Large scale neutral-macroscopic-microscopic dynamics coupling numerical simulation method based on plasma statistical physics theory

Abstract

The application discloses a large-scale neutral-macroscopic dynamics-microscopic dynamics coupling numerical simulation method based on a plasma statistical physics theory and relates to the technical field of plasma physics research, and comprises the following steps: step 1, obtaining initial physical variables; step 2, performing numerical discrete processing on the initial physical variables to obtain average flow field information on a neutral scale; step 3, performing macroscopic dynamics coupling processing on the average flow field information to obtain an intermediate result after coupling; step 4, performing local refinement processing on the intermediate result after coupling by using a microscopic dynamics numerical discrete method to obtain a refined particle dynamics simulation result; step 5, comprehensively processing the average flow field information, the intermediate result after coupling and the refined particle dynamics simulation result by using a cross-scale coupling algorithm to obtain a cross-time-space coupling numerical simulation result; and step 6, outputting the numerical simulation result and analyzing the evolution law of a solar electromagnetic storm or corresponding plasma dynamic behavior.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of plasma physics research, and more particularly to a large-scale neutral-macroscopic dynamics-microscopic kinetics coupling numerical simulation method based on plasma statistical physics theory. BACKGROUND

[0002] In the field of plasma physics research, especially for the study of complex systems such as solar electromagnetic storms, plasma confinement of controlled nuclear fusion devices, and interstellar medium multiphase flow, it is crucial to accurately simulate the multi-scale dynamic behavior of plasma from the macroscopic to the microscopic. Traditional numerical simulation methods often face significant limitations when dealing with such problems, mainly in the scale separation and coupling between macroscopic dynamics and microscopic kinetics.

[0003] In the prior art, plasma simulation usually adopts two independent methods: macroscopic method mainly based on magnetohydrodynamics (MHD) theory, which describes the overall flow, magnetic field distribution and energy transfer of plasma by solving macroscopic partial differential equations, suitable for large-scale (such as macroscopic evolution of solar storm) simulation. However, this method is difficult to accurately capture the physical phenomena of microscopic scale (such as particle-level perturbation, collision process), especially the non-equilibrium distribution and high-frequency fluctuation characteristics between particles. On the other hand, microscopic methods such as direct simulation Monte Carlo (DSMC) or particle-in-cell (PIC) method can describe the microscopic dynamics of plasma by tracking the motion trajectories and interactions of a large number of microscopic particles, but the computational cost is extremely high, and it is difficult to extend to the macroscopic scale, which cannot effectively simulate the overall dynamic characteristics of large-scale plasma.

[0004] In addition, the existing technology often uses simplified turbulence models or empirical formulas when dealing with turbulent flow in plasma, which is difficult to accurately describe the spatial distribution and temporal evolution of turbulent dissipation terms, resulting in significant errors in the simulation results in terms of turbulent energy transfer and dissipation. At the same time, for multi-component, multi-abundance, and multi-isotope plasma systems, traditional methods lack an effective description framework, making it difficult to handle the complex interactions between real fluids (such as electrons, protons, and various ions) and field pseudo-fluids (such as electromagnetic fields).

[0005] Therefore, developing a numerical simulation method that can efficiently couple large-scale neutral, macroscopic dynamics, and microscopic kinetics is of great significance for in-depth understanding of the multi-scale physical mechanisms of plasma, improving the accuracy of space weather forecasting, and optimizing plasma confinement of controlled nuclear fusion devices, etc. SUMMARY

[0006] Therefore, the application provides a large-scale neutral-macroscopic dynamics-microscopic dynamics coupling numerical simulation method based on a plasma statistical physics theory, which can realize efficient coupling numerical simulation, deeply understand multi-scale physical mechanisms of the plasma, improve spatial weather forecast accuracy and optimize plasma confinement of a controllable nuclear fusion device.

[0007] In order to achieve the above object, the application adopts the following technical scheme: a large-scale neutral-macroscopic dynamics-microscopic dynamics coupling numerical simulation method based on a plasma statistical physics theory, comprising:

[0008] Step 1: obtaining initial physical variables according to attribute parameters of the plasma;

[0009] Step 2: performing numerical discrete processing on the initial physical variables to obtain average flow field information on a neutral scale;

[0010] Step 3: performing macroscopic dynamics coupling processing on the average flow field information to obtain an intermediate result after coupling;

[0011] Step 4: performing local refinement processing on the intermediate result after coupling by using a microscopic dynamics numerical discrete method to obtain a refined particle dynamics simulation result

[0012] Step 5: comprehensively processing the average flow field information, the intermediate result after coupling and the refined particle dynamics simulation result by using a cross-scale coupling algorithm to obtain a cross-time-space coupling numerical simulation result;

[0013] Step 6: outputting the numerical simulation result and analyzing evolution rules of solar electromagnetic storm or corresponding plasma dynamic behavior.

