining structural information, operating condition information, and information about the material to be mixed of a target stirring device, wherein the target stirring device adopts a multi-body structure composed of a plurality of rigid bodies, the operating condition information includes construction process parameters of the stirring device's rotation and movement, and the information about the material to be mixed includes physical property parameters of the fluid slurry and bulk particles; Based on the structural information and working condition information, the multi-body dynamics model of the target mixing device is carried out to obtain the multi-body dynamics model of the mixing device; Build a multi-body multi-field coupled simulation environment based on the calibrated information of the material to be mixed; Using the multi-body multi-field coupling simulation environment and the multi-body dynamics model of the stirring device, a multi-body multi-field coupling simulation is performed on the target stirring device to obtain simulation data; Among them, the construction of the multi-body multi-field coupling simulation environment includes constructing a fluid slurry model and a dispersed particle model. The construction of the fluid slurry model is based on the moving particle semi-implicit 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.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions: The multi-body and multi-field coupled dynamic modeling and simulation system of the stirring device includes: an information acquisition module configured to: acquire structural information, operating condition information, and information of a material to be mixed of a target stirring device, wherein the target stirring device adopts a multi-body structure composed of a plurality of rigid bodies, the operating condition information includes construction process parameters of the stirring device's rotation and movement, and the information of the material to be mixed includes physical property parameters of a fluid slurry and dispersed particles; The model building module is configured to: perform multi-body dynamics modeling on the target stirring device based on the structural information and the operating condition information to obtain a multi-body dynamics model of the stirring device; The environment building module is configured to: build a multi-body multi-field coupled simulation environment based on the calibrated information of the material to be mixed; The coupling simulation module is configured to: perform a multi-body multi-field coupling simulation on a target stirring device using a multi-body multi-field coupling simulation environment and a multi-body dynamics model of the stirring device to obtain simulation data; Among them, the construction of the multi-body multi-field coupling simulation environment includes constructing a fluid slurry model and a dispersed particle model. The construction of the fluid slurry model is based on the moving particle semi-implicit 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.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions: A computer program product includes a computer program, which implements the multi-body multi-field coupled dynamic modeling and simulation method of a stirring device when the computer program is executed by a processor.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions: A non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the multi-body multi-field coupled dynamic modeling and simulation method of the stirring device is implemented.

[0012] According to some embodiments, the present disclosure adopts the following technical solutions: An electronic device comprises: 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 dynamic modeling and simulation method of a stirring device.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention uses the moving particle semi-implicit method to perform fluid modeling for the slurry, divides the fluid into particles for calculation, avoids meshing the fluid domain, and does not require pre-defining meshes in areas that the fluid may reach. It is suitable for simulating the spraying process of a stirring device.

[0014] The present invention performs multi-body dynamics modeling on a stirring device composed of a plurality of rigid bodies, and adds rotation and feed constraints and hinge constraints, which is more in line with the actual working conditions of the stirring device and improves the accuracy of the modeling.

[0015] Considering the interaction of multi-body and multi-field in the multi-body and multi-field coupled dynamic modeling simulation scenario, the present invention provides a calibration sequence and method for the physical property parameters of fluid slurry and dispersed particles, thereby ensuring the accuracy of the parameters used for modeling and thus improving the accuracy of modeling.

[0016] The present invention provides a method for evaluating the stirring effect of a stirring device, which uses simulation results to calculate the mixing ratio of bulk particles and slurry particles, and evaluates the stirring effect based on the mixing ratio, thereby improving the accuracy of the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which constitute a part of the present disclosure, are used to provide a further understanding of the present disclosure. The exemplary embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation to the present disclosure.

[0018] Figure 1 This is a flow chart of the method of Example 1. Figure 2 This is the structural diagram of the cement mixing pile in Example 1. Figure 3 Schematic diagram of the cement slurry static drop experiment results in Example 1.

[0019] Figure 4 Schematic diagram of the cement slurry sliding test results of Example 1.

[0020] Figure 5 Schematic diagram of cement slurry sliding simulation calibration in Example 1.

[0021] Figure 6 Schematic diagram of the soil accumulation angle experimental results of Example 1.

[0022] Figure 7 Schematic diagram of soil accumulation angle simulation calibration in Example 1.

