An improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing method and system

Abstract

The application discloses an arbitrary shape particle CFD-DEM processing method and system based on improved immersed boundary and directed distance field, which creates a fluid model corresponding to an arbitrary shape particle, generates first data corresponding to the fluid model, constructs a corresponding first model in real time according to the first data and in combination with a directed distance field or an improved immersed boundary, processes the arbitrary shape particle in real time through the first model, generates particle behavior data corresponding to the arbitrary shape particle and in a multiphase particle flow, and a corresponding system and platform can accurately accommodate various shape characteristics of particles and provide a general particle modeling method with optimal calculation efficiency. That is, the scheme has good precision and stability, and has potential to better simulate the behavior of particles in a complex fluid environment in effectively calculating and simulating a multiphase particle flow involving arbitrary shape particles.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of particle analysis processing, and particularly relates to an arbitrary shape particle CFD-DEM processing method and system based on improved immersed boundary and directed distance field. BACKGROUND

[0002] Fluid-particle systems are common in nature and are of great importance to engineering practice. They can exist in various forms, such as geological fluids like debris and mud flows, internal erosion of dams, wave-induced coral rubble breakage and transport, and particle mixing and reactions in fluidized beds, etc. The CFD-DEM coupling method is one of the main methods for numerical simulation of granular materials.

[0003] It is well known that in fluid-particle systems, particles often have non-spherical characteristics, and the irregularity of particles has a significant impact on the macroscopic properties of granular media, such as packing density, stiffness, and strength. Introducing arbitrary shape particles in fully analytical CFD-DEM based on IBM is currently a frontier of research at home and abroad. There are mainly three methods for this field of research. The first is to introduce spherical polyhedral technology or polygon technology, etc. The second is to integrate DEM based on images with CFD for coupled modeling. The above two methods require large memory or high computational cost when dealing with irregular shape particles in DEM, which limits their application in large particle systems. The third is the multi-sphere particle method. However, the multi-sphere particle method has the disadvantages of low computational efficiency and unrealistic contact parameters.

[0004] Therefore, in view of the technical problems and defects of requiring large memory or high computational cost, and having low computational efficiency and unrealistic contact parameters, there is an urgent need to design and develop an arbitrary shape particle CFD-DEM processing method and system based on improved immersed boundary and directed distance field. SUMMARY

[0005] To overcome the deficiencies and difficulties of the prior art, the purpose of the present application is to provide an arbitrary shape particle CFD-DEM processing method, system and platform based on improved immersed boundary and directed distance field, which can accurately accommodate various shape characteristics of particles and provide a general particle modeling method with optimal computational efficiency.

[0006] The first purpose of the present application is to provide an arbitrary shape particle CFD-DEM processing method based on improved immersed boundary and directed distance field. The second purpose of the present application is to provide an arbitrary shape particle CFD-DEM processing system based on improved immersed boundary and directed distance field. The third purpose of the present application is to provide an arbitrary shape particle CFD-DEM processing platform based on improved immersed boundary and directed distance field.

[0007] A first object of the present application is achieved by the method comprising the steps of:

[0008] creating a fluid model corresponding to the arbitrary shape particle, and generating first data corresponding to the fluid model; wherein the first data is the interface state data between the multiphase fluid and the two phases in the fluid model;

[0009] constructing a corresponding first model in real time according to the first data and in combination with a directed distance field or an improved immersed boundary; wherein the first model is an SDF-CFD-DEM framework model;

[0010] processing the arbitrary shape particle in real time through the first model, and generating particle behavior data corresponding to the arbitrary shape particle and in the multiphase particle flow.

[0011] Further, the creating a fluid model corresponding to the arbitrary shape particle, and generating first data corresponding to the fluid model further comprises:

[0012] obtaining second data between irregular particles, and generating third data corresponding to the second data in real time in combination with a directed distance field; wherein the second data is surface state data of the irregular particles; and the third data is irregular particle discrete processing data based on a directed distance field contact algorithm;

[0013] obtaining fourth data between the fluid and the particles, and generating fifth data corresponding to the fourth data in real time in combination with an improved immersed boundary; wherein the fourth data is interaction data between the fluid and the particles; and the fifth data is data processed by the improved immersed boundary method.

[0014] Further, the creating a fluid model corresponding to the arbitrary shape particle, and generating first data corresponding to the fluid model further comprises:

[0015] obtaining sixth data between the arbitrary shape particles in real time, and generating contact force data corresponding to the arbitrary shape particles based on SDF-DEM processing; wherein the sixth data is coordinate data of the particles, contact data between the particles, and directional representation data of the particles; and the contact force data is normal force data and normal torque data between the particles;

[0016] respectively obtaining fluid density data and fluid velocity data corresponding to the fluid model, and respectively performing correction processing on the fluid density data and the fluid velocity;

[0017] obtaining interaction data between the fluid and the particles, and generating corresponding force data applied by the fluid to the particles;

[0018] Obtaining SDF value data corresponding to each unit node of the fluid model, and processing the corresponding grid unit and node classification in real time according to the SDF value data and in combination with the grid node symbol data.

[0019] Further, the calculation formula of the force data is:

[0020]

[0021] Wherein, F f is the force data; is the density-weighted solid score; the summation symbol represents the summation of all grids overlapped by one particle; x i is the grid center; x p is the mass center; sigma is the fluid stress; f IB represents the interaction force based on the IBM of the solid particles; V c is the grid volume.

