Mesoscopic hydrodynamics method and system for non-equilibrium compressible fluids

Abstract

The application discloses a mesoscopic kinetic method and system for non-equilibrium compressible fluid, and the method comprises the following steps: obtaining macroscopic physical quantities according to the initialization of specific working conditions of a non-equilibrium compressible fluid system; solving a discrete equilibrium state distribution function from the relationship between the macroscopic physical quantities and kinetic moments, and obtaining a first discrete distribution function by Taylor expansion on the discrete equilibrium state distribution function; determining a second discrete distribution function according to the direction of discrete velocity and boundary conditions set according to the specific working conditions of the non-equilibrium compressible fluid system; obtaining kinetic equations meeting conservation conditions after processing the first discrete distribution function and the second discrete distribution function; and updating the macroscopic physical quantities based on the kinetic equations, and judging whether the time iteration step number meets a preset loop termination condition. The mesoscopic kinetic method and system for non-equilibrium compressible fluid provided in the embodiment of the application can accurately depict detailed fluid mechanics and thermodynamics non-equilibrium behaviors.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fluid dynamics simulation, and in particular to a mesoscopic kinetic method and system for non-equilibrium compressible fluid. BACKGROUND

[0002] Compressible fluid systems exist widely in many scientific and engineering fields, and are important physical problems that scientists and engineers are concerned about. In the field of aerospace, for example, high-speed aircrafts face significant compressibility and non-equilibrium effects in the rarefied atmosphere. With the rapid development of computer technology, numerical simulation provides an effective means for in-depth study of compressible fluid systems. However, compressible fluid systems usually involve a large number of nonlinear, unstable and non-equilibrium processes, and contain multiple orders of magnitude of time and space scales, which poses a great challenge to the applicability of traditional numerical methods. On the one hand, traditional macroscopic methods are mainly based on the assumption of continuous medium, such as the commonly used Navier-Stokes equation set, which contains nonlinear convection terms that are difficult to handle, and cannot accurately describe and measure the significant and rich discrete effects and non-equilibrium effects in related compressible fluid systems. On the other hand, traditional microscopic methods, such as molecular dynamics, can track each molecule in the physical system in real time, and then obtain macroscopic physical quantities by statistically processing a large number of molecules. Such methods have the advantages of high physical accuracy and rich physical information, but have the disadvantage of being difficult to efficiently simulate physical systems with large time and space scales.

[0003] As a bridge between macroscopic and microscopic methods, mesoscopic methods provide a feasible approach to accurately and efficiently simulate fluid systems. The discrete Boltzmann method (DBM) is a mesoscopic kinetic method that is suitable for non-equilibrium, compressible fluid systems, and can solve the problems of insufficient physical accuracy of traditional macroscopic methods and limited simulation time and space scales of microscopic methods. However, DBM has the disadvantage of numerical instability when describing detailed fluid mechanics and thermodynamics non-equilibrium behavior.

[0004] Therefore, how to accurately and stably describe detailed fluid mechanics and thermodynamics non-equilibrium behavior has become a technical problem to be solved by those skilled in the art. SUMMARY

[0005] The present application provides a mesoscopic kinetic method and system for non-equilibrium compressible fluid, which is used to solve the problem of numerical instability, and to achieve the effect of accurately describing detailed fluid mechanics and thermodynamics non-equilibrium behavior.

[0006] To solve the above technical problems, the present application provides a mesoscopic kinetic method for non-equilibrium compressible fluid, comprising:

[0007] initializing macroscopic physical quantities according to specific working conditions of the non-equilibrium compressible fluid system;

[0008] solving discrete equilibrium distribution functions according to the macroscopic physical quantities and the relationship between the kinetic moments, and substituting the discrete equilibrium distribution functions into a Taylor expansion of the discrete distribution functions to obtain first discrete distribution functions;

[0009] determining second discrete distribution functions according to the directions of the discrete velocities and boundary conditions set based on the specific working conditions of the non-equilibrium compressible fluid system;

[0010] performing kinetic moment summation processing on the first discrete distribution functions and the second discrete distribution functions to obtain kinetic equations satisfying conservation conditions;

[0011] updating the macroscopic physical quantities iteratively based on the kinetic equations, and determining whether a time iteration step number satisfies a preset loop termination condition; if the time iteration step number does not satisfy the loop termination condition, repeating the above steps to update the macroscopic physical quantities according to the updated kinetic equations until the loop termination condition is reached.

