Calculation method and device for multi-scale particle multiphase flow field and electronic equipment

Abstract

The invention discloses a calculation method and device for a multiphase flow field of multi-scale particles and electronic equipment, and the method comprises the steps: determining large-scale analytic particles and small-scale non-analytic particles in a multiphase flow according to a preset computational domain grid size; acquiring flow field medium parameters of the analytic particles and physical parameters of discrete particles, and solving flow field information and physical information of multiphase flow by using an immersion boundary method; interface parameters of each medium composition in the non-analytic particle flow field and physical parameters of discrete particles are obtained, the particle volume fraction is solved through a statistical kernel method, and based on the particle volume fraction, physical information of multiphase flow is solved through a fluid volume method; and according to the physical information solved by the analytic particles and the non-analytic particles, calculating the physical parameters of the multi-scale particle multiphase flow field.

Description

Technical Field

[0001] The present application relates to the field of computational fluid dynamics particle multiphase flow technology, and in particular to a method and device for calculating a multi-scale particle multiphase flow field, and an electronic device. Background Art

[0002] The phenomenon of multiphase flow with multi-scale particles coexisting is widely present in nature and in industrial fields such as chemical industry, metallurgy, and mining. For example, the multiphase flow phenomenon in which large-scale ores and small-scale sediments coexist in deep-sea mining involves the interaction between particles of various sizes and shapes and fluids. For the interaction between particles with regular shapes and small volumes and fluids, computer simulation methods are relatively mature. The solution to the particle-fluid coupled flow field can be divided into analytical and non-analytical methods. The analytical method can use the immersed boundary method to solve the boundary of the particle. The grid is smaller than the particle scale, and the calculation amount is large. It is not suitable for the presence of a large number of particles. The non-analytical method only tracks the particle trajectory and cannot describe the particle boundary. It is not applicable to the solution of the interaction between larger-scale particles and fluids.

[0003] However, when considering the coexistence of large and small scale particles and multiple continuous fluids in the flow field, it is urgent to establish a multi-scale multiphase flow calculation method that couples analytical and non-analytical methods. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a calculation method and device for multi-scale particle multiphase flow fields, and electronic equipment to solve the technical problem existing in the related technology involving the interaction between particles of various sizes and shapes and fluids, and the more complicated solution process when large and small scale particles coexist in the flow field.

[0005] According to a first aspect of an embodiment of the present application, a method for calculating a multi-scale particle multiphase flow field is provided, comprising:

[0006] According to the pre-set computational domain grid size, large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow are determined;

[0007] Obtaining the flow field medium parameters of the analytical particles and the physical parameters of the discrete particles, and solving the flow field information and the physical information of the multiphase flow by using the immersed boundary method;

[0008] Obtaining the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, solving the particle volume fraction by using the statistical kernel method, and solving the physical information of the multiphase flow by using the fluid volume method based on the particle volume fraction;

[0009] The physical parameters of the multi-scale particle multiphase flow field are calculated based on the physical information solved by the analytical particles and the unanalyzed particles.

[0010] Optionally, according to a preset computational domain grid size, large-scale resolved particles and small-scale unresolved particles in the multiphase flow are determined, including:

[0011] Determine the mesh size of the created fluid domain;

[0012] According to the fluid domain grid size, the particle size is compared with the grid size. Particles larger than 8 times the grid size are analyzed particles, and particles smaller than or equal to the grid size are unanalyzed particles.

[0013] Optionally, obtaining medium parameters and physical parameters of discrete particles in the analytical particle flow field and solving physical information of multiphase flow using an immersed boundary method includes:

[0014] Obtaining medium parameters and physical parameters of discrete particles in the analytical particle flow field;

[0015] According to the medium parameters and physical parameters, the flow field information is obtained by solving the Navier-Stokes equation; the particle boundary is described by the immersed boundary method, and the particle physical information is obtained by solving;

[0016] The multiphase flow physical information is obtained by solving the flow field information and the particle physical information.