[0023] Figure 8 This is the calibration flow chart of Example 1.

[0024] Figure 9 Schematic diagram of the cement mixing pile simulation model of Example 1.

[0025] Figure 10 Schematic diagram of the cement mixing pile simulation results of Example 1.

[0026] Among them, 1: drill rod, 2: drill bit, 3: first stirring blade, 4: first injection port, 5: second injection port, 6: second stirring blade. DETAILED DESCRIPTION

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

[0028] Example 1 In one embodiment of the present disclosure, a multi-body and multi-field coupled dynamic modeling and simulation method for a stirring device is provided. While greatly improving the computational efficiency, it is also possible to monitor the stirring effect of the stirring pile in real time and analyze the stirring effect of the stirring device, thereby determining the optimal drill bit structure and construction process.

[0029] There are many types of mixing devices involving multi-body and multi-field coupling, including cement mixing piles, bio-fermentation tank mixers, food mixers, etc. This embodiment takes cement mixing piles as an example and selects Particleworks and RecurDyn for joint simulation. Particleworks is a computational fluid dynamics software based on MPS, and RecurDyn is a computational multi-body dynamics (MFBD) software that can be collaboratively simulated with the Particleworks particle solver. Of course, those skilled in the art can select the corresponding modeling software according to their own situation and needs, and are not limited to the above examples. Figure 1 Steps shown: Step S1: Obtain structural information, operating condition information, and information about the material to be mixed of the target stirring device, wherein the target stirring device adopts a multi-body structure composed of several rigid bodies, the operating condition information includes the construction process parameters of the rotation and movement of the stirring device, and the information about the material to be mixed includes the physical property parameters of the fluid slurry and the dispersed particles.

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

[0031] Specifically, the cement mixing pile (i.e., the target mixing device) is composed of a drill rod 1, a drill bit 2, a mixing blade, etc. Figure 2 As shown, the cement mixing pile has the motion of rotating along the axis and feeding downward, so a cylindrical pair shown in red is set between the drill rod 1 and the ground, and 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 2.

[0032] Two similar mixing blades are arranged on the drill bit 1: a rigidly connected first mixing blade 3 and a hinged second mixing blade 6. A group of first mixing blades 3 are fixed at the lower end of the drill bit 1, which have a certain inclination angle with the horizontal plane. A first spray port 4 is arranged at the end of the first mixing blade 3 for spraying cement slurry (i.e. slurry). Cutting blades are arranged on both sides of the first spray port 4, and the cutting blades are longer than the spray port 4, which are used to cut soil blocks during the mixing process and create a spraying space for the first spray port 4. Above the first mixing blade 3, a second spray port 5 is arranged on the side wall of the drill bit 1, so that the cement slurry is evenly sprayed in the radial direction of the mixing pile; two groups of upper and lower hinged mixing blades are arranged on the drill bit, and the two groups of hinged mixing blades have a certain interval along the axial direction, and each group consists of two second mixing blades 6, which are arranged at an interval of 180° along the circumferential direction.

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

[0034] Step S2: Based on the structural information and the operating condition information, a multi-body dynamics model is performed on the target stirring device to obtain a multi-body dynamics model of the stirring device. The specific steps are as follows: Step S2-1: Import the three-dimensional geometric model of the target stirring device into the multi-body 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 multi-body dynamics software, according to the connection relationship of each rigid body in the three-dimensional geometric model, the rotation and feed constraints of the cylindrical pair and the hinge constraints of the stirring blade are set to establish the motion constraint relationship of the target stirring device.

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

[0038] A hinge constraint is used between the stirring blade and the drill bit of the stirring device. The stirring blade can rotate around the hinge position and generate a contact relationship with the side wall of the drill bit based on the Hertz contact theory. A contact model between the stirring blade and the drill bit is set to constrain the motion range of the stirring blade.

[0039] The various working conditions of the mixing operation include the screw-in movement speed, rotation speed, and reverse rotation operation stroke and speed. In this embodiment, the drill rod feed speed is 75-100 cm / min, and the rotation speed is 30-60 rpm. Within this range, based on construction requirements, the feed speed and rotation speed combination is selected, and a function equation is used to define the drive of the cylindrical pair rotation and feed speed. 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: Building a multi-body multi-field coupling simulation environment based on the calibrated information of the material to be mixed.