[0014] Preferably, the step 1 simultaneously describes multi-component, multi-abundance and multi-isotope attributes of real fluid and field pseudo-fluid by using a generalized distribution function.

[0015] The generalized distribution function is decomposed into a low-frequency average part and a high-frequency perturbation part, the statistical characteristics of the real fluid in the turbulent flow attribute are described by using the low-frequency average part, and the statistical characteristics of the field pseudo-fluid are described by using the high-frequency perturbation part, so as to obtain the initial physical variables.

[0016] Preferably, the initial physical variables are discretely processed based on a large-time-space neutral scale, comprising: using a grid model, according to a preset space scale parameter and a time step, using conservation equations and turbulent dissipation terms for describing neutral flow in the plasma statistical physics theory, so as to obtain the average flow field information on the neutral scale.

[0017] Preferably, a function expression of the large-time-space neutral scale is as follows:

[0018]

[0019] wherein, are different physical properties, including density, velocity, current, magnetic field, pressure;

[0020] are different particle species, including electrons, ions, neutral particles;

[0021] are different spatial scales, including flow property large scale, flow property macroscopic kinetic scale, particle property microscopic kinetic scale;

[0022] is: the time variation characteristic of the generalized distribution function corresponding to the neutral particles;

[0023] is: the generalized distribution function corresponding to the neutral particles;

[0024] is: the neutral fluid velocity;

[0025] is: the viscosity correlation coefficient related to the neutral particles;

[0026] x is: the generalized distribution function corresponding to the neutral particles;

[0027] is: the momentum variation characteristic of the generalized distribution function corresponding to the neutral particles;

[0028] is: the collision correlation coefficient related to the neutral particles;

[0029] is: the momentum gradient of the neutral particles;

[0030] is: the momentum-related gradient of the generalized distribution function of the neutral particles;

[0031] is: the generalized force related to the neutral particles.

[0032] Preferably, the magnetohydrodynamics MHD partial differential equations and their numerical discretization methods are applied to realize the simulation of large-scale macroscopic kinetic energy and momentum transfer, and the intermediate results after coupling are obtained.

[0033] Preferably, the expression of the weakly ionized, partially ionized macroscopic kinetic distribution function used by the magnetohydrodynamics MHD partial differential equation and its numerical discretization method is as follows:

[0034]

[0035] wherein:

[0036] is: the time variation characteristic of the generalized distribution function corresponding to the electrons and ions;

[0037] is: the generalized distribution function corresponding to the electrons and ions;

[0038] is: the generalized distribution velocity corresponding to the electrons and ions;

[0039] is: the resistance correlation coefficient related to the electrons and ions;

[0040] is: the curl of the generalized distribution function corresponding to the electrons and ions;

[0041] is: the momentum variation characteristic of the generalized distribution function corresponding to the electrons and ions;

[0042] is: the collision correlation coefficient related to the electrons and ions;

[0043] is: the momentum gradient of the electrons and ions;

[0044] is: the momentum-related gradient of the generalized distribution function of the electrons and ions;

[0045] is: the generalized force related to the electrons and ions.

[0046] Preferably, the micro-dynamical numerical discrete method is used for the coupling intermediate result, the discrete form of the Boltzmann control equation and the deviation equilibrium distribution function are used to locally refine the high-frequency disturbance part of the particles, and the refined particle dynamical simulation result is obtained.

[0047] Preferably, the multi-scale statistical average method and the error control technology are used for the comprehensive processing of the cross-scale coupling algorithm, the average flow field information, the coupling intermediate result and the refined particle dynamical simulation result are jointly updated and fed back, and the statistical average and error correction are performed on the refined result.

[0048] According to the above technical solution, compared with the prior art, the large-scale neutral-macroscopic dynamics-micro-dynamics coupling numerical simulation method based on the plasma statistical physics theory is provided, and the beneficial effects are as follows:

[0049] (1) The present application realizes the collaborative description of turbulent flow properties and particle dynamics behavior through the decomposition of low-frequency average and high-frequency disturbance of generalized distribution function, and breaks through the limitation of macro-micro scale separation in traditional simulation. Combined with large space-time neutral scale dispersion and multi-scale coupling algorithm, neutral fluid, magnetohydrodynamics (MHD) and micro dynamics are coupled in a unified framework for the first time, which can accurately capture the whole chain physical process from the macro evolution of kilometer solar storm to the energy transfer of particle disturbance.