[0017] Optionally, interface parameters of each medium composition and physical parameters of discrete particles in the unanalyzed particle flow field are obtained, a statistical kernel method is used to solve the particle volume fraction, and based on the particle volume fraction, a fluid volume method is used to solve the physical information of the multiphase flow, including:

[0018] Obtain the interface parameters of each medium component and the physical parameters of discrete particles in the unanalyzed particle flow field;

[0019] According to the physical parameters of the discrete particles, a statistical kernel method is used to solve the volume fraction of the particles in the flow field grid;

[0020] According to the interface parameters of each medium component in the unanalyzed particle flow field and the volume fraction of particles in the flow field, the physical information of the multiphase flow is solved by the fluid volume method.

[0021] According to a second aspect of an embodiment of the present application, a computing device for a multi-scale particle multiphase flow field is provided, comprising:

[0022] The particle determination module is used to determine the large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow according to the preset computational domain grid size;

[0023] A first solution module is used to obtain the flow field medium parameters of the analytical particles and the physical parameters of the discrete particles, and solve the flow field information and the physical information of the multiphase flow by using the immersed boundary method;

[0024] The second solution module is used to obtain the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, solve the particle volume fraction by using the statistical kernel method, and solve the physical information of the multiphase flow by using the fluid volume method based on the particle volume fraction;

[0025] The calculation module is used to calculate the physical parameters of the multi-scale particle multiphase flow field according to the physical information solved by the analytical particles and the unanalyzed particles.

[0026] According to a third aspect of an embodiment of the present application, there is provided an electronic device, including:

[0027] one or more processors;

[0028] A memory for storing one or more programs;

[0029] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in the first aspect.

[0030] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer instructions are stored, and when the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0031] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0032] It can be seen from the above embodiments that the present application simultaneously uses the immersed boundary method to solve the flow field information of the analytical particles and the physical information of the multiphase flow, and uses the statistical kernel method to calculate the volume fraction of the analytical particles in the unanalyzed particle flow field. Based on the particle volume fraction, the fluid volume method is used to solve the physical information of the multiphase flow. This overcomes the technical problems existing in the related technologies involving the interaction between particles of various sizes and shapes and fluids, and the complex solution process when large and small scale particles coexist in the flow field, thereby achieving the effect of efficiently solving the problem of large and small particle-fluid interaction.

[0033] 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

[0034] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0035] Figure 1 It is a flow chart of a method for calculating a multi-scale particle multiphase flow field according to an exemplary embodiment.

[0036] Figure 2It is a schematic diagram of a multi-scale particle-fluid two-dimensional simulation of a multi-scale particle multiphase flow field according to an exemplary embodiment.

[0037] Figure 3 It is a block diagram of a computing device for a multi-scale particle multiphase flow field according to an exemplary embodiment.

[0038] Figure 4 The diagram is a schematic structural diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0040] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0041] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0042] When it comes to the interaction between solids and fluids of various sizes and shapes (i.e., multiphase flow processes that simultaneously contain gas-liquid and discrete particles such as solid particles and discrete bubbles. For example, multiphase fluid transportation, dust separation and collection, fluidized beds, cavitation flows of underwater vehicles or rotating machinery, etc.), when large and small-scale particles coexist in the flow field, the solution process of the immersion method is more complicated.

[0043] Figure 1 is a flow chart of a method for calculating a multi-scale particle multiphase flow field according to an exemplary embodiment. Figure 1 As shown, the method may include the following steps:

[0044] S1: According to the preset computational domain grid size, determine the large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow; this step includes the following sub-steps:

[0045] S11: Determine the mesh size of the created fluid domain;

[0046] Specifically, the mesh file is read to confirm the mesh size.

[0047] S12: according to the fluid domain grid size, the particle size is compared with the grid size, and particles larger than 8 times the grid size are analyzed particles, and particles smaller than or equal to the grid size are unanalyzed particles;

[0048] Specifically, read the particle file to check the particle size and compare it with the grid size. Particles that are larger than 8 times the grid size are analyzed particles, and particles that are smaller than or equal to the grid size are unanalyzed particles. Figure 2 shown.

[0049] The analytical particles are discrete particles when the particle volume is larger than 8 times the computational domain grid size, and the unanalyzed particles are discrete particles when the particle volume is smaller than 8 times the computational domain grid size.

[0050] S2: Obtain the flow field medium parameters of the analytical particles and the physical parameters of the discrete particles, and use the Immersed Boundary Method (IBM) to solve the flow field information and the physical information of the multiphase flow; this step includes the following sub-steps:

[0051] S21: Obtaining medium parameters and physical parameters of discrete particles in the analytical particle flow field;

[0052] Specifically, the physical parameters of the particles are read, including Young's modulus, density, and diameter; the fluid medium parameters are read, including density and viscosity.