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

[0042] Based on the moving particle semi-implicit method, particle discrete continuum mechanics is used to divide the fluid into particles to simulate the grouting process of the mixing pile. That is, a fluid particle object is constructed to simulate the slurry. Its physical parameters include the intrinsic parameters of the slurry, the slurry-steel contact coefficient, and the slurry-soil contact coefficient. Among them, the intrinsic parameters of the slurry include density, surface tension coefficient, and kinematic viscosity. The slurry-steel contact coefficient includes the slip coefficient and contact angle between the slurry and the steel. The slurry-soil contact coefficient includes the slurry-soil slip coefficient. The calibration method is: First, define the particle diameter of the fluid slurry. 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 slurry and steel (i.e., the multi-body cement mixing pile) were calibrated through the slurry-steel plate sliding test and the slurry-steel plate static drop test, respectively. Finally, the slurry-soil slip coefficient can be obtained through slurry-soil sliding test calibration.

[0043] Specifically, this example calibrates the slurry-steel contact angle and slurry-steel slip coefficient based on slurry-steel sessile drop and slurry-steel sliding experiments. Seven slurry groups with water-cement ratios ranging from 0.6 to 1.2 were prepared. Since slurry temperature changes significantly affect adhesion performance, the prepared slurries were placed in a water bath and heated to 20°C. After heating, the kinematic viscosity and surface tension coefficient of the slurries 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 kinematic viscosity measurement of cement slurry

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

[0046] The cement slurry was subjected to a cement slurry-steel static drop experiment. 1 ml of cement slurry was taken with a dropper and dropped steadily onto the steel plate surface. The contact angle was measured within 50-70 seconds to avoid the influence of droplet diffusion or curing reaction on the measurement results. This was used to calibrate the cement slurry-steel contact angle. Figure 3 Table 3 shows the experimental phenomenon of cement slurry static drop with a water-cement ratio of 0.6. Table 4 shows the experimental results of cement slurry-steel static drop.

[0047] Table 3 Results of sessile drop test of cement slurry

[0048] The cement slurry was subjected to a cement slurry-steel sliding test. 1 ml of cement slurry was taken with a dropper and dropped steadily on a steel plate with an inclination angle of 25°. The maximum distance it could slide was measured to calibrate the cement slurry-steel sliding coefficient. The experimental phenomena were as follows: Figure 4 As shown in Table 4, the results of cement slurry-steel sliding test with different water-cement ratios are shown.

[0049] Table 4 Cement slurry sliding test results

[0050] Based on the cement slurry experimental results, a fluid property object was established, and the same simulation model was built through the cement slurry-steel sliding experimental device for calibration. 7 sets of velocity boundaries were set, corresponding to 7 sets of cement slurries with different water-cement ratios. The velocity boundaries can spray cement slurry particles outward at the set speed to simulate the process of cement slurry dripping from a dropper in the cement slurry-steel sliding experiment. In the model, an inclined plate with an angle of 25° to the horizontal plane was set below the 7 sets of velocity boundaries to simulate the steel plate in the sliding experiment. Cement slurry particles were ejected from the velocity boundaries, and the distance that the cement slurry particles in the model slid on the steel plate was measured. Based on this cement slurry-steel sliding simulation model and experimental results, the cement slurry-steel slip coefficient was calibrated. The calibration results are shown as follows: Figure 5 shown.

[0051] The cement slurry with a water-cement ratio of 0.6 was taken as the research object. According to the calibration results, the property density of the cement slurry with a water-cement ratio of 0.6 was set to 1750 kg / m 3 , the kinematic viscosity is 1.37×10 -4 m 3 / s, and the surface tension coefficient is 0.068N / m. The slip coefficient between it and the bulk soil particles is set to 15, the slip coefficient between it and the stirring device is set to 5, the contact angle is set to 22.28°, and a cement slurry model is established based on the above calibration results. Based on the MPS control equation, the pressure term calculation of the cement slurry particles is set to implicit calculation, and the viscosity calculation method is set to explicit calculation. The surface tension model uses the CSF (Continuum Surface Force, continuous medium surface force) model. Based on the model size and calculation efficiency in this embodiment, the cement slurry particle diameter is set to 6mm.