[0022] Further, the real-time CFD-DEM processing of the arbitrary-shaped particles according to the first model further comprises:

[0023] CFD and DEM are initialized respectively, and the seventh data corresponding to the particles is processed synchronously; wherein, the seventh data is particle geometric data, particle position data and particle velocity data;

[0024] The seventh data is mapped to the linked list of the CFD grid nodes, and the solid score field is updated, and the corresponding fluid density field is corrected;

[0025] Fluid force data corresponding to the fluid model and acting on the particles is generated, and the corresponding particles are processed in real time by DEM according to the fluid force data;

[0026] The VOF of the fluid is updated, and the corresponding phase interface is reconstructed; and the velocity prediction data corresponding to the fluid is generated in real time according to the data of the previous time step;

[0027] In combination with the obtained fluid force data, the velocity data and the pressure data corresponding to the fluid are updated and generated.

[0028] The second object of the application is achieved in that the system is applied to an arbitrary-shaped particle CFD-DEM processing method based on improved immersed boundary and directed distance field, and the system comprises:

[0029] A first data generating unit is configured to create a fluid model corresponding to the arbitrary-shaped particle and generate first data corresponding to the fluid model, wherein the first data is interface state data between the multiphase fluid and the two phases in the fluid model.

[0030] A model constructing unit is configured to construct a first model in real time according to the first data and in combination with a distance field or an improved immersed boundary, wherein the first model is an SDF-CFD-DEM framework model.

[0031] A second data generating unit is configured to process the arbitrary-shaped particle in real time by the first model and generate particle behavior data corresponding to the arbitrary-shaped particle and in the multiphase particle flow.

[0032] Further, the first data generating unit further comprises:

[0033] A first data generating module is configured to obtain second data between irregular particles and generate third data corresponding to the second data in real time in combination with a distance field, wherein the second data is surface state data of the irregular particles, and the third data is irregular particle discrete processing data based on a distance field contact algorithm.

[0034] A second data generating module is configured to obtain fourth data between the fluid and the particles and generate fifth data corresponding to the fourth data in real time in combination with an improved immersed boundary, wherein the fourth data is interaction data between the fluid and the particles, and the fifth data is data processed by the improved immersed boundary method.

[0035] The second data generating unit further comprises:

[0036] A first data processing module is configured to initialize CFD and DEM respectively and process seventh data corresponding to the particles synchronously, wherein the seventh data is particle geometry data, particle position data and particle velocity data.

[0037] A second data processing module is configured to map the seventh data to a linked list of CFD grid nodes, update a solid fraction field, and correct fluid density field corresponding to the particles.

[0038] A third data generating module is configured to generate fluid force data corresponding to the fluid model and acting on the particles, and process the particles in real time in combination with DEM according to the fluid force data.

[0039] A fourth data generating module is configured to update VOF of the fluid and reconstruct a corresponding phase interface, and generate velocity prediction data corresponding to the fluid in real time according to data of a previous time step.

[0040] The fifth data generation module is configured to update and generate velocity data and pressure data corresponding to the fluid in combination with the acquired fluid force data.

[0041] Further, the first data generation unit further comprises:

[0042] The sixth data generation module is configured to acquire sixth data between arbitrary shape particles in real time, and generate contact force data corresponding to the arbitrary shape particles based on SDF-DEM processing; wherein the sixth data is coordinate data of the particles, contact data between the particles and direction representation data of the particles; and the contact force data is normal force data and normal torque data between the particles.

[0043] The third data processing module is configured to acquire fluid density data and fluid velocity data corresponding to the fluid model respectively, and perform correction processing on the fluid density data and the fluid velocity respectively.

[0044] The seventh data generation module is configured to acquire interaction data between the fluid and the particles, and generate corresponding force data applied by the fluid to the particles.

[0045] The fourth data processing module is configured to acquire SDF value data corresponding to the fluid model and each unit node, and process corresponding grid units and node classification in real time according to the SDF value data and in combination with grid node symbol data.

[0046] Further, the calculation formula of the force data is:

[0047]

[0048] wherein F f is the force data; is the density weighted solid fraction; the summation symbol represents the sum of all grids overlapped by one particle; x i is the grid center; x p is the mass center; σ is the fluid stress; f IB represents the interaction force of the solid particles based on IBM; V c is the grid volume.

[0049] The third object of the present application is achieved by comprising a processor, a memory and an improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing platform control program; wherein the improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing platform control program is executed by the processor, the improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing platform control program is stored in the memory, and the improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing platform control program implements the improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing method.

[0050] The present application creates a fluid model corresponding to an arbitrary shape particle, generates first data corresponding to the fluid model, wherein the first data is the interface state data between the multiphase fluid and the two phases in the fluid model, constructs a corresponding first model in real time according to the first data and in combination with a directed distance field or an improved immersed boundary, wherein the first model is an SDF-CFD-DEM framework model, processes the arbitrary shape particle in real time through the first model, and generates particle behavior data corresponding to the arbitrary shape particle and in a multiphase particle flow, and a system and platform corresponding to the method can accurately accommodate various shape characteristics of particles and provide a general particle modeling method with optimal computing efficiency.

