Multi-scale particle flow calculation method

Abstract

The invention relates to the field of multiphase flow numerical simulation, and discloses a multi-scale particle flow calculation method which comprises the following steps: acquiring position coordinates, speed and volume of particles in a current time step; positioning a grid where the particles are located by combining grid distribution in Fluent software, and obtaining a volume value of the grid to calculate a grid particle size ratio at the current moment; calculating grid porosity and background flow field information by adopting different methods according to whether the grid particle size ratio is greater than 3; the porosity, the background flow field information, the particle speed and the particle volume are substituted into a drag force model for calculation, and drag force borne by the particles is obtained; inputting the drag force into EDEM software to iteratively calculate the motion of the particles to obtain the motion state of the particles in the next time step; and adding the negative value of the drag force into a momentum equation of Fluent software in a source item form to iteratively calculate the motion of the fluid to obtain the speed and pressure information of all grids in the next time step. And accurate numerical simulation of the multi-scale particles is realized.

Description

Technical Field

[0001] The present application relates to the field of multiphase flow numerical simulation, and in particular to a multi-scale particle flow calculation method. Background Art

[0002] Particle-fluid two-phase flow describes a complex physical system formed by the interaction between particles and fluids. It includes particle systems, fluid systems, and the exchange of momentum and energy between particles and fluids. It is an important branch of multiphase flow systems and is widely present in natural phenomena and industrial production. With the rapid development of modern computer technology, numerical simulation has become an important method for studying particle-fluid two-phase flow. The study of numerical simulation methods helps to understand the motion laws of particle matter itself and the mechanism of fluid-solid coupling between particles and fluids.

[0003] The unresolved CFD-DEM model is the most widely used computational model for describing particle-fluid two-phase flow. This model does not require an accurate description of the particle boundary and the flow field around the par- ticles . It calculates the force of the fluid on the particles through various empirical formulas, and the reaction force of the particles on the fluid acts on the fluid unit through the local averaging method. In order to better capture the velocity, porosity and other information of the background fluid around the particles, the unresolved CFD-DEM model requires that the particle grid size ratio is greater than 3. When the grid size ratio is less than 3, the calculation accuracy of the unresolved CFD-DEM model is greatly reduced. Therefore, this model is mostly used for the simulation of large-scale small-scale particles. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a multi-scale particle flow calculation method to solve the limitation problem that the traditional unresolved CFD-DEM method can only be used to calculate small-scale particles with a grid particle size ratio of more than 3.

[0005] According to an embodiment of the present application, a multi-scale particle flow calculation method is provided, comprising: Get the position coordinates, velocity and volume of the particles in the current time step from the EDEM software; Obtain the position distribution information of all grids in the Fluent software, and locate the grid where the center of the particle is located according to the position coordinates of the particle, obtain the volume value of the grid, and calculate the grid particle size ratio at the current moment with the volume of the particle; The porosity of the grid is calculated by two different methods when the grid particle size ratio is greater than 3 and less than or equal to 3; When the grid particle size ratio is greater than 3 and less than or equal to 3, two different methods are used to calculate the background flow field information; The porosity, background flow field information, particle velocity and particle volume are brought into the drag model for calculation to obtain the drag force on the particle; The drag force is input into the EDEM software to iteratively calculate the movement of the particles, and obtain the position and velocity information of the particles in the next time step; The negative value of the drag force is added to the momentum equation of the Fluent software as a source term to iteratively calculate the movement of the fluid and obtain the velocity and pressure information of all grids in the next time step.

[0006] Optionally, the grid particle size ratio is ,in is the grid volume where the particle center is located, is the particle volume.

[0007] Optionally, the mesh porosity is calculated by two different methods when the mesh particle size ratio is greater than 3 and less than or equal to 3, respectively, including: According to the grid particle size ratio, the solid content of the grid within the particle action range is calculated, wherein when the grid particle size ratio is greater than 3, the particle volume is dispersed in a plurality of evenly distributed feature points, each feature point equally contains the volume of the particle portion, and when the feature point is located in a certain grid, it is considered that the part of the volume of the particle contained in the feature point belongs to the grid; when the grid particle size ratio is less than or equal to 3, the particle volume is weightedly distributed in the surrounding grids by using a statistical kernel function; After traversing all particles, the porosity within the grid is calculated by: In the formula is the solid content of the i-th particle acting on the x-th grid in the fluid domain.

[0008] Optionally, the grid particle size ratio is greater than 3 and less than or equal to 3, respectively, using two different methods to calculate the background flow field information, including: When the grid-particle size ratio is greater than 3, the flow field information of the grid where the particle center is located is used as the background flow field information of the particle; When the grid-particle diameter ratio is less than or equal to 3, the flow field information of the grid where six characteristic points evenly distributed on the particle surface are located is extracted and averaged to serve as the background flow field information where the particle is located.