[0053] S22: according to the medium parameters and physical parameters, the flow field information is obtained by solving the Navier-Stokes equation; the particle boundary is described by using the immersed boundary method, and the particle physical information is obtained by solving the equation;

[0054] Specifically, the flow field information includes the expected velocity V of the IB point determined by the discrete element method (DEM) at each time step. n+1 , the interpolation velocity U of the surrounding mesh nodes for the same IB point n+1 , additional body force F n+1 . Solution First, use the Navier-Stokes equations to describe the motion of an incompressible viscous fluid with a free surface:

[0055]

[0056] Where u is the velocity (here the velocity is the initial value), t is the time, ρ is the density, p is the pressure, and τ is the viscous stress tensor defined as Where μ is the dynamic viscosity, F b represents the volume force, and F indicates that the added volume force is affected by the moving solid boundary.

[0057] According to the feature-based splitting scheme, the time-discrete formulation of the momentum equation can be expressed as:

[0058] Δu=G n +H n+1 +F n+1 Δt(3)

[0059] Where n represents the time step;

[0060]

[0061] Unmatched special nodes in the immersed boundary method (IBM) require an interpolation function to interpolate the physical properties on the grid nodes to the IB points, while a distribution function is required to distribute the physical quantities on the IB points to the grid nodes. The interpolation function I and the distribution function D are defined by the following formulas:

[0062] V n+1 =U n+1 =I(u n+1 )=I(u n +Δu)=I(u n +G n +H n+1 +F n+1 Δt)(6)

[0063] The fluid phase is discretized by a fixed Cartesian grid, satisfying the no-slip boundary condition:

[0064] V n+1 =U n+1 (7)

[0065] Where V n+1 is the expected velocity at point IB determined by the discrete element method, U n+1 is the interpolation velocity of the surrounding mesh nodes for the same IB point.

[0066] The additional volume force can be solved using the following formula:

[0067] F n+1 Δt=D[V n+1 -I(u n +G n +H n+1 )] (8)

[0068] The particle physical information includes translational acceleration Pan speed Rotational acceleration Contact force Fc. During the solution, the motion of a rigid object entering water is governed by Newton's second law:

[0069]

[0070] Where m is the mass of the solid, is the translational acceleration, F e 、F c and F f They represent the external force, contact force and coupling force exerted by the surrounding fluid on the solid, c is the damping coefficient, is the translation speed, I M is the moment of inertia tensor, is the rotational acceleration and M is the total torque.

[0071] Each rigid body is modeled as a discrete element, and contact detection is performed between the elements. When solids collide with each other, contact forces between discrete elements are generated. According to DEM, the contact force Fc can be divided into the normal contact force Fcn and the tangential force Fct, which can be written as follows:

[0072]

[0073] F ct =RF ct '+k t ·Δδ ct (12)

[0074] Where p is the penalty parameter, β c and β t are contact particles and target particles respectively. is the overlapping domain β c ∩β t The boundary of , where n is the outward unit vector, and is the potential function of the contact particle and the target particle, R is the equivalent transfer F ct The matrix of the direction, which is the tangential contact force at the previous time step, k t is the tangential stiffness coefficient, Δδ ct is the increment of tangential displacement.

[0075] According to Coulomb's friction law, the tangential force should satisfy:

[0076]

[0077] Among them (F ct )max Max is the maximum allowable static friction, is the maximum friction angle. The force F acting on the rigid body f Unlike the added body force f in the equation; which is applied at the mesh nodes in the framework of the Euler description, the coupling force f is applied at the IB points according to the Lagrangian description. The interaction force acting on the solid can be derived as:

[0078]

[0079] Where Ω' represents the entire computational domain inside, which consists of the fluid phase Ω and the solid phase Ω".

[0080] The above calculation method - immersed boundary-discrete element method is used to track the particle boundary and calculate the particle motion parameters, which can effectively handle the complex motion of particles in the flow field. The particle velocity, acceleration and additional volume force can be effectively solved.