[0050] (2) The present application improves the simulation accuracy of magnetic energy-kinetic energy conversion by embedding viscous-pressure-gravitational coupling term in the improved MHD equation in macroscopic dynamics coupling; the local phase space grid dispersion and collision integral approximation algorithm are used in micro dynamics processing, which reduces the calculation complexity while retaining the characteristics of non-equilibrium particle distribution. Combined with cross-scale statistical average and error feedback, the energy dissipation distortion problem caused by scale truncation in traditional method is effectively solved.

[0051] (3) The present application ensures numerical stability and long-time evolution reliability based on the time-space dispersion strategy of CFL condition and the fine integral of turbulent dissipation term of grid model. Through dynamic evolution analysis of output results, the propagation path of magnetic cloud, the acceleration mechanism of high-energy particles and the intensity of geomagnetic disturbance in solar electromagnetic storm can be accurately predicted, which provides a key theoretical tool for space weather prediction. In addition, this method also has significant advantages in plasma confinement optimization of controllable nuclear fusion device, interstellar medium multiphase flow simulation and other fields, and promotes the paradigm innovation of plasma multi-scale physical research. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of the provided drawings.

[0053] Figure 1 The method flowchart provided by the present application is provided;

[0054] Figure 2 The large space-time scale neutral scale, macroscopic dynamics scale, micro dynamics scale turbulent dissipation term table provided by the present application is provided;

[0055] Figure 3 The working boundary and initial condition diagram of the present application provided by the flare loop rotational instability RHPIC-LBM numerical simulation is provided;

[0056] Figure 4A display diagram of Rotational Rayleigh-Taylor instabilities, Rotational Kelvin-Helmholtz instabilities of the flare loop provided by the present application;

[0057] Figure 5 A display diagram of Rotational Rayleigh-Taylor instabilities, Rotational Kelvin-Helmholtz instabilities of the flare loop provided by the present application;

[0058] Figure 6 A first example of a diagram of Rotational theta-pinch kink instabilities provided by the present application;

[0059] Figure 7 A second example of a diagram of Rotational theta-pinch kink instabilities provided by the present application;

[0060] Figure 8 A first example of a diagram of Z-pinch kink instabilities provided by the present application;

[0061] Figure 9 A second example of a diagram of Z-pinch kink instabilities provided by the present application. DETAILED DESCRIPTION

[0062] 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 part of the embodiments of the present application, rather than all the embodiments. 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 protection of the present application.

[0063] As shown in Figure 1 the embodiments of the present application disclose a large-scale neutral-macroscopic-microscopic dynamics coupling numerical simulation method based on plasma statistical physics theory, which comprises:

[0064] Step 1: obtaining initial physical variables according to the attribute parameters of the plasma;

[0065] Step 2: numerical discrete processing is performed on the initial physical variable to obtain average flow field information on a neutral scale;

[0066] Step 3: macroscopic dynamics coupling processing is performed on the average flow field information to obtain a coupled intermediate result;

[0067] Step 4: local refinement processing is performed on the coupled intermediate result by using a microscopic dynamic numerical discrete method to obtain a refined particle dynamic simulation result

[0068] Step 5: the average flow field information, the coupled intermediate result and the refined particle dynamic simulation result are comprehensively processed by a cross-scale coupling algorithm to obtain a cross-time-space coupling numerical simulation result;

[0069] Step 6: the numerical simulation result is output, and the evolution law of the solar electromagnetic storm or the corresponding plasma dynamic behavior is analyzed.

[0070] Specifically, the multi-component, multi-abundance and multi-isotope properties of the real fluid and the field pseudo-fluid are described by the generalized distribution function in step 1.

[0071] The generalized distribution function is decomposed into a low-frequency average part and a high-frequency disturbance part, the statistical characteristics of the real fluid are described by the low-frequency average part, and the statistical characteristics of the field pseudo-fluid are described by the high-frequency disturbance part, to obtain the initial physical variable.

[0072] In an embodiment of the present application, the real fluid is electrons, protons, various ions, etc., and the field pseudo-fluid is the magnetic field.