[0009] The technical solution provided by the embodiments of the present application may have the following beneficial effects: It can be seen from the above embodiments that the present application adopts different methods to calculate the porosity and background flow field information required in the unresolved CFD-DEM particle flow field calculation model for different grid particle size ratios, while taking into account the time-varying nature of the grid particle size ratio, updating the grid particle size ratio at each time step, thereby improving the calculation accuracy, solving the limitation problem that the traditional unresolved CFD-DEM method is only suitable for calculating small-scale particles, and realizing the accurate calculation of multi-scale particles by the unresolved CFD-DEM method.

[0010] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a flow chart of a method for calculating multi-scale particle porosity according to an exemplary embodiment.

[0012] Figure 2 is a schematic diagram of a solid content calculation method according to an exemplary embodiment, wherein a is a DPVM method and b is an SKM method.

[0013] Figure 3 It is a schematic diagram of a method for calculating background flow field information according to an exemplary embodiment.

[0014] Figure 4 It is a schematic diagram of a large-scale particle computing verification model according to an exemplary embodiment.

[0015] Figure 5 1 is a comparison of large-scale particle calculation verification results shown according to an exemplary embodiment.

[0016] Figure 6 is a schematic diagram of a multi-scale particle computing verification model according to an exemplary embodiment.

[0017] Figure 7 1 is a comparison of multi-scale particle calculation verification results shown according to an exemplary embodiment. DETAILED DESCRIPTION

[0018] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0019] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0020] Figure 1 is a flow chart of a multi-scale particle flow calculation method according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps: S1: Get the position coordinates, velocity and volume of the particle in the current time step from the EDEM software.

[0021] Specifically, the API development environment provided by the EDEM software is used to write and run scripts to obtain particle position coordinates, velocity, and volume. Through custom scripts, key information can be flexibly obtained, dynamic information of particles can be systematically obtained, and accurate data of particles can be provided.

[0022] S2: Obtain the position distribution information of all grids in the Fluent software, and locate the grid where the center of the particle is located according to the position coordinates of the particle, obtain the volume value of the grid, and calculate the grid particle size ratio at the current moment with the volume of the particle; Specifically, the user-defined function (UDF) function provided by Fluent software is used to extract grid information, including grid position (node ​​coordinates and grid center coordinates) and volume, and then the nearest grid center is found according to the particle position to achieve the matching of the grid and particle position.

[0023] Calculate the mesh-particle size ratio based on the matched mesh and particle volumes .

[0024] In the formula is the grid volume where the particle center is located, is the particle volume.

[0025] S3: using two different methods to calculate the porosity of the grid when the grid particle size ratio is greater than 3 and less than or equal to 3; Specifically, Figure 2 is a schematic diagram of a solid content calculation method according to an exemplary embodiment. When the particle size is smaller than 3, the DPVM method is used, that is, the particle volume is dispersed in multiple evenly distributed feature points, each feature point equally contains the volume of the particle part. When the feature point is located in a certain grid, it is considered that the part of the volume of the particle contained in the feature point belongs to the fluid grid; when the grid particle size ratio is calculated, For large-scale particles with a particle size less than 3, the SKM method is used, that is, the particle volume is weightedly distributed in the surrounding grid through a statistical kernel function.

[0026] After traversing all particles, the porosity in the grid Calculated by the following formula: In the formula is the solid content of the i-th particle acting on the x-th grid in the fluid domain.

[0027] By analyzing the grid size ratio to determine the relative size of the particles and using different porosity calculation methods in a targeted manner, accurate porosity values ​​can be obtained for particles of different sizes, thereby improving the accuracy of subsequent drag calculations.

[0028] S4: using two different methods to calculate the background flow field information when the grid particle size ratio is greater than 3 and less than or equal to 3; Specifically, when calculating the grid size ratio For small-scale particles larger than 3, the flow field information of the grid where the particle center is located is used as the background flow field information of the particle; when calculating the grid particle size ratio When the particle size is smaller than 3, Figure 3 It is a schematic diagram of a method for calculating background flow field information according to an exemplary embodiment, which extracts the flow field information of the grid where six characteristic points evenly distributed on the surface of a particle are located and averages them as the background flow field information where the particle is located.

[0029] The relative scale of the particles is determined by analyzing the grid particle size ratio, and different background flow field information calculation methods are used for particles of different scales. This greatly saves computing resources and improves computing efficiency while ensuring the calculation accuracy.

[0030] S5: bringing the porosity, background flow field information, particle velocity and particle volume into the drag model for calculation to obtain the drag force on the particle; Specifically, the Gidaspow drag model is used. The Gidaspow drag model calculates the drag experienced by particles according to the Gidaspow correlation coefficient, taking into account the porosity, background flow field and particle dynamics, and enhancing the physical significance of the drag calculation.

[0031] S6: input the drag force into the EDEM software to iteratively calculate the movement of the particles, and obtain the position and velocity information of the particles in the next time step; Specifically, EDEM software is based on the particle motion equation, taking into account the collision forces between particles and particles and between particles and walls, dynamically coupling drag and particle motion, improving the physical accuracy of the calculation, and achieving efficient dynamic simulation of particles.

[0032] S7: Add the negative value of the drag force as a source term to the momentum equation of the Fluent software to iteratively calculate the movement of the fluid and obtain the velocity and pressure information of all grids in the next time step.