[0081] S23: Obtaining multiphase flow physical information according to the flow field information and particle physical information;

[0082] Specifically, the multiphase flow physical information includes the coupling velocity u, pressure p and additional force f of the fluid-solid system and the fluid phase, as well as the inner ring volume force f n+1,k,i . The strongly coupled fluid-solid system and the coupling u, p and f of the fluid phase all require an iterative algorithm. Where k represents the number of iterations. According to the standard Galerkin procedure, the iterative format of the spatially discrete governing equations of the fluid phase can be expressed as:

[0083] (Δu n,k ,Δp n, k)=RHS f (u n ,p n ,δ n+1,k-1 ) (15)

[0084] where RHS f represents the right-hand format of the discrete momentum equation. Similarly, based on the velocity Verlet algorithm, the iterative format of the solid control equation can be written as follows:

[0085]

[0086] where RHS s is the right-hand form of the solid discretized governing equations. Once the convergence criteria of the iterative scheme for the coupled system are met, the loop is broken, or k+1 iterations of n+1 steps are performed to achieve a tightly coupled system.

[0087] The added volume force f in the inner ring n+1,k,i It is solved by the following formula:

[0088]

[0089] S3: Obtain the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, use the statistical kernel method (SKM) to solve the particle volume fraction, and based on the particle volume fraction, use the volume of fluid (VOF) method to solve the physical information of the multiphase flow; this step includes the following sub-steps:

[0090] S31: Obtaining interface parameters of each medium component and physical parameters of discrete particles in the unanalyzed particle flow field;

[0091] Specifically, the physical parameters of the particles, such as Young's modulus, density, and diameter, are read; the fluid medium parameters are calculated through the medium interface parameters, and the continuous fluid pressure, velocity, and other information are solved through formulas (1) and (2).

[0092] S32: according to the physical parameters of the discrete particles, the volume fraction of the particles in the flow field grid is solved by using the SKM method;

[0093] Specifically, the particle flow field information is solved by referring to the statistical kernel method and the fluid volume method. Since the particles are not resolved and the particle volume is smaller than the grid volume, it is necessary to solve the particle volume fraction α(x). In order to facilitate the solution of the particle volume fraction, the statistical kernel method (with embedded Gaussian distribution kernel function) is used here. The volume fraction of each discrete unit can be calculated as:

[0094]

[0095] where ε sc is the solid volume fraction defined at the center of cell c; x is the coordinate of the grid or particle; i is the general index of the particle, from 1 to Np (the total number of particles in the system); the cell index m ranges from 1 to Nc (the total number of grids); ω i is the weight of the contribution of particle i, where the unit number is omitted from the subscript; the Gaussian distribution function is the calculation function of the kernel function K:

[0096]

[0097] Similarly, the solid phase velocity can be obtained by the following averaging procedure:

[0098]

[0099] ω i In a similar way, the drag force per unit volume of the mixture flow field (or the drag force on the unit c when discrete) is calculated from the drag force of a single particle as follows:

[0100]

[0101] The above content is an introduction to the SKM algorithm for small-scale particle calculations;

[0102] In the solution of the particle field, in order to solve the position information of the particles, the kernel function uses a three-dimensional Gaussian distribution function:

[0103]

[0104] Where: T is the vector transpose sign; b is the Gaussian distribution function parameter, which characterizes the spatial range affected by the particle; x i is the center position coordinate of the ith particle in the calculation domain, and x is the spatial coordinate.

[0105] In three-dimensional space, this expression satisfies the normalization condition:

[0106] ∫h(x)dx=1 (24)

[0107] In the calculation domain, the volume fraction value of a point in space is obtained by superimposing the volume weights of different particles at that point:

[0108]

[0109] Where: α(x) is the volume fraction of the particle at the spatial position x, N p is the number of particles whose influence range includes the spatial position, V p,i is the volume of the i-th particle in the computational domain.

[0110] This calculation method distributes the particle volume in the entire calculation domain according to the kernel function, which can effectively reduce the calculation error and improve the calculation efficiency.

[0111] S33: According to the interface parameters of each medium component in the unanalyzed particle flow field and the volume fraction of particles in the flow field, the physical information of the multiphase flow is solved by the fluid volume method.