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

[0054] The physical property parameters of bulk soil particles are used to simulate bulk soil particles. These physical property parameters include the intrinsic parameters of the soil, the bulk soil particle-bulk soil particle contact coefficient, the bulk soil particle-steel contact coefficient, and the cement slurry-bulk soil particle contact coefficient. The intrinsic parameters of bulk soil particles include soil density, Young's modulus, and Poisson's ratio. The bulk soil particle-bulk soil particle contact coefficient includes the adhesion coefficient and the contact force coefficient. The bulk soil particle-steel contact coefficient includes the static friction coefficient and the kinetic friction coefficient. The cement slurry-bulk soil particle contact coefficient includes the cement slurry-soil slip coefficient. The calibration method is: First, the particle diameter of the dispersed particles is defined. The density can be measured by the mass volume method, and the Young's modulus and Poisson's ratio can be measured by shear tests. Then, the soil bulk particle-soil bulk particle adhesion coefficient and contact force coefficient can be obtained through soil accumulation angle experimental calibration; Secondly, the static friction coefficient and dynamic friction coefficient of soil bulk particles-steel can be obtained by calibration of soil-steel sliding test. Finally, the slip coefficient of cement slurry-soil bulk particles can be obtained by calibrating the cement slurry-soil sliding experiment.

[0055] Specifically, this embodiment calibrates the adhesion coefficient and contact force coefficient of soil bulk particles-soil bulk particles based on the soil stacking angle experiment. The soil is placed in a constant temperature 105 degrees Celsius oven and dried for 8 hours. Then, a soil sample with a moisture content of 25% is prepared. The soil stacking angle experiment is performed on the sample to calibrate the liquid bridge force and van der Waals force coefficient between the particles. In order to improve the measurement accuracy, it is usually necessary to repeat the stacking angle experiment multiple times and take the average value. The stacking angle results measured in 7 groups of experiments were 39.01°, 37.55°, 35.24°, 37.80°, 39.62°, 35.53° and 37.30°, respectively. The average stacking angle was calculated to be 37.44°. The experimental phenomena are as follows: Figure 6 shown.

[0056] Based on the soil accumulation angle experiment, the particle property object is established, and the same simulation model is built through the accumulation angle experimental device for calibration. The calibration results are as follows: Figure 7 As shown. In the particle properties, based on the calibrated soil bulk particle intrinsic parameters, soil bulk particle-soil bulk particle contact parameters, soil bulk particle-steel contact parameters, cement slurry-soil bulk particle contact parameters, and Hertz contact model, a soil bulk particle model is constructed, taking into account the contact effect between particles. At the same time, in order to consider the inter-particle force between the soil bulk particles, the van der Waals force and liquid bridge force model are used to establish the adhesion effect between the soil bulk particles, and a soil bulk particle model is established. The density is set to 2660kg / m 3 The Young's modulus is 0.03 GPa, the Poisson's ratio is 0.36, the surface roughness is set to 2 mm, the inter-particle restitution coefficient is set to 0.5, the elastic modulus is 500, the shape factor is 2, the contact angle parameter in the inter-particle liquid bridge force is 30°, the dimensionless volume is set to 2, and the adjustment coefficient in the van der Waals force is set to 1000. The diameters of the soil bulk particles are set to 8, 9, and 10 mm, accounting for 30%, 40%, and 30%, respectively.

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

[0058] Step S4: using the multi-body multi-field coupling simulation environment and the multi-body dynamics model of the stirring device, a multi-body multi-field coupling simulation is performed 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 injection port of the agitator to spray cement slurry particles. The maximum agitation diameter of the agitator is 800 mm. To generate bulk soil particles and avoid wall effects during mixing, place a cylindrical container with an inner diameter of 1200 mm below the agitator. The model is as follows: Figure 9 shown.

[0060] After the parameters of cement slurry and soil bulk particles are calibrated, preprocessing is performed based on the current model to generate an initial particle swarm. The co-simulation function with Particleworks is enabled in RecurDyn, and the simulation time is set to 75s and the step size is 0.005s. The following results are obtained: Figure 10 The simulation results described.