[0012] As one of the preferred solutions, the macroscopic physical quantities include density, momentum, and energy.

[0013] As one of the preferred solutions, the first discrete distribution functions are discrete distribution functions inside a physical field, and the second discrete distribution functions are discrete distribution functions at boundaries.

[0014] As one of the preferred solutions, the calculation formula of the discrete distribution functions is

[0015]

[0016] where f i eq (r, t) is a discrete equilibrium distribution function at time t and position r, f i eq (r-v i Δt, t-Δt) is a discrete equilibrium distribution function at time t-Δt and position r-v i Δt, Δt is a time step, and τ is a relaxation time.

[0017] As one of the preferred solutions, the calculation formula of the kinetic equations is

[0018]

[0019] where W = (ρ J E) T is a conserved quantity, is the flux, ρ represents the density, J represents the momentum, E represents the energy, and t is time, is the Hamiltonian operator, f i is the discrete distribution function, v i is the discrete velocity, which is related to the translational kinetic energy of the molecule, n i is used to describe the internal energy corresponding to the rotation and vibration of the molecule, and the superscript T represents matrix transposition.

[0020] As one of the preferred solutions, the conservation condition is

[0021] ρ = ∑ i f i

[0022] J = ∑ i f i v i

[0023]

[0024] where ρ represents the density, J represents the momentum, E represents the energy, and v i is the discrete velocity, η i is used to describe the internal energy corresponding to the rotation and vibration of the molecule.

[0025] As one of the preferred solutions, the calculation formula of the discrete equilibrium distribution function is

[0026] f eq =C -1 M

[0027] wherein, the elements of the discrete equilibrium distribution function are M = (M1M2…M N ) T the elements of the kinetic tensor are the elements of the kinetic tensor, and the square matrix C -1 is the inverse matrix of C, which is used to connect the kinetic tensor space of the discrete distribution function and the velocity space.

[0028] Another embodiment of the present application provides a mesoscopic kinetic system for a non-equilibrium compressible fluid, comprising:

[0029] An initialization module is configured to initialize to obtain macroscopic physical quantities according to specific working conditions of a non-equilibrium compressible fluid system;

[0030] A first discrete distribution function module is configured to solve a discrete equilibrium distribution function from a kinetic tensor relationship required by the macroscopic physical quantities and the discrete equilibrium distribution function, and to obtain a first discrete distribution function by Taylor expansion of the discrete equilibrium distribution function.

[0031] a second discrete distribution function module configured to determine a second discrete distribution function according to a direction of the discrete velocity and boundary conditions set based on a specific working condition of the non-equilibrium compressible fluid system;

[0032] a processing module configured to perform kinetic moment summation processing on the first discrete distribution function and the second discrete distribution function to obtain kinetic equations satisfying a conservation condition;

[0033] a judging module configured to update the macroscopic physical quantity based on the kinetic equations, and judge whether a time iteration step number satisfies a preset loop termination condition; if the time iteration step number does not satisfy the iteration loop termination condition, repeating the above steps to update the macroscopic physical quantity according to the updated kinetic equations until a preset iteration loop condition is reached.

[0034] Another embodiment of the present application provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, so that the computer device performs steps of implementing the above method.

[0035] Another embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement steps of the above method.

[0036] Compared with the prior art, the embodiment of the present application has at least one of the following advantages:

[0037] (1) Compared with the traditional macroscopic method, the present application converts complex nonlinear partial differential equations into linear equations, which can stably and accurately depict and measure detailed fluid mechanics and thermodynamics non-equilibrium behavior;

[0038] (2) Compared with the existing mesoscopic kinetic DBM, the method of the present application has good numerical stability, can take a larger time step, and can be applied to simulate non-equilibrium and compressible fluid systems. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is a flowchart of a mesoscopic kinetic method for non-equilibrium compressible fluid in one embodiment of the present application;

[0040] Figure 2 is a program flowchart of a mesoscopic kinetic method for non-equilibrium compressible fluid in one embodiment of the present application;

[0041] Figure 3 is a structural block diagram of a mesoscopic kinetic system for non-equilibrium compressible fluid in one embodiment of the present application;

[0042] Figure 4 is a schematic diagram of a mesoscopic kinetic processing device for a non-equilibrium compressible fluid in one of the embodiments of the present application.