[0112] Specifically, the physical information of multiphase flow includes the fluid volume fraction ε, particle velocity v, contact force F in the flow field grid, and the particle velocity v in the flow field grid. c , surface tension f s , fluid velocity u;

[0113]

[0114] The weight here It is clear that the particle completely surrounded by the grid is If the particle intersects the mesh boundary, then The void fraction ε is expressed by the complement of the solid particle volume fraction, that is, ε = 1-α(x). Therefore, the liquid volume in the grid can be calculated:

[0115] V fluid =(1-α)·ε·V cell (27)

[0116] At this time, since the particles are unanalyzed particles, the particle dynamic parameters are solved by Newton's second law:

[0117]

[0118] m p ,v,I p , ω is the particle mass, velocity, moment of inertia and angular velocity; V p is the particle volume, F c ,g,p,F s 、F p 、T c They represent the contact force, gravity, fluid pressure, surface tension, fluid-particle interaction force and contact force torque. c The fluid-particle interaction term F p Various coupling terms may be included, such as drag, lift, and virtual mass forces. Fluid drag is relatively dominant, while other hydrodynamic forces are sometimes neglected. Therefore, only one term related to drag will be accepted as a fluid-particle interaction:

[0119] F p =F drag (30)

[0120] The drag force is the effective drag force calculated by some analytical or empirical correlation. The particle's velocity, position, and angular velocity states are then updated using the Symplectic Euler scheme.

[0121] The momentum equation of the flow field is:

[0122]

[0123] Where ρ and μ are the density and viscosity of the mixture, defined as:

[0124] ρ=γρ1+(1-γ)ρ g (32)

[0125] μ=γμ1+(1-γ)u g (33)

[0126] When a particle passes through a fluid interface, the structure of the fluid interface is described by a function γ that represents the volume fraction of the liquid phase. Its value is 1 for liquid, 0 for gas, and 0<γ<1 at the interface. The interface motion is then given by the γ advection equation based on the fluid velocity:

[0127]

[0128] Calculate the surface tension per unit volume by using the continuum-surface force model

[0129]

[0130] Where σ is the surface tension coefficient and the curvature κ of the free surface is calculated as:

[0131]

[0132] S4: Calculating physical parameters of multi-scale particle multiphase flow field according to the physical information solved by the analytical particles and the unanalyzed particles;

[0133] Specifically, the multi-scale particle multiphase flow field physical parameters include the reaction force source term f acting on large and small scale particles p , the calculation process is as follows:

[0134]

[0135] The local cavity fraction ε is equal to the value of the fluid unit containing the particle, and the flow velocity u is obtained by linear interpolation at the center of the particle. The coefficient β is calculated as:

[0136]

[0137] d p is the particle size. D is the drag coefficient of a single sphere:

[0138]

[0139] The particle Reynolds number is defined as:

[0140]

[0141] The fluid-particle interaction forces of different particles are calculated based on the local flow conditions and particle states. Their reaction forces become a source term f p , added to the right side of the volume-averaged Navier-Stokes equations. In the fluid solver, these dispersed forces are collected from the particles and distributed as the volume force for each calculation, expressed as:

[0142]

[0143] ε1 is the void fraction in the Euler element, and the calculated result is:

[0144]

[0145] Among them, V cell and V p are the volumes of the grid and particles, respectively, and f p is the fractional volume force on a particle located in the considered grid. ε min is a value that is set slightly greater than 0 to avoid cells being completely occupied by a particle.

[0146] As can be seen from the above embodiments, the present application has established a solution algorithm for the interaction between the large and small scale particle (i.e., analytical and non-analytical particle) model and different continuous phases. The above method is based on the fluid volume method, the immersed boundary method, and the discrete element method, and determines the calculation method used for particles of different sizes in the calculation problem based on the grid scale. The discrete particles can be solid particles, discrete bubbles or droplets.

[0147] Corresponding to the aforementioned embodiment of the method for calculating the multi-scale particle multiphase flow field, the present application also provides an embodiment of a device for calculating the multi-scale particle multiphase flow field.