[0061] This embodiment carries out multi-body multi-field coupled dynamic simulation of the stirring device, and the specific steps are as follows: Set the physical properties of the mixing device wall model and set a pressure boundary at the injection port to spray fluid particles and simulate the process of the mixing device spraying cement slurry. According to actual project requirements, set the multi-operation parameters of the mixing device, including different rotation and feed speeds, and shotcrete pressure; The dynamic simulation of the mixing device under multiple working conditions is carried out. By setting the rotation and feed drive of the mixing device, as well as the shotcrete pressure on the pressure boundary, the multi-physics field dynamic simulation of the mixing process is controlled to obtain the simulation results of the mixing pile.

[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 bulk soil particles. By setting several detection areas on a mixed pile, the probe function can be used to calculate the number of cement slurry particles and bulk soil particles within the set areas and the proportion of the mixture. By comparing the proportion of cement slurry particles and bulk soil particles within several detection areas and the proportion of the two between different areas, the mixing effect of the mixing pile can be analyzed and used as a basis for evaluating the mixing effect of the mixing pile. The mixing effect of one example is shown in Table 5. Among them, the proportion of bulk soil particles and cement slurry particles in areas 1 and 5 is quite different. The proportion of cement slurry particles in area 1 is 53.28%, which is significantly lower than the 73.21% in area 5. This indicates that the distribution of mixing particles between areas 1 and 5 is uneven.

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

[0065] Example 2 In one embodiment of the present disclosure, a multi-body multi-field coupled dynamic modeling and simulation system for a stirring device is provided, comprising: an information acquisition module configured to: acquire structural information, operating condition information, and information of a material to be mixed of a target stirring device, wherein the target stirring device adopts a multi-body structure composed of a plurality of rigid bodies, the operating condition information includes construction process parameters of the stirring device's rotation and movement, and the information of the material to be mixed includes physical property parameters of a fluid slurry and dispersed particles; The model building module is configured to: perform multi-body dynamics modeling on the target stirring device based on the structural information and the operating condition information to obtain a multi-body dynamics model of the stirring device; The environment building module is configured to: build a multi-body multi-field coupled simulation environment based on the calibrated information of the material to be mixed; The coupling simulation module is configured to: perform a multi-body multi-field coupling simulation on a target stirring device using a multi-body multi-field coupling simulation environment and a multi-body dynamics model of the stirring device to obtain simulation data; Among them, the construction of the multi-body multi-field coupling simulation environment includes constructing a fluid slurry model and a dispersed particle model. The construction of the fluid slurry model is based on the moving particle semi-implicit 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.

[0066] Example 3 In one embodiment of the present disclosure, a computer program product is provided, including a computer program, which, when executed by a processor, implements the multi-body multi-field coupled dynamic modeling and simulation method for a stirring device.

[0067] Example 4 In one embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, which is used to store computer instructions. When the computer instructions are executed by a processor, the multi-body multi-field coupled dynamic modeling and simulation method of the stirring device is implemented.

[0068] Example 5 In one embodiment of the present disclosure, an electronic device is provided, comprising: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes the multi-body multi-field coupled dynamic modeling and simulation method of the stirring device.

[0069] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0070] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0071] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Those skilled in the art should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A multi-body multi-field coupled dynamic modeling and simulation method for a stirring device, characterized in that: include: Obtaining structural information, operating condition information, and information about the material to be mixed of a target stirring device, wherein the target stirring device adopts a multi-body structure composed of a plurality of rigid bodies, the operating condition information includes construction process parameters of the stirring device's rotation and movement, and the information about the material to be mixed includes physical property parameters of the fluid slurry and bulk particles; Based on the structural information and working condition information, the multi-body dynamics model of the target mixing device is carried out to obtain the multi-body dynamics model of the mixing device; Build a multi-body multi-field coupled simulation environment based on the calibrated information of the material to be mixed; Using the multi-body multi-field coupling simulation environment and the multi-body dynamics model of the stirring device, a multi-body multi-field coupling simulation is performed on the target stirring device to obtain simulation data; Among them, the construction of the multi-body multi-field coupling simulation environment includes constructing a fluid slurry model and a dispersed particle model. The construction of the fluid slurry model is based on the moving particle semi-implicit 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.