[0043] Reference signs:

[0044] Wherein, 11, initialization module; 12, first discrete distribution function module; 13, second discrete distribution function module; 14, processing module; 15, judgment module; 21, processor; 22, memory. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments of the present application. The purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0046] In the description of the present application, the terms "first", "second", "third" and the like are only used for description purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second", "third" and the like can explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0047] In the description of the present application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present application have the same meaning as understood by those skilled in the art. The terms used in the specification of the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the present application. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0048] An embodiment of the present application provides a mesoscopic kinetic method for a non-equilibrium compressible fluid, specifically, please refer to Figure 1 and Figure 2 , Figure 1 shows a flowchart of a mesoscopic kinetic method for a non-equilibrium compressible fluid in one of the embodiments of the present application, Figure 2 shows a program flowchart of a mesoscopic kinetic method for a non-equilibrium compressible fluid in one of the embodiments of the present application, and the specific steps are as follows:

[0049] S1: initialization according to the specific working condition of the non-equilibrium compressible fluid system to obtain macroscopic physical quantity;

[0050] S2: solving the discrete equilibrium distribution function from the relationship of the macroscopic physical quantity and the kinetic moment required by the discrete equilibrium distribution function, and obtaining a first discrete distribution function by Taylor expansion of the discrete equilibrium distribution function;

[0051] S3: determining a second discrete distribution function according to the direction of the discrete velocity and the boundary condition set based on the specific working condition of the non-equilibrium compressible fluid system;

[0052] S4: obtaining a kinetic equation satisfying the conservation condition after kinetic moment summation processing of the first discrete distribution function and the second discrete distribution function;

[0053] S5: updating the macroscopic physical quantity based on the kinetic equation, and judging whether the time iteration step number meets the preset loop termination condition; if the time iteration step number does not meet the loop termination condition, repeating the above steps to update the macroscopic physical quantity according to the updated kinetic equation until the loop termination condition is met.

[0054] Preferably, the macroscopic physical quantity can be density, momentum, energy, temperature, velocity, pressure and kinetic moment of the discrete distribution function.

[0055] The present scheme starts from the discrete Boltzmann equation, which is as follows:

[0056]

[0057] Where, t is time, is Hamilton operator, f i is the discrete distribution function, v i is the discrete velocity, which is related to the translational kinetic energy of the molecule. At the same time, the symbol η i is introduced in the present scheme to describe the internal energy corresponding to the rotation and vibration of the molecule.

[0058] It should be noted that the discrete velocity distribution function f i is the discrete form of the particle velocity distribution function f in the velocity space. Therefore, the discrete Boltzmann equation is the result of special discretization of the Boltzmann equation in the velocity space.

[0059] In theory, the discrete velocity distribution function f i , the time derivative and the Hamilton operator can be expanded with respect to the small number ε of the order of Knudsen, i.e.

[0060]

[0061] Where, f i(j) is the j-th order small quantity, is the j-th order small quantity, is the 1st order small quantity, subscript j = 1, 2, …. Substituting the above three equations into the discrete Boltzmann equation, the relationship of small quantities of different orders ε can be obtained, i.e. at the 0th order small quantity level: i (0) = f i eq at the 1st order small quantity level: O(ε 1 ): Then, the two equations are combined with the following Taylor expansion:

[0062]

[0063]

[0064]

[0065] where f i eq (r, t) is the discrete equilibrium distribution function at time t and position r, f i eq (r - v i Δt, t - Δt) is the discrete equilibrium distribution function at time t - Δt and position r - v i Δt, and Δt is the time step.

[0066] Substituting the expression of f i (1) into the expansion of the discrete distribution function f i = f i (0) + f i (1) + f i (2) + …, and ignoring the second and higher order small quantities, the discrete distribution function at time t and position r can be finally obtained as:

[0067]

[0068] At the same time, the summation symbols ∑ i , ∑ i v i and are applied to the discrete Boltzmann equation, respectively, and the conservation conditions: density ρ = ∑ i f i = ∑ i f i eq , momentum J = ∑ i f i v i = ∑​i f i eq v i , and energy Then we can get

[0069]

[0070] Introducing column vector W = (p J E) T and column vector represent the conserved quantity and flux, respectively, where the superscript T represents the matrix transpose, and the above equation is summarized as follows:

[0071]

[0072] Based on the above kinetic equation, the iteration macroscopic physical quantity is updated, and it is judged whether the time iteration step number meets the preset loop termination condition; if the time iteration step number does not meet the loop termination condition, the above steps are repeated, the macroscopic physical quantity is updated according to the updated kinetic equation, until the loop termination condition is reached.