[0051] That is, the present application is an improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing method, which has good precision and stability, and has the potential to better simulate the behavior of particles in a complex fluid environment in effectively calculating and simulating a multiphase particle flow involving arbitrary shape particles. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0053] Figure 1 A flowchart of an improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing method of the present application;

[0054] Figure 2 An embodiment workflow schematic diagram of an improved immersed boundary and directed distance field-based arbitrary shape particle CFD-DEM processing method of the present application;

[0055] Figure 3 Figure 1 is a schematic diagram of a solid fraction field based on SDF calculation for different shape particles according to an embodiment of the present application;

[0056] Figure 4 Figure 2 is a schematic diagram of a snapshot of simulating collision of irregular shape particles according to an embodiment of the present application;

[0057] Figure 5 Figure 3 is a schematic diagram of a snapshot of simulating various shape particles entering water according to an embodiment of the present application;

[0058] Figure 6 Figure 4 is a schematic diagram of a snapshot of simulating particle collapse according to an embodiment of the present application;

[0059] Figure 7 Figure 5 is a schematic diagram of a system architecture of CFD-DEM processing of arbitrary shape particles based on improved immersed boundary and directed distance field according to an embodiment of the present application;

[0060] Figure 8 Figure 6 is a schematic diagram of a platform architecture of CFD-DEM processing of arbitrary shape particles based on improved immersed boundary and directed distance field according to an embodiment of the present application;

[0061] The purposes, technical solutions and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0062] In order to better understand the purposes, technical solutions and advantages of the present application, the present application will be further described with reference to the embodiments and the accompanying drawings. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in the present specification.

[0063] The present application can also be implemented or applied by other different specific examples, and each detail in the present specification can be modified and changed in various ways based on different views and applications without departing from the spirit of the present application.

[0064] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement condition, etc. between components in a certain specific posture (as shown in the drawings). If the specific posture changes, the directional indications also change accordingly.

[0065] In addition, if the description of "first", "second" and the like is involved in the embodiments of the present application, the description of "first", "second" and the like is only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can be explicitly or implicitly included at least one of the features. Secondly, the technical solutions of various embodiments can be combined with each other, but it must be based on the realization of the ordinary skilled in the art, when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, and is not within the protection scope required by the present application.

[0066] Preferably, the improved immersed boundary and directed distance field based CFD-DEM processing method for particles of arbitrary shape is applied in one or more terminals or servers. The terminal is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0067] The terminal can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing devices. The terminal can interact with the user through a keyboard, a mouse, a remote controller, a touchpad or a voice control device.

[0068] The present application is to realize an improved immersed boundary and directed distance field based CFD-DEM processing method for particles of arbitrary shape, system and platform.

[0069] As shown in Figure 1 , it is a flow chart of the improved immersed boundary and directed distance field based CFD-DEM processing method for particles of arbitrary shape provided by the embodiments of the present application.

[0070] In the present embodiment, the improved immersed boundary and directed distance field based CFD-DEM processing method for particles of arbitrary shape can be applied in a terminal with display function or a fixed terminal, and the terminal is not limited to a personal computer, a smart phone, a tablet computer, a desktop computer or an all-in-one computer with a camera, etc.

[0071] The improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing method can also be applied to a hardware environment composed of a terminal and a server connected to the terminal through a network. The network includes but is not limited to a wide area network, a metropolitan area network or a local area network. The improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing method of the embodiment of the application can be executed by the server, or by the terminal, or by the server and the terminal together.

[0072] For example, for a terminal that needs to perform improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing, the improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing function provided by the method of the application can be integrated directly on the terminal, or a client for implementing the method of the application can be installed. For another example, the method provided by the application can also run on a device such as a server in the form of a software development kit (SDK), and the improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing function is provided in the form of an interface of the SDK, so that a terminal or other device can implement the improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing function through the provided interface. The application will be further described below with reference to the accompanying drawings.

[0073] As shown in Figures 1-6 The application provides an improved immersed boundary and directional distance field based arbitrary shape particle CFD-DEM processing method, which comprises the following steps:

[0074] S01, creating a fluid model corresponding to an arbitrary shape particle, and generating first data corresponding to the fluid model; wherein the first data is the interface state data between the multiphase fluid and the two phases in the fluid model;

[0075] S02, constructing a corresponding first model in real time according to the first data and in combination with a directional distance field or an improved immersed boundary; wherein the first model is an SDF-CFD-DEM framework model;

[0076] S03, performing real-time CFD-DEM processing on the arbitrary shape particle through the first model, and generating particle behavior data corresponding to the arbitrary shape particle and in a multiphase particle flow.

[0077] The creating of the fluid model corresponding to the arbitrary shape particle and the generating of the first data corresponding to the fluid model further comprises:

[0078] S011, acquire second data between irregular particles, and generate third data corresponding to the second data in real time in combination with a directed distance field; wherein the second data is surface state data of irregular particles; and the third data is irregular particle discrete processing data based on a directed distance field contact algorithm;

[0079] S012, acquire fourth data between fluid and particles, and generate fifth data corresponding to the fourth data in real time in combination with an improved immersed boundary; wherein the fourth data is interaction data between fluid and particles; and the fifth data is data processed by the improved immersed boundary method.

[0080] The creating a fluid model corresponding to the arbitrary shape particles and generating first data corresponding to the fluid model further comprises:

[0081] S013, acquire sixth data between the arbitrary shape particles in real time, and generate contact force data corresponding to the arbitrary shape particles based on SDF-DEM processing; wherein the sixth data is coordinate data of the particles, contact data between the particles, and direction representation data of the particles; and the contact force data is normal force data and normal torque data between the particles;

[0082] S014, acquire fluid density data and fluid velocity data corresponding to the fluid model respectively, and perform correction processing on the fluid density data and the fluid velocity respectively;

[0083] S015, acquire interaction data between fluid and particles, and generate corresponding force data applied by the fluid to the particles;

[0084] S016, acquire SDF value data corresponding to the fluid model and each unit node, and process corresponding grid units and node classification in real time according to the SDF value data in combination with grid node symbol data.