[0073] Further, the magnetic field pseudo-fluid is assumed to be the magnetic field, the electric field pseudo-fluid is assumed to be the electric field, and the electromagnetic field pseudo-fluid is assumed to be the electromagnetic field; this assumption is a basic assumption of plasma statistical physics method, and the interaction between the pseudo-fluids and the interaction between the pseudo-fluids and the real fluid are converted into the interaction between the generalized distribution functions through the grid points to obtain statistical results, and the initial (magnetic field, electric field, electromagnetic field) physical variable is obtained.

[0074] Specifically, the initial physical variable is discretely processed based on a large space-time neutral scale, including: using a grid point model, according to a preset space scale parameter and time step, using the conservation equation and the turbulent dissipation term in the plasma statistical physics theory to describe the neutral flow, so as to obtain the average flow field information on the neutral scale.

[0075] In a specific embodiment of the present application, in the case of satisfying the conservation equation, the neutral dissipation term includes a classical dissipation term determined by fluid properties and a turbulent dissipation term additionally generated by the internal turbulent pressure, temperature and velocity of the neutral fluid, and the latter is 100,000 times the former; the specific implementation is to divide the quantity [pressure, density, temperature, velocity, etc.] in the neutral fluid into a low-frequency large quantity and a high-frequency small quantity, the high-frequency small quantity will generate instability through chaotic action, and then generate turbulence, and finally develop into a fully mature turbulent state through linear turbulent process, nonlinear turbulent process.

[0076] Specifically, the function expression of the large space-time neutral scale is:

[0077]

[0078] Wherein, are different physical properties, including density, velocity, current, magnetic field, pressure;

[0079] are different particle species, including electrons, ion neutral particles;

[0080] are different spatial scales, including flow property large scale, flow property macroscopic dynamics scale, particle property microscopic dynamics scale;

[0081] is: the time variation characteristic of the generalized distribution function corresponding to the neutral particle;

[0082] is: the generalized distribution function corresponding to the neutral particle;

[0083] is: the velocity of the neutral fluid;

[0084] is: the viscosity correlation coefficient related to the neutral particle;

[0085] x is: the curl of the generalized distribution function corresponding to the neutral particle;

[0086] is: the momentum variation characteristic of the generalized distribution function corresponding to the neutral particle;

[0087] is: the collision correlation coefficient related to the neutral particle;

[0088] is: the momentum gradient of the neutral particle;

[0089] is the gradient of the generalized distribution function of the neutral particle related to the momentum;

[0090] F is the generalized force related to neutral particles.

[0091] In one embodiment of the present application, the formula for calculating the generalized force related to neutral particles is as follows:

[0092]

[0093] In the formula, F is the generalized force related to neutral particles.

[0094] V is the neutral fluid velocity;

[0095] Fp is the generalized force related to pressure of neutral particles;

[0096] Vt is the turbulent viscosity coefficient of neutral particles;

[0097] V is the velocity divergence of neutral particles;

[0098] Fg is the gravity of neutral particles;

[0099] V is the viscosity coefficient of neutral particles.

[0100] Specifically, the magnetohydrodynamics (MHD) partial differential equations and their numerical discretization methods are applied to realize the simulation of large-scale macroscopic kinetic energy and momentum transfer, and to obtain the intermediate results after coupling.

[0101] Specifically, the expression of the weakly ionized and partially ionized macroscopic kinetic distribution function used in the magnetohydrodynamics (MHD) partial differential equations and their numerical discretization methods is as follows:

[0102]

[0103] In the formula, F is the generalized force related to neutral particles.

[0104] Ft is the time variation characteristic of the generalized distribution function corresponding to electrons and ions;

[0105] F is the generalized distribution function corresponding to electrons and ions;

[0106] V is the generalized distribution velocity corresponding to electrons and ions;

[0107] R is the resistance correlation coefficient related to electrons and ions;

[0108] F is the curl of the generalized distribution function corresponding to electrons and ions;

[0109] f is the generalized distribution function of electrons and ions as a function of momentum;

[0110] f is the collision correlation coefficient associated with electrons and ions;

[0111] f is the momentum gradient of electrons and ions;

[0112] f is the momentum-dependent gradient of the generalized distribution function of electrons and ions;

[0113] f is the generalized force associated with electrons and ions.