[0073] When applied to numerical simulation, the kinetic equation needs to be discretized in velocity, time and space, and the expression of the discrete velocity is:

[0074]

[0075] In the formula, v a is an adjustable variable, which is used to adjust the size of the discrete velocity; the subscript i = 0, 1, 2, …, N-1 is used to mark the direction of the discrete velocity, wherein N = 9 represents the number of discrete velocities. At the same time, η i is set to

[0076]

[0077] In the formula, η a , η b and η c are adjustable variables.

[0078] For the time partial derivative of the kinetic equation, the first-order Runge-Kutta method can be used for processing, and other formats also belong to the scope covered by the present application. When the first-order Runge-Kutta method is used, the kinetic equation of the model constructed by the present application will be transformed into the following form:

[0079]

[0080] In the formula, W = W t represents the conserved quantity at time t, W new = W t+Δt represents the conserved quantity at time t+Δt, U = Ut This represents the flow rate at time t.

[0081] The spatial partial differential of the kinetic equations can be processed using a second-order accurate, waveless, parameterless dissipative finite difference scheme. Other schemes are also within the scope of this invention. When using a second-order accurate, waveless, parameterless dissipative finite difference scheme, the kinetic equations of this scheme can be further transformed into...

[0082]

[0083] In the formula

[0084]

[0085]

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] Where, j α This represents the j-th mesh layer in the α = x or y direction, and H indicates that it depends on H. L With H R The function, H L Indicates dependence With minmod functions, H R Indicates dependence With the minmod function, Indicates dependence The function, Indicates dependence The function, f i + The column vector composed of the four lower-order kinetic moments, f i - The column vector f is composed of four lower-order kinetic moments. i + This indicates that it depends on v. iα A function f that takes values i - This indicates that it depends on v.iα Another function to take a value, v iα Represents discrete velocity v i In the α-direction, the function minmod[X,Y] is defined as follows: when X and Y have the same algebraic sign, the variable with the smaller absolute value between X and Y is taken as the value of the function; when X and Y have opposite algebraic signs, zero is taken as the value of the function.

[0093] For details, please see Figure 3 , Figure 3 The diagram shown is a structural block diagram of a mesoscopic kinetic system for non-equilibrium compressible fluids according to one embodiment of the present invention, comprising:

[0094] Initialization module 11 is used to initialize and obtain macroscopic physical quantities according to the specific working conditions of the non-equilibrium compressible fluid system.

[0095] The first discrete distribution function module 12 is used to solve the discrete equilibrium distribution function from the relationship between the macroscopic physical quantity and the discrete equilibrium distribution function, and to perform a Taylor expansion on the discrete equilibrium distribution function to obtain the first discrete distribution function.

[0096] The second discrete distribution function module 13 is used to determine the second discrete distribution function based on the direction of the discrete velocity and the boundary conditions set based on the specific working conditions of the non-equilibrium compressible fluid system.

[0097] Processing module 14 is used to obtain a kinetic equation that satisfies the conservation conditions by performing kinetic moment summation on the first discrete distribution function and the second discrete distribution function;

[0098] The judgment module 15 is used to update the macroscopic physical quantity based on the kinetic equation and determine whether the number of time iteration steps meets the preset cycle termination condition. If the number of time iteration steps does not meet the iteration cycle termination condition, the above steps are repeated to update the macroscopic physical quantity according to the updated kinetic equation until the preset iteration cycle condition is reached.

[0099] One embodiment of the present invention provides a mesoscopic kinetic system for non-equilibrium compressible fluids. For details, please refer to [link to specific documentation]. Figure 4 , Figure 4The processing device for mesoscopic hydrodynamics method for non-equilibrium compressible fluid in one of the embodiments of the present application, the processing device for mesoscopic hydrodynamics method for non-equilibrium compressible fluid 20 can include, but not limited to, a processor 21, a memory 22. The processing device for mesoscopic hydrodynamics method for non-equilibrium compressible fluid 20 provided by the embodiments of the present application includes a processor 21, a memory 22 and a computer program stored in the memory 22 and configured to be executed by the processor 21, when the processor 21 executes the computer program, the steps in the above-mentioned embodiments of the mesoscopic hydrodynamics method for non-equilibrium compressible fluid are implemented, such as steps S1-S5 in the above-mentioned embodiments of the mesoscopic hydrodynamics method for non-equilibrium compressible fluid; or, the processor 21 executes the computer program to implement the functions of each module in the above-mentioned device embodiments, such as the initialization module 11. Figure 1