[0085] The calculation formula of the force data is:

[0086]

[0087] Wherein, F f is the force data; is the density weighted solid fraction; the summation symbol represents the sum of all grids overlapped by one particle; x i is the grid center; x p is the mass center; σ is the fluid stress; f IB represents the interaction force of the solid particles based on IBM; V c is the grid volume.

[0088] The method further comprises the following steps of:

[0089] S031, respectively initializing the CFD and DEM, and synchronously processing seventh data corresponding to the particles; wherein the seventh data is particle geometry data, particle position data and particle velocity data;

[0090] S032, mapping the seventh data into a linked list of CFD grid nodes, updating a solid fraction field, and correcting a fluid density field corresponding to the processing;

[0091] S033, generating fluid force data corresponding to the fluid model and acting on the particles, and processing the particles in real time according to the fluid force data and in combination with the DEM;

[0092] S034, updating VOF of the fluid, and reconstructing a corresponding phase interface; simultaneously, generating velocity prediction data corresponding to the fluid in real time according to data of a previous time step;

[0093] S035, updating and generating velocity data and pressure data corresponding to the fluid in combination with the obtained fluid force data.

[0094] Specifically, in the embodiment of the present application, in order to solve the above-mentioned shortcomings of irregular shape particle research modeling, the primary purpose of the present application is to provide an improved immersed boundary method-based full analytical computational fluid dynamics and discrete element method, and the workflow is as shown in Figure 2 .

[0095] That is, the present application is realized by the following technical scheme: providing an improved immersed boundary method-based full analytical computational fluid dynamics and discrete element method, including the following contents:

[0096] S1, a fluid volume (VOF) method is used to simulate the interface between the multiphase fluid and the two phases, and for the DEM, an irregular particle discrete element method (SDF-DEM) based on a directed distance field contact algorithm is used; for the interaction between the fluid and the particles, an improved IBM method is used. S2, a calculation method for simulating the interaction of multiphase fluid and irregular shape particles is proposed, and a brand new SDF-CFD-DEM framework is constructed.

[0097] The particle multiphase flow model, in content S1, the irregular particle discrete element method (SDF-DEM) based on the directed distance field contact algorithm and the improved immersed boundary method (IBM) include: (1) contact force based on SDF-DEM;

[0098] For two contacting particles, assume particle A as the reference configuration, located at the origin. The configuration of particle B is characterized by its position x and orientation θ relative to the body coordinates of particle A. The normal force F n and the normal moment M n between the particles can be expressed as:

[0099]

[0100] In the node-based contact friction linear spring model, it is assumed that each intruding node bears a friction force and the friction force is updated in an incremental manner, i.e.

[0101]

[0102] F t = F t 0 -k t δ t (4)

[0103] where F s and F t are the contact friction forces in tangential directions s and t, respectively, the superscript 0 denotes the friction force at the previous time step, k t is the contact tangential stiffness, δ s and δ t are the relative displacements in contact tangential directions s and t, respectively.

[0104] To further incorporate Coulomb’s friction law, the contact friction force is constrained as:

[0105]

[0106]

[0107] where the symbol'denotes the updated contact friction force according to Coulomb’s friction law, the subscript i is the node index, F st is the total contact friction force, μ is the contact friction coefficient, and F n is the normal force.

[0108] The total contact force and moment are calculated as:

[0109]

[0110] where F c and M n are the normal force and normal moment between the particles, respectively, F' s and F' tP represents the contact friction forces along the tangential directions s and t, respectively, where s and t are the relative displacements along the contact tangential directions, and b is the branch vector from the center of mass to the contact point; i It refers to all surface nodes that invade another particle.

[0111] (2) IBM-based fluid-particle interaction method

[0112] To account for the influence of particles, the fluid density is first corrected to a combined density, where ρ f It is the fluid density, ρ s It is the particle density, φ s It is the fraction of solid units, which is calculated as: ρ=(1-φ s )ρ f +φ s ρ s Then, for the fluid cells covered by particles, the fluid velocity is corrected to... in Represents the density-weighted entity score, u f It is the fluid velocity, u s This represents the solid velocity interpolated at the element center and is calculated as u. s =u p +ω p ×(x i -x p ), where x i It is the center of the grid cell, x p It is the center of mass of the particle, u p and ω p These are particle velocity and angular velocity, respectively. Therefore, the calculation of the relevant source force by IBM is as follows:

[0113]

[0114] in, It is the corrected fluid velocity, u f It is the fluid velocity before correction, A u These are coefficients derived from the momentum equation.

[0115] (3) IBM Improvement Methods

[0116] By refining the IBM method to align it with the SDF, the fluid-particle interactions can be fully resolved in the presence of non-spherical particles, including considering the density ρ. s The particle can be considered as a combination of two parts, namely, having a density ρ f The fluid portion and having a density ρ s -ρ fthe solid part. The fluid part and the solid part are connected by virtual springs, the motion of the fluid part is described by the Navier-Stokes equation, and the momentum equation is integrated over the overlapping particle domain to get:

[0117]

[0118] where u f is the fluid velocity, p is the pressure, p f is the fluid density, is the density-weighted volume fraction, V c is the grid volume, g is the gravity coefficient, f IB represents the interaction force between the solid particles based on IBM, and s is the fluid stress. Replacing the left side with the averaged fluid acceleration a, we can write:

[0119]

[0120] where p f is the fluid density, is the density-weighted volume fraction, V c is the grid volume, g is the gravity coefficient, f IB represents the interaction force between the solid particles based on IBM, and s is the fluid stress. V p is the particle volume, and the averaged fluid acceleration a is composed of the particle acceleration a p resulting from the rigid body motion constraint of the particles and the error a r due to the grid resolution and the fluid motion not being a rigid body. For the solid part, its motion is described by the Newton equation as follows:

[0121] (p s - p f ) V p a p = (p s - p f ) V p g -∑ cells f IB V c (13)

[0122] where p s is the particle density, p f is the fluid density, a p is the particle acceleration resulting from the rigid body motion constraint of the particles, V c is the grid volume, g is the gravity coefficient, f IB represents the interaction force between the solid particles based on IBM, and s is the fluid stress. V p is the particle volume.