[0033] Specifically, the calculated drag source term is dynamically added to the momentum equation of the fluid through the UDF function. At each time step, Fluent will guide the momentum change of the fluid through the source term and update the velocity and pressure field of the fluid according to the source term. The dynamic update of the source term of the momentum equation can reflect the coupling process of particles and fluid in real time and enhance the simulation accuracy.

[0034] It can be seen from the above embodiments that the present invention solves the particle-fluid two-phase flow based on the unresolved CFD-DEM model. When solving large-scale particles in the model, the original porosity and background flow field information calculation method cannot fully describe the actual working conditions, resulting in a significant reduction in the calculation accuracy of the model. A modified porosity and background flow field information calculation method is proposed. The multi-scale particle calculation method proposed in the present invention can not only accurately simulate the movement of small-scale particles in the fluid, but also accurately simulate the movement of large-scale particles, thereby realizing accurate numerical simulation of multi-scale particles.

[0035] In order to verify the effectiveness of the multi-scale particle calculation method proposed in the present invention, the calculation of large-scale particles is first verified by comparing it with a single particle sedimentation experiment. Figure 4 It is a schematic diagram of a single particle sedimentation model according to an exemplary embodiment, the particle is a nylon ball, the medium is silicone oil, the container cross-section is 100mm*100mm, the liquid level is 160mm, and the particle falls freely from a height of 120mm. Figure 5 It is a comparison diagram of simulation and experimental results using different methods according to an exemplary embodiment. It can be seen from the figure that before the calculation method proposed in the present invention is adopted, the particle velocity change results simulated using the unanalyzed CFD-DEM method have a large error with the experimental results. After using the porosity and background flow field information calculation method proposed in the present invention, the numerical simulation results are very close to the experimental results, which proves the effectiveness of the present invention for large-scale particle calculation.

[0036] Then, the calculation of multi-scale particles was verified by comparing the binary particle fluidized bed experiment. Figure 6 : is a schematic diagram of a fluidized bed model according to an exemplary embodiment. The pipe diameter is 50 mm, the medium is water, and particles of two different particle sizes, 5 mm and 8 mm, are mixed. Figure 7 A comparison of verification results of multi-scale particle calculation is shown according to an exemplary embodiment. From the particles in the figure, it can be seen that at different inlet velocities, the inlet and outlet pressure differences measured experimentally are very close to the numerical simulation results, which proves the effectiveness of the present invention for multi-scale particle calculation.

[0037] Those skilled in the art will readily appreciate other embodiments of the present application after considering the description and practicing the contents disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The description and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0038] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A multi-scale particle flow calculation method, characterized in that: include: Get the position coordinates, velocity and volume of the particles in the current time step from the EDEM software; Obtain the position distribution information of all grids in the Fluent software, and locate the grid where the center of the particle is located according to the position coordinates of the particle, obtain the volume value of the grid, and calculate the grid particle size ratio at the current moment with the volume of the particle; The porosity of the grid is calculated by two different methods when the grid particle size ratio is greater than 3 and less than or equal to 3; When the grid particle size ratio is greater than 3 and less than or equal to 3, two different methods are used to calculate the background flow field information; The porosity, background flow field information, particle velocity and particle volume are brought into the drag model for calculation to obtain the drag force on the particle; The drag force is input into the EDEM software to iteratively calculate the movement of the particles, and obtain the position and velocity information of the particles in the next time step; The negative value of the drag force is added to the momentum equation of the Fluent software as a source term to iteratively calculate the movement of the fluid and obtain the velocity and pressure information of all grids in the next time step.

2. A multi-scale particle flow calculation method according to claim 1, characterized in that: The grid particle size ratio is ,in is the grid volume where the particle center is located, is the particle volume.

3. A multi-scale particle flow calculation method according to claim 1, characterized in that: The porosity of the grid is calculated by two different methods when the grid particle size ratio is greater than 3 and less than or equal to 3, respectively, including: According to the grid particle size ratio, the solid content of the grid within the particle action range is calculated, wherein when the grid particle size ratio is greater than 3, the particle volume is dispersed in a plurality of evenly distributed feature points, each feature point equally contains the volume of the particle portion, and when the feature point is located in a certain grid, it is considered that the part of the volume of the particle contained in the feature point belongs to the grid; when the grid particle size ratio is less than or equal to 3, the particle volume is weightedly distributed in the surrounding grids by using a statistical kernel function; After traversing all particles, the porosity within the grid is calculated by: In the formula is the solid content of the i-th particle acting on the x-th grid in the fluid domain.

4. A multi-scale particle flow calculation method according to claim 1, characterized in that: The background flow field information is calculated by two different methods when the grid particle size ratio is greater than 3 and less than or equal to 3, including: When the grid-particle size ratio is greater than 3, the flow field information of the grid where the particle center is located is used as the background flow field information of the particle; When the grid-particle diameter ratio is less than or equal to 3, the flow field information of the grid where six characteristic points evenly distributed on the particle surface are located is extracted and averaged to serve as the background flow field information where the particle is located.

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