[0100] For example, the computer program can be divided into one or more modules, the one or more modules are stored in the memory 22 and executed by the processor 21 to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the processing device for mesoscopic hydrodynamics method for non-equilibrium compressible fluid 20. For example, the computer program can be divided into an initialization module 11, a first discrete distribution function module 12, a second discrete distribution function module 13, a processing module 14 and a judgment module 15, and the specific functions of each module are as follows:

[0101] The initialization module 11 is used to initialize to obtain macroscopic physical quantities according to the specific working conditions of the non-equilibrium compressible fluid system;

[0102] The first discrete distribution function module 12 is used to solve the discrete equilibrium state distribution function from the macroscopic physical quantities and the hydrodynamic moment relationship required by the discrete equilibrium state distribution function, and to obtain the first discrete distribution function by Taylor expansion of the discrete equilibrium state distribution function;

[0103] The second discrete distribution function module 13 is used to determine the second discrete distribution function according to the direction of the discrete velocity and the boundary conditions set based on the specific working conditions of the non-equilibrium compressible fluid system;

[0104] The processing module 14 is used to obtain the hydrodynamic equation satisfying the conservation condition after the hydrodynamic moment summation processing of the first discrete distribution function and the second discrete distribution function;

[0105] ​The judging module 15 is configured to judge whether the time iteration step number meets a preset loop termination condition based on the updated iteration of the kinetic equation of the macroscopic physical quantity; if the time iteration step number does not meet the iteration loop termination condition, repeat the above steps, update the macroscopic physical quantity according to the updated kinetic equation, until the preset iteration loop condition is met.

[0106] Those skilled in the art can understand that the schematic diagram is only an example of the processing device for mesoscopic kinetics of non-equilibrium compressible fluid, and does not constitute a limitation on the processing device 20 for mesoscopic kinetics of non-equilibrium compressible fluid, which can include more or less components than the diagram, or combine certain components, or different components, for example, the processing device 20 for mesoscopic kinetics of non-equilibrium compressible fluid can also include input and output devices, network access devices, buses, etc.

[0107] The processor 21 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The processor 21 is the control center of the processing device 20 for mesoscopic kinetics of non-equilibrium compressible fluid, and connects various parts of the processing device 20 for mesoscopic kinetics of non-equilibrium compressible fluid through various interfaces and lines.

[0108] The memory 22 can be used to store the computer programs and / or modules, and the processor 21 realizes various functions of the mesoscopic dynamics processing device 20 for non-equilibrium compressible fluids by running or executing the computer programs and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, and the like; and the data storage area can store data created according to the use of the program and the like. In addition, the memory 22 can include a high-speed random access memory, and can also include a non-volatile memory such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0109] The modules integrated in the mesoscopic dynamics processing device 20 for non-equilibrium compressible fluids can be stored in a computer-readable storage medium if they are realized in the form of software function units and sold or used as independent products. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be realized. The computer program includes computer program code, which can be in the form of source code, object code, an executable file, or some intermediate form, etc. The computer-readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0110] It can be understood by those of ordinary skill in the art that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, and the program can include the processes of the above-mentioned various method embodiments when executed. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0111] Accordingly, the embodiments of the present application provide a computer readable storage medium comprising a stored computer program, wherein the computer program, when executed, controls a device in which the computer readable storage medium is located to perform the steps in the mesoscopic hydrodynamics method for non-equilibrium compressible fluids as described in the above embodiments, for example Figure 1 S1-S5 described in the above embodiments.

[0112] Compared with the prior art, the embodiments of the present application have at least one of the following advantages:

[0113] (1) Compared with the traditional macroscopic method, the present application converts the complex nonlinear partial differential equation group into a linear equation group, which can stably and accurately depict and measure the detailed fluid mechanics and thermodynamics non-equilibrium behavior.

[0114] (2) Compared with the existing mesoscopic hydrodynamics DBM, the method of the present application has good numerical stability, can take a larger time step, and can be applied to simulate non-equilibrium, compressible fluid systems.

[0115] 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 scope of protection of the patent of the present application should be subject to the appended claims.