[0123] Adding the two equations, we get:

[0124]

[0125] where p s is the particle density, p f is the fluid density, a p is the particle acceleration due to rigid body motion constraints of the particle, a r is the error acceleration due to grid resolution and the fact that the fluid motion is not a rigid body, is the density weighted solid fraction, V c is the grid volume, g is the gravitational coefficient, f IB denotes the IBM-based solid particle interaction force, s is the fluid stress, V p is the particle volume.

[0126] The force exerted by the fluid on the particle is integrated from the fluid force acting on the particle surface, which can be computed by applying the divergence theorem as:

[0127]

[0128] where F f is the force data; is the density weighted solid fraction; the summation sign denotes the summation over all grids that are overlapped by one particle; x i is the grid center; x p is the centroid; s is the fluid stress; f IB denotes the IBM-based solid particle interaction force; V c is the grid volume.

[0129]

[0130] where M f is the moment of force generated by the force; is the density weighted solid fraction; the summation sign denotes the summation over all grids that are overlapped by one particle; x i is the grid center; x p is the centroid; s is the fluid stress; f IB denotes the IBM-based solid particle interaction force; V c is the grid volume.

[0131] (4) SDF-based solid fraction estimation

[0132] The present application proposes a method for SDF-based solid fraction estimation, by utilizing the SDF value of each cell node, the classification of grid cells and nodes can be efficiently and robustly handled by simply testing the sign of each grid node without performing traditional grid intersection tests.

[0133] Cell solid fraction

[0134]

[0135] where, denotes the sum of the SDF values of the nodes inside the cell, while denotes the sum of the absolute values of the SDF values of all the cell nodes.

[0136] In the content S2, the calculation method for simulating the interaction of multiphase fluid with particles of any shape, comprising:

[0137] (1) Search for solid nodes:

[0138] A linked list mapping CFD grid nodes to DEM particles is introduced and implemented in the CFD-DEM coupler, which functions as follows: for a given query node, first obtain the DEM partition cell that encloses the node, and then query the particles connected to this partition cell to determine all the particles that overlap with the node. With the SDF-based particle description, the linked list of nodes to particles can be effectively constructed by testing the sign of the SDF of the given node with respect to each particle.

[0139] (2) Domain discretization:

[0140] Both the CFD and SDF-DEM codes support parallel computing through the Message Passing Interface (MPI). The simulation data is distributed among different processors, and data exchange is required between processors. Due to the different distributions of fluid and particles, the DEM data of each processor is synchronized to all other processors in each CFD-DEM coupling cycle. The present invention has implemented an MPI-based DEM data synchronization algorithm.

[0141] (3) Fully analytical SDF-CFD-DEM calculation:

[0142] A new analytical CFD-DEM coupler is implemented under the SDF framework, with CFD and DEM being solved separately through the exchange of particle-fluid interaction forces. The main solving steps of the fully analytical SDF-CFD-DEM include:

[0143] 1. Initialize CFD by domain geometry, domain and grid discretization, velocity field, pressure field, and boundary conditions.

[0144] 2. Initialize DEM with particles, boundary walls, contact models, and domain discretization.

[0145] 3. For the case of parallel computing, synchronize particle data such as geometry, position, and velocity to all processors.

[0146] 4. Update the linked list of particles mapped to the CFD grid nodes.

[0147] 5. Update the solid volume fraction field and correct the fluid density field.

[0148] 6. Calculate the fluid force acting on the particles.

[0149] 7. Run the DEM, including contact detection and resolution, contact force evaluation, particle motion calculation, and update the particle geometry description.

[0150] 8. Solve the continuity equation, update the VOF of the fluid, and reconstruct the phase interface.

[0151] 9. Update the Navier-Stokes momentum equation and solve the velocity prediction using the data from the previous time step (e.g., velocity and pressure fields).

[0152] 10. Calculate the source force associated with the IBM to account for the effect of particle motion on the fluid. Repeat this step according to the prescribed number of iterations of the Pressure-Implicit with Splitting of Operators (PISO) scheme.

[0153] 11. Go to step 3 and repeat the entire CFD-DEM simulation until the end time is reached.

[0154] Compared with the prior art, the present application has the following advantages: (1) The proposed SDF-CFD-DEM method integrates SDF-DEM into computational particle dynamics, while combining IBM with SDF, to solve the interaction between fluid and particles in a fully analytical manner, thereby enabling flexible and efficient simulation of multiphase fluid and numerical modeling of particles of arbitrary shape. (2) The energy-conserving contact theory based on contact potential energy is used to solve the contact behavior between particles of arbitrary shape, thereby realizing quantitative energy analysis of CFD-DEM simulation. In order to map DEM particles to the CFD domain, a solid volume fraction estimation method based on SDF is proposed. (3) The proposed SDF-based CFD-DEM will help to release the advantages of computational particle mechanics involving irregular shapes, and become an efficient and robust tool for exploring complex fluid-particle interactions, to improve the understanding of the interaction between irregularly shaped particles and fluid.

[0155] To achieve the purpose of the present application scheme, simulation examples are provided to verify and demonstrate the function of the fully analytical computational fluid dynamics and discrete element method based on the improved immersed boundary method. Examples include collision tests of irregularly shaped particles, particle entry into water tests, particle collapse tests, and bed load transport tests.