2. The multi-body multi-field coupled dynamics modeling and simulation method for a stirring device according to claim 1, characterized in that: The structural information is represented by a three-dimensional geometric model of the target stirring device; Among them, the rigid bodies in the three-dimensional geometric model include a drill rod, a drill bit, a mixing blade, and a spray port. 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 mixing blade is set on the drill bit, and the spray port is arranged on the drill bit.

3. The multi-body multi-field coupled dynamics modeling and simulation method for a stirring device according to claim 2, characterized in that: The multi-body dynamics modeling includes the following specific steps: Import the three-dimensional geometric model of the target stirring device into the multi-body dynamics software; In the multi-body dynamics software, based on the connection relationship between each rigid body in the three-dimensional geometric model, the relationship between the drill rod and the earth is defined by a cylindrical pair, and the rotation and movement drive constraints of the cylindrical pair are defined with the help of function expressions to simulate the rotation and movement construction process of the mixing device; the rotation pair is used to define the articulation constraint of the mixing blade and the drill bit, and the motion constraint relationship of the target mixing device is established.

4. The multi-body multi-field coupled dynamic modeling and simulation method for a stirring device according to claim 1, characterized in that: The physical property parameters of the fluid slurry include intrinsic parameters of the fluid slurry, a fluid slurry-multi-body structure contact coefficient, and a fluid slurry-dispersed particle contact coefficient; Among them, the intrinsic parameters of the fluid slurry include density, surface tension coefficient, and kinematic viscosity; the fluid slurry-multi-body structure contact coefficient includes the slip coefficient and contact angle between the fluid slurry and the multi-body structure; and the fluid slurry-dispersed particle contact coefficient includes the fluid slurry-dispersed particle slip coefficient.

5. The multi-body multi-field coupled dynamic modeling and simulation method for a stirring device according to claim 1, characterized in that: The calibration method of the physical property parameters of the fluid slurry is: First, the particle diameter of the fluid slurry is defined, and the density, surface tension coefficient, and kinematic viscosity of the fluid slurry are measured; Then, the slip coefficient and contact angle between the fluid slurry and the multi-body structure are calibrated through the fluid slurry-multi-body structure sliding test and the fluid slurry-multi-body structure sessile drop test, respectively. Finally, the fluid slurry-dispersed particle slip coefficient is obtained through the fluid slurry-dispersed particle sliding experiment calibration.

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

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

8. The multi-body multi-field coupled dynamic modeling and simulation method for a stirring device according to claim 7, characterized in that: The calibration method of the physical property parameters of the dispersed particles is: First, the particle diameter of the dispersed particles is defined, and the particle density, Young's modulus, and Poisson's ratio are measured; Then, the particle-particle adhesion coefficient and contact force coefficient are obtained by calibrating the particle stacking angle experiment. Secondly, the static friction coefficient and kinetic friction coefficient of the bulk particle-multibody structure are obtained by calibrating the bulk particle-multibody structure sliding experiment; Finally, the fluid slurry-dispersed particle slip coefficient is obtained by calibration of the fluid slurry-dispersed particle sliding experiment.

9. The multi-body multi-field coupled dynamic modeling and simulation method for a stirring device according to claim 1, characterized in that: The construction of the dispersed particle model is based on the calibrated intrinsic parameters of the dispersed particles, the dispersed particle-dispersed particle contact coefficient, the dispersed particle-multi-body structure contact coefficient, and the fluid slurry-dispersed particle contact coefficient. Based on the Hertz contact model, the particle domain is divided into particles, and discrete particles are used to solve the contact force between particles. Based on the van der Waals force and liquid bridge force model, an adhesion force model between dispersed particles is established.

10. The multi-body multi-field coupled dynamics modeling and simulation method for a stirring device according to claim 1, characterized in that: It also includes analyzing the simulation data and evaluating the stirring effect of the target stirring device, specifically: Set up several detection areas within the mixing range of the mixing pile, determine the shape, size and position of the detection areas, and ensure the rationality of the analysis results; Calculate the number of fluid slurry particles and bulk particles in the detection area and the mixing ratio, which is used as the evaluation index of the stirring effect; The mixing ratios of fluid slurry particles and bulk particles in the detection areas at different locations are compared to analyze the mixing effect of mixing piles under multiple working conditions.

Images