Claims

1. A mesoscopic kinetic method for non-equilibrium compressible fluids, characterized in that, include: Step 1: Initialize the system based on the specific operating conditions of the non-equilibrium compressible fluid system to obtain macroscopic physical quantities; Step 2: Solve for the discrete equilibrium distribution function from the relationship between the macroscopic physical quantities and the kinetic moments, and substitute the discrete equilibrium distribution function into the Taylor expansion of the discrete distribution function to obtain the first discrete distribution function; Step 3: Determine the second discrete distribution function based on the direction of the discrete velocity and the boundary conditions set according to the specific working conditions of the non-equilibrium compressible fluid system; Step 4: Summate the kinetic moments of the first and second discrete distribution functions to obtain the kinetic equations that satisfy the conservation conditions, wherein the formula for calculating the discrete distribution function is: in, For at any time Location is The discrete equilibrium distribution function, For at any time Location is The discrete equilibrium distribution function, For time step, Relaxation time; The formula for calculating the kinetic equation is as follows: in, For conservation of quantity, For circulation volume, Indicates density, Indicates momentum. Indicates energy. For Hamiltonian operators, The discrete distribution function includes a first discrete distribution function and a second discrete distribution function. The first discrete distribution function is the discrete distribution function inside the physical field, and the second discrete distribution function is the discrete distribution function at the boundary. The velocity is discrete and is related to the translational kinetic energy of the molecule. Used to describe the internal energy corresponding to molecular rotation and vibration, the superscript T indicates matrix transpose; Step 5: Update the macroscopic physical quantity based on the kinetic equation and determine whether the number of time iteration steps meets the preset cycle termination condition; if the number of time iteration steps does not meet the cycle termination condition, repeat steps 2 to 5 above, update the macroscopic physical quantity according to the updated kinetic equation, until the cycle termination condition is met.

2. The mesoscopic kinetic method for non-equilibrium compressible fluids as described in claim 1, characterized in that, The macroscopic physical quantities include density, momentum, and energy.

3. The mesoscopic kinetic method for non-equilibrium compressible fluids as described in claim 1, characterized in that, The conservation condition is: 。 4. The mesoscopic kinetic method for non-equilibrium compressible fluids as described in claim 1, characterized in that, The formula for calculating the discrete equilibrium distribution function is as follows: in, The elements are the discrete equilibrium distribution function. The elements are kinetic moments, square matrices. yes The inverse matrix is ​​used to connect the kinetic moment space and the velocity space of the discrete distribution function.

5. A mesoscopic kinetic system for non-equilibrium compressible fluids, characterized in that, The system includes: The initialization module is used to initialize and obtain macroscopic physical quantities based on the specific operating conditions of the non-equilibrium compressible fluid system. The first discrete distribution function module is used to solve the discrete equilibrium distribution function from the relationship between the macroscopic physical quantity and the discrete equilibrium distribution function, and to obtain the first discrete distribution function by performing a Taylor expansion on the discrete equilibrium distribution function. The second discrete distribution function module is used to determine the second discrete distribution function based on the direction of the discrete velocity and the boundary conditions set based on the specific working conditions of the non-equilibrium compressible fluid system. The processing module is used to perform kinetic moment summation on the first discrete distribution function and the second discrete distribution function to obtain a kinetic equation that satisfies the conservation conditions, wherein the calculation formula for the discrete distribution function is as follows: in, For at any time Location is The discrete equilibrium distribution function, For at any time Location is The discrete equilibrium distribution function, For time step, Relaxation time; The formula for calculating the kinetic equation is as follows: in, For conservation of quantity, For circulation volume, Indicates density, Indicates momentum. Indicates energy. Hamiltonian operator, The discrete distribution function includes a first discrete distribution function and a second discrete distribution function. The first discrete distribution function is the discrete distribution function inside the physical field, and the second discrete distribution function is the discrete distribution function at the boundary. The velocity is discrete and is related to the translational kinetic energy of the molecule. Used to describe the internal energy corresponding to molecular rotation and vibration, the superscript T indicates matrix transpose; The judgment module is used to update the macroscopic physical quantity based on the kinetic equation and determine whether the number of time iteration steps meets the preset loop termination condition. If the number of time iteration steps does not meet the iteration loop termination condition, the steps of the first discrete distribution function module, the second discrete distribution function module, the processing module and the judgment module are repeated to update the macroscopic physical quantity according to the updated kinetic equation until the preset iteration loop condition is reached.

6. A computer device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the mesoscopic kinetic method for nonequilibrium compressible fluids as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the device containing the computer-readable storage medium executes the computer program, it implements the mesoscopic kinetic method for non-equilibrium compressible fluids as described in any one of claims 1 to 4.

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