[0156] Embodiment 1:

[0157] Perform a collision simulation between two particles. The two particles are placed in a free-flowing water stream with an initial separation distance of 0.01 m. One particle is fixed in place, while the other is designed to move towards the first particle with an initial velocity of 0.02 m / s, colliding approximately after 0.5 seconds. Both particles have an equivalent diameter of 0.02 m and a density of 7800 kg / m³. 3 A linear contact model is adopted, with a normal stiffness of 2.0 × 10⁻⁶. 6 N / m, shear stiffness is 1.0×10 6 N / m, contact friction and contact damping are both zero. For example Figure 4 The diagram illustrates the collision process of irregularly shaped particles. Both irregularly shaped and spherical particles were considered, and the influence of particle shape irregularity on potential eddies in the fluid can be clearly observed by comparing the fluid velocity field. The results demonstrate that SDF-CFD-DEM possesses excellent energy evolution capture capabilities.

[0158] Example 2:

[0159] A simulation of a particle immersion test was conducted. Numerous particles were inserted into the top of a 1.0m cubic container, allowing them to enter the water and settle under gravity. Different particle models were considered, including hyperquadratic surfaces, spherical harmonics, polyhedra, and level sets. In all cases, the equivalent particle size was assumed to be 0.1m, and the density to be 2650kg / m³. 3 A linear contact model is adopted, with a normal stiffness of 2.0 × 10⁻⁶. 6 N / m, shear stiffness is 1.0×10 6 The fluid density is N / m, the contact friction coefficient is 0.5, the contact damping coefficient is 0.7, the water depth is 0.5m, and the entire fluid domain is discretized into a 100×100×100 element grid. In the case of... Figure 5 As shown, the process of particles entering the water is illustrated. The results demonstrate that the SDF-CFD-DEM method has a good ability to model the dynamics of irregularly shaped particles.

[0160] Example 3:

[0161] Simulate particle collapse tests. For example... Figure 6 As shown, the structure consists of 320 irregularly shaped particles with an equivalent diameter of 3.86 cm, and dimensions of approximately 20 cm (width) × 20 cm (depth) × 50 cm (height). The particles are modeled using spherical harmonic functions based on the SDF-DEM method, and collapse simulations were performed by removing the left sidewalls of the constrained particles. For comparison, a collapse test of a column of spherical particles was also conducted. This test also involved two fluid phases to demonstrate the performance of SDF-CFD-DEM in modeling free surfaces and their interactions with particles.

[0162] To achieve the above object, the application further provides an arbitrary shape particle CFD-DEM processing system based on improved immersed boundary and directed distance field, which is applied to the arbitrary shape particle CFD-DEM processing method based on improved immersed boundary and directed distance field, as shown in the figure, and comprises: Figure 7

[0163] A first data generating unit is configured to create a fluid model corresponding to the arbitrary shape particle and generate first data corresponding to the fluid model, wherein the first data is interface state data between multiphase fluid and two phases in the fluid model.

[0164] A model constructing unit is configured to construct a first model in real time according to the first data and in combination with the directed distance field or the improved immersed boundary, wherein the first model is an SDF-CFD-DEM framework model.

[0165] A second data generating unit is configured to process the arbitrary shape particle in real time through the first model and generate particle behavior data corresponding to the arbitrary shape particle and in a multiphase particle flow.

[0166] The first data generating unit further comprises:

[0167] A first data generating module is configured to acquire second data between irregular particles and generate third data corresponding to the second data in real time in combination with the directed distance field, wherein the second data is surface state data of the irregular particles, and the third data is irregular particle discrete processing data based on the directed distance field contact algorithm.

[0168] A second data generating module is configured to acquire fourth data between fluid and particles and generate fifth data corresponding to the fourth data in real time in combination with the improved immersed boundary, wherein the fourth data is interaction data between fluid and particles, and the fifth data is data processed through the improved immersed boundary method.

[0169] The second data generating unit further comprises:

[0170] A first data processing module is configured to initialize CFD and DEM respectively and process seventh data corresponding to the particles synchronously, wherein the seventh data is particle geometry data, particle position data and particle velocity data.

[0171] A second data processing module is configured to map the seventh data to a link list of CFD grid nodes, update a solid fraction field and correct fluid density field corresponding to the processing.

[0172] ​a third data generation module configured to generate fluid force data corresponding to the fluid model and acting on the particles, and to generate the corresponding particles by real-time discrete element method (DEM) processing based on the fluid force data;

[0173] a fourth data generation module configured to update the volume of fluid (VOF) processing of the fluid and to reconstruct the corresponding phase interface, and to generate real-time velocity prediction data corresponding to the fluid based on the data of the previous time step;

[0174] a fifth data generation module configured to update and generate velocity data and pressure data corresponding to the fluid based on the obtained fluid force data.

[0175] The first data generation unit further comprises:

[0176] a sixth data generation module configured to obtain sixth data between the particles of any shape in real time, and to generate contact force data corresponding to the particles of any shape based on SDF-DEM processing, wherein the sixth data comprises coordinate data of the particles, contact data between the particles, and directional representation data of the particles, and the contact force data comprises normal force data and normal torque data between the particles;

[0177] a third data processing module configured to obtain fluid density data and fluid velocity data corresponding to the fluid model respectively, and to perform correction processing on the fluid density data and the fluid velocity respectively;

[0178] a seventh data generation module configured to obtain interaction data between the fluid and the particles, and to generate force data applied by the fluid to the particles;

[0179] a fourth data processing module configured to obtain SDF value data corresponding to the fluid model and each unit node, and to perform real-time processing on the corresponding grid unit and node classification based on the SDF value data and in combination with grid node symbol data.