[0114] In one embodiment of the application, the generalized force associated with electrons and ions is given by the formula:

[0115]

[0116] where:

[0117] f is the generalized force associated with electrons and ions and electrical resistance;

[0118] f is the turbulent viscosity coefficient of electrons and ions;

[0119] f is the velocity gradient of the flow of electrons and ions;

[0120] f is the unit velocity vector of electrons and ions;

[0121] f is the generalized force associated with electrons and ions;

[0122] f is the generalized force associated with electrons and ions and pressure;

[0123] f is the turbulent resistance associated with electrons and ions;

[0124] f is the electrical resistance associated with electrons and ions; (determined by the properties of the plasma itself)

[0125] f is the gravitational force of electrons and ions;

[0126] f is the viscous correlation coefficient associated with electrons and ions;

[0127] f is the velocity of electrons and ions;

[0128] F: characteristic parameter; (related to plasma electron properties and ion particle properties).

[0129] In one embodiment of the present application, by using a numerical solution method of the coupling term of viscosity, pressure and gravity in the MHD equation, the transfer and dissipation simulation of kinetic energy and magnetic energy in a large scale range is realized, and the intermediate result after coupling is obtained.

[0130] Specifically, the micro-dynamics numerical discrete method is used for the intermediate result after coupling, the discrete form of the Boltzmann control equation and the distribution function deviating from the equilibrium state is used, and the local refinement processing of the particle high-frequency disturbance part is performed, so that the refined particle dynamics simulation result is obtained.

[0131] In one embodiment of the present application, the micro-dynamics processing uses an improved Boltzmann discrete method to discretize the distribution function in the local phase space, and uses a method for solving the collision integral approximation to numerically solve the particle high-frequency disturbance, so as to obtain the refined particle dynamics information.

[0132] Specifically, the multi-scale statistical average method and error control technology are used for the comprehensive processing of the cross-scale coupling algorithm, the average flow field information, the intermediate result after coupling and the refined particle dynamics simulation result are jointly updated and fed back, and the refined result is statistically averaged and error corrected.

[0133] In one embodiment of the present application, the multi-scale statistical average method and error control technology are used for the comprehensive processing of the cross-scale coupling algorithm, the results obtained in the large-scale neutral, macroscopic dynamics and micro-dynamics stages are jointly updated and fed back, the refined result is statistically averaged and error corrected, and the physical consistency and simulation accuracy of the results of each scale are ensured.

[0134] Further, in the embodiment, time and space discretization is performed under the condition of satisfying the Courant-Friedrichs-Lewy (CFL) condition, the numerical stability and rationality of the time step selection are ensured, and the entire coupling simulation process can obtain accurate dynamic results within the predetermined real evolution time.

[0135] In one embodiment provided by the present application, in the spherical coordinate system, , , ) below, a grid of 16000 x 32000 x 16000 is carried out in the Cartesian coordinate system x (x1, x2, x3) through coordinate transformation for the geometric region of a hemisphere with a radius of 6 million meters, the mass of a proton / mass of an electron = 1836, the simulation time step is 10E5 ion characteristic time (real evolution time 300 seconds), and the Courant-Friedrichs-Lewy (CFL) condition is met The numerical simulation of the rotational instability of a flare loop is carried out by using the RHPIC-LBM method. The turbulent dissipation terms in the large space-time neutral scale, macroscopic kinetic scale, and microscopic kinetic scale are as shown in the following formula: Figure 2

[0136] As shown in the following formula: Figures 3 to 9 It is found that the rotational Z-pinch kink instabilities, rotational θ-pinch kink instabilities, rotational Rayleigh-Taylor instabilities, and rotational Kelvin-Helmholtz instabilities are consistent with observations.

[0137] As can be seen from the above, through the low-frequency average and high-frequency disturbance decomposition of the generalized distribution function, the collaborative description of the turbulent flow properties and the particle kinetic behavior is realized, and the limitation of the macro-micro scale separation in the traditional simulation is broken. Combined with the large space-time neutral scale discretization and the multi-scale coupling algorithm, the neutral fluid, magneto-hydrodynamics (MHD), and microscopic kinetic are coupled in a unified framework for the first time, and the whole chain of physical processes from the macroscopic evolution of the kilometer-class solar storm to the energy transfer of the particle-level disturbance can be accurately captured.

[0138] The macroscopic kinetic coupling is embedded with viscosity-pressure-gravity coupling terms through the improved MHD equation, which significantly improves the simulation accuracy of the magnetic energy-kinetic energy conversion; the microscopic kinetic processing adopts the local phase space grid discretization and collision integral approximation algorithm, which reduces the computational complexity while retaining the characteristics of the non-equilibrium particle distribution. Combined with the cross-scale statistical average and error feedback, the energy dissipation distortion problem caused by scale truncation in the traditional method is effectively solved.