[0148] Figure 3 is a block diagram of a computing device for a multi-scale particle multiphase flow field according to an exemplary embodiment. Figure 3 , the device comprises:

[0149] The particle determination module 1 is used to determine the large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow according to the preset computational domain grid size;

[0150] The first solution module 2 is used to obtain the flow field medium parameters of the analytical particles and the physical parameters of the discrete particles, and solve the flow field information and the physical information of the multiphase flow by using the immersed boundary method;

[0151] The second solution module 3 is used to obtain the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, solve the particle volume fraction by using the statistical kernel method, and solve the physical information of the multiphase flow by using the fluid volume method based on the particle volume fraction;

[0152] The calculation module 4 is used to calculate the physical parameters of the multi-scale particle multiphase flow field according to the physical information solved by the analytical particles and the unanalyzed particles.

[0153] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0154] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0155] Accordingly, the present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for calculating the multi-scale particle multiphase flow field. Figure 4 As shown, a hardware structure diagram of a computing device for a multi-scale particle multiphase flow field provided by an embodiment of the present invention is provided for any device with data processing capability, except Figure 4 In addition to the processor, memory, DMA controller, disk, and non-volatile memory shown, any device with data processing capabilities in which the apparatus in the embodiment is located may also include other hardware, which will not be described in detail, generally based on the actual functions of the device with data processing capabilities.

[0156] Accordingly, the present application also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the calculation method of the multi-scale particle multiphase flow field as described above. The computer-readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the aforementioned embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), an SD card, a flash card (Flash Card), etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of any device with data processing capabilities and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store data that has been output or is to be output.

[0157] 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.

[0158] 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 method for calculating multi-scale particle multiphase flow field, characterized in that: include: According to the pre-set computational domain grid size, large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow are determined; Obtaining the flow field medium parameters of the analytical particles and the physical parameters of the discrete particles, and solving the flow field information and the physical information of the multiphase flow by using the immersed boundary method; Obtaining the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, solving the particle volume fraction by using the statistical kernel method, and solving the physical information of the multiphase flow by using the fluid volume method based on the particle volume fraction; The physical parameters of the multi-scale particle multiphase flow field are calculated based on the physical information solved by the analytical particles and the unanalyzed particles.

2. The method for calculating a multi-scale particle multiphase flow field according to claim 1, characterized in that: According to the preset computational domain grid size, large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow are determined, including: Determine the mesh size of the created fluid domain; According to the fluid domain grid size, the particle size is compared with the grid size. Particles larger than 8 times the grid size are analyzed particles, and particles smaller than or equal to the grid size are unanalyzed particles.

3. The method for calculating a multi-scale particle multiphase flow field according to claim 1, characterized in that: Obtaining medium parameters and physical parameters of discrete particles in the analytical particle flow field, and solving physical information of multiphase flow using the immersed boundary method, including: Obtaining medium parameters and physical parameters of discrete particles in the analytical particle flow field; According to the medium parameters and physical parameters, the flow field information is obtained by solving the Navier-Stokes equation; the particle boundary is described by the immersed boundary method, and the particle physical information is obtained by solving; The multiphase flow physical information is obtained by solving the flow field information and the particle physical information.

4. The method for calculating a multi-scale particle multiphase flow field according to claim 1, characterized in that: Obtain the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, use the statistical kernel method to solve the particle volume fraction, and use the fluid volume method to solve the physical information of the multiphase flow based on the particle volume fraction, including: Obtain the interface parameters of each medium component and the physical parameters of discrete particles in the unanalyzed particle flow field; According to the physical parameters of the discrete particles, a statistical kernel method is used to solve the volume fraction of the particles in the flow field grid; According to the interface parameters of each medium component in the unanalyzed particle flow field and the volume fraction of particles in the flow field, the physical information of the multiphase flow is solved by the fluid volume method.

5. A computing device for multi-scale particle multiphase flow field, characterized in that: include: The particle determination module is used to determine the large-scale analytical particles and small-scale unanalyzed particles in the multiphase flow according to the preset computational domain grid size; A first solution module is used to obtain the flow field medium parameters of the analytical particles and the physical parameters of the discrete particles, and solve the flow field information and the physical information of the multiphase flow by using the immersed boundary method; The second solution module is used to obtain the interface parameters of each medium composition and the physical parameters of discrete particles in the unanalyzed particle flow field, solve the particle volume fraction by using the statistical kernel method, and solve the physical information of the multiphase flow by using the fluid volume method based on the particle volume fraction; The calculation module is used to calculate the physical parameters of the multi-scale particle multiphase flow field according to the physical information solved by the analytical particles and the unanalyzed particles.

6. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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