[0180] The calculation formula of the force data is:

[0181]

[0182] wherein F f is the force data; is the density-weighted solid fraction; the summation symbol represents the sum of all grids overlapped by one particle; x i is the grid center; x p is the mass center; σ is the fluid stress; f IB represents the interaction force of the solid particles based on IBM; V c is the grid volume.

[0183] In the system embodiment of the present invention, the specific details of the method steps involved in the CFD-DEM processing of arbitrary-shaped particles based on improved immersion boundary and directional distance field have been described above. That is to say, the functional modules in the system are used to implement the steps or sub-steps in the above method embodiment, which will not be repeated here.

[0184] To achieve the above objectives, the present invention also provides a CFD-DEM processing platform for arbitrary-shaped particles based on improved immersion boundaries and oriented distance fields, such as... Figure 8 As shown, it includes a processor, a memory, and a control program for an arbitrary-shaped particle CFD-DEM processing platform based on improved immersion boundary and directed distance field. The processor executes the control program, which is stored in the memory. This control program implements the steps of the arbitrary-shaped particle CFD-DEM processing method based on improved immersion boundary and directed distance field. For example:

[0185] S01. Create a fluid model corresponding to particles of arbitrary shape, and generate first data corresponding to the fluid model; wherein, the first data is the interface state data between the multiphase fluid and the two phases in the fluid model;

[0186] S02. Based on the first data and combined with the directed distance field or improved immersion boundary, construct the corresponding first model in real time; wherein, the first model is the SDF-CFD-DEM framework model.

[0187] S03. Using the first model, CFD-DEM is used to process particles of arbitrary shape in real time, and particle behavior data corresponding to the arbitrary shape particles in the multiphase particle flow is generated.

[0188] The specific details of the steps have been explained above and will not be repeated here.

[0189] In the embodiment of the present application, the processor built in the processing platform for CFD-DEM of arbitrary shape particle based on improved immersed boundary and directed distance field can be composed of integrated circuits, for example, can be composed of a single packaged integrated circuit, or can be composed of multiple packaged integrated circuits with same function or different functions, including one or more central processing units (CPU), microprocessors, digital processing chips, graphic processors and combinations of various control chips, etc. The processor connects various components by various interfaces and lines, executes programs or units stored in the memory and calls data stored in the memory, so as to execute various functions and process data of CFD-DEM of arbitrary shape particle based on improved immersed boundary and directed distance field.

[0190] The memory is used for storing program codes and various data, is installed in the processing platform for CFD-DEM of arbitrary shape particle based on improved immersed boundary and directed distance field, and realizes high-speed and automatic access of programs or data during running.

[0191] The memory includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memory, disk memory, tape memory, or any other computer readable medium capable of carrying or storing data.

[0192] The application creates a fluid model corresponding to an arbitrary shape particle, and generates first data corresponding to the fluid model; wherein the first data is the interface state data between the multiphase fluid and the two phases in the fluid model; according to the first data, and in combination with a directed distance field or an improved immersed boundary, a corresponding first model is constructed in real time; wherein the first model is an SDF-CFD-DEM framework model; through the first model, the arbitrary shape particle is processed in real time CFD-DEM, and particle behavior data corresponding to the arbitrary shape particle and in the multiphase particle flow is generated; and a system and platform corresponding to the method can accurately accommodate various shape characteristics of particles and provide a general particle modeling method with optimal computing efficiency.

[0193] That is, the present scheme is an arbitrary shape particle CFD-DEM processing method based on an improved immersed boundary and a directed distance field, which has good precision and stability, and has potential to better simulate the behavior of particles in a complex fluid environment in effectively calculating and simulating the processing of a multiphase particle flow involving arbitrary shape particles.

[0194] The above-described embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be noted that for ordinary skilled persons in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of protection of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for processing CFD-DEM of arbitrary-shaped particles based on improved immersion boundary and oriented distance field, characterized in that, The method includes the following steps: The process includes: creating a fluid model corresponding to particles of arbitrary shape and generating first data corresponding to the fluid model; acquiring second data between irregular particles and generating third data corresponding to the second data in real time by combining a directed distance field; acquiring fourth data between fluid and particles and generating fifth data corresponding to the fourth data in real time by combining an improved immersion boundary; acquiring sixth data between particles of arbitrary shape in real time and generating contact force data corresponding to the particles of arbitrary shape based on SDF-DEM processing; acquiring fluid density data and fluid velocity data corresponding to the fluid model respectively, and performing correction processing on the fluid density data and the fluid velocity data respectively; acquiring interaction data between fluid and particles, and generating corresponding force data exerted by the fluid on the particles. According to the data, the SDF value data corresponding to each element node of the fluid model is obtained, and the corresponding mesh elements and node classifications are processed in real time based on the SDF value data and the mesh node symbol data; wherein, the first data is the interface state data between multiphase fluid and two phases in the fluid model; the second data is the surface state data of irregular particles; the third data is the data of irregular particles discretized based on the directed distance field contact algorithm; the fourth data is the interaction data between fluid and particles; the fifth data is the data processed by the improved immersion boundary method; the sixth data is the coordinate data of particles, the contact data between particles, and the orientation characterization data of particles; the contact force data is the normal force data and normal moment data between particles; the calculation formula of the force data is: In the formula, F f For force data; Density-weighted entity fraction; summation symbol represents the sum of all meshes overlapped by a single particle; σ is the fluid stress; f IB Represents the interaction force of solid particles based on IBM; V c For the mesh volume; Based on the first data, and combined with the directed distance field or improved immersion boundary, a corresponding first model is constructed in real time; wherein, the first model is an SDF-CFD-DEM framework model. Using the first model, particles of arbitrary shape are processed in real time via CFD-DEM, and particle behavior data corresponding to the arbitrary shape particles in the multiphase particle flow is generated.