[0139] Based on the space-time discretization strategy of the CFL condition and the fine integral of the turbulent dissipation term of the grid model, the numerical stability and the reliability of long-time evolution are ensured.

[0140] ​Through the dynamic evolution analysis of the output results, the propagation path of the magnetic cloud, the high-energy particle acceleration mechanism and the geomagnetic disturbance intensity in the solar electromagnetic storm can be accurately predicted, thereby providing a key theoretical tool for space weather prediction. In addition, the method also has significant advantages in the optimization of plasma confinement in controllable nuclear fusion devices, simulation of interstellar medium multiphase flow and other fields, and promotes the paradigm innovation of plasma multiscale physical research.

[0141] The various embodiments are described in the present specification in a progressive manner, each embodiment focusing on the differences from other embodiments, and the same or similar parts between the various embodiments can be mutually referred to. For the device disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0142] The above description of disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A large-scale neutral-macroscopic dynamics-microscopic kinetics coupling numerical simulation method based on the statistical physics theory of plasma, characterized in that, The method comprises the following steps: Step 1: obtaining initial physical variables according to attribute parameters of the plasma; Step 2: performing numerical discrete processing on the initial physical variables to obtain average flow field information on a neutral scale; The discrete processing on the initial physical variables based on the large space-time neutral scale comprises: adopting a grid model, utilizing a conservation equation and a turbulent dissipation term for describing neutral flow in a statistical physics theory of the plasma according to preset space scale parameters and time steps, so as to obtain the average flow field information on the neutral scale; Step 3: performing macroscopic kinetic coupling processing on the average flow field information to obtain a coupling intermediate result; applying a magnetic fluid dynamics (MHD) partial differential equation and a numerical discrete method thereof to realize simulation of large-scale macroscopic kinetic energy and momentum transfer, so as to obtain the coupling intermediate result; Step 4: performing local refinement processing on the coupling intermediate result by using a microscopic kinetic numerical discrete method, so as to obtain a refined particle kinetic simulation result; Step 5: comprehensively processing the average flow field information, the coupling intermediate result and the refined particle kinetic simulation result by using a cross-scale coupling algorithm to obtain a cross-space-time coupling numerical simulation result; performing local refinement processing on the coupling intermediate result by using a microscopic kinetic numerical discrete method, utilizing a Boltzmann control equation and a discrete form of a distribution function deviating from an equilibrium state to process a high-frequency disturbance part of particles, so as to obtain the refined particle kinetic simulation result; Step 6: outputting the numerical simulation result and analyzing evolution rules of solar electromagnetic storm or corresponding plasma dynamic behavior.

2. The large-scale kinetic-macrodynamic-microdynamic coupling numerical simulation method based on plasma statistical physics theory according to claim 1, characterized in that, The step 1 simultaneously describes multi-component, multi-abundance and multi-isotope attributes of real fluid and field pseudo fluid by using a generalized distribution function; The generalized distribution function is decomposed into a low-frequency average part and a high-frequency disturbance part; the statistical characteristics of the real fluid are described by using the low-frequency average part, and the statistical characteristics of the field pseudo fluid are described by using the high-frequency disturbance part, so as to obtain the initial physical variables.

3. The large-scale kinetic-macrodynamic-microdynamic coupling numerical simulation method based on plasma statistical physics theory according to claim 1, characterized in that, The function expression of the large space-time neutral scale is as follows: wherein are different physical properties, including density, velocity, current, magnetic field, pressure; For different particle species, including electrons, ions, neutral particles; for different spatial scales, including flow property macro-scale, flow property meso-dynamic scale, particle property micro-dynamic scale; is: the time-varying characteristic of the generalized distribution function corresponding to the neutral particles; where: f is the generalized distribution function corresponding to the neutral particles; where: neutral fluid velocity; is the viscosity correlation factor associated with the neutral particles; x is the generalized distribution function of the neutral particles. F is: the generalized distribution function corresponding to the characteristics of the momentum of the neutral particles; Cn: collision correlation associated with neutral particles; is the neutral particle momentum gradient; is the gradient of the generalized distribution function of neutral particles with respect to momentum; F = neutral particle related generalized force.

4. The large-scale kinetic-macrodynamic-microdynamic coupling numerical simulation method based on plasma statistical physics theory according to claim 1, characterized in that, The expression of the weakly ionized and partially ionized macroscopic kinetic distribution function used in the application of the MHD partial differential equation and the numerical discrete method thereof is as follows: Wherein: are: the characteristics of the generalized distribution function of the electrons and ions