2. The CFD-DEM processing method for arbitrary-shaped particles based on improved immersion boundary and directional distance field according to claim 1, characterized in that, The step of processing arbitrary-shaped particles in real time using CFD-DEM through the first model and generating particle behavior data corresponding to the arbitrary-shaped particles in a multiphase particle flow also includes: Initialize and process CFD and DEM respectively, and process the seventh data corresponding to the particles synchronously; wherein, the seventh data is particle geometry data, particle position data and particle velocity data; The seventh data is mapped to the link list of CFD mesh nodes, and the solid fractional field is updated, as well as the corresponding fluid density field is corrected. Generate fluid force data corresponding to the fluid model and acting on the particles; and based on the fluid force data, combine the corresponding particles with real-time discrete element processing of the DEM. The VOF of the processed fluid is updated, and the corresponding phase interface is reconstructed; at the same time, based on the data of the previous time step, the velocity prediction data corresponding to the fluid is generated in real time. By combining the acquired fluid force data, the velocity and pressure data corresponding to the fluid are updated, processed, and generated.

3. A CFD-DEM processing system for arbitrary-shaped particles based on improved immersion boundary and oriented distance field, characterized in that, The system is applied to the CFD-DEM processing method for arbitrary-shaped particles based on improved immersion boundary and oriented distance field as described in any one of claims 1-2, and the system comprises: The first data generation unit is used to create a fluid model corresponding to particles of arbitrary shape and generate first data corresponding to the fluid model; wherein, the first data is the interface state data between multiphase fluids and two phases in the fluid model. The model building unit is used to build a corresponding first model in real time based on the first data and in combination with a directed distance field or an improved immersion boundary; wherein the first model is an SDF-CFD-DEM framework model. The second data generation unit is used to process particles of arbitrary shape in real time using CFD-DEM through the first model, and generate particle behavior data corresponding to the particles of arbitrary shape in the multiphase particle flow.

4. The CFD-DEM processing system for arbitrary-shaped particles based on improved immersion boundary and oriented distance field according to claim 3, characterized in that, The first data generation unit further includes: The first data generation module is used to acquire second data between irregular particles and generate third data corresponding to the second data in real time by combining the directed distance field; wherein, the second data is the surface state data of the irregular particles; and the third data is the irregular particle discretization data based on the directed distance field contact algorithm. The second data generation module is used to acquire fourth data between the fluid and the particles, and to generate fifth data corresponding to the fourth data in real time by combining the improved immersion boundary method; wherein, the fourth data is the interaction data between the fluid and the particles; and the fifth data is the data processed by the improved immersion boundary method. The second data generation unit further includes: The first data processing module is used to initialize and process CFD and DEM respectively, and synchronously process the seventh data corresponding to the particles; wherein, the seventh data is particle geometry data, particle position data and particle velocity data; The second data processing module is used to map the seventh data to the link list of CFD mesh nodes, update the solid fractional field, and correct the corresponding fluid density field. The third data generation module is used to generate fluid force data corresponding to the fluid model and acting on the particles. Based on the fluid force data, the corresponding particles are processed in real time using the DEM. The fourth data generation module is used to update the VOF of the processed fluid and reconstruct the corresponding phase interface; at the same time, it generates velocity prediction data corresponding to the fluid in real time based on the data of the previous time step. The fifth data generation module is used to combine the acquired fluid force data, update and process it, and generate velocity and pressure data corresponding to the fluid.

5. A CFD-DEM processing system for arbitrary-shaped particles based on an improved immersion boundary and a directed distance field, as described in claim 3 or 4, characterized in that... The first data generation unit further includes: The sixth data generation module is used to acquire the sixth data between particles of arbitrary shape in real time, and generate contact force data corresponding to the particles of arbitrary shape based on SDF-DEM processing; wherein, the sixth data is the coordinate data of the particles, the contact data between the particles, and the orientation characterization data of the particles; the contact force data is the normal force data and normal moment data between the particles; The third data processing module is used to acquire fluid density data and fluid velocity data corresponding to the fluid model, and to perform correction processing on the fluid density data and the fluid velocity data respectively. The seventh data generation module is used to acquire interaction data between fluid and particles, and generate corresponding force data exerted by the fluid on the particles; The fourth data processing module is used to acquire the SDF value data corresponding to each unit node of the fluid model, and to process the corresponding grid units and node classifications in real time based on the SDF value data and the grid node symbol data.

6. The CFD-DEM processing system for arbitrary-shaped particles based on improved immersion boundary and oriented distance field according to claim 5, characterized in that, The formula for calculating the force data is: in, F f For force data; The density-weighted entity fraction; the summation symbol represents the sum of all meshes overlapped by a single particle; σ is the fluid stress; f IB Represents the interaction force of solid particles based on IBM; V c This represents the mesh volume.

7. A CFD-DEM processing platform for arbitrary-shaped particles based on improved immersion boundary and oriented distance field, characterized in that, The system includes a processor, a memory, and a control program for an arbitrary-shaped particle CFD-DEM processing platform based on an improved immersion boundary and a directed distance field. The processor executes the control program, which is stored in the memory. The control program implements the arbitrary-shaped particle CFD-DEM processing method based on an improved immersion boundary and a directed distance field as described in any one of claims 1 to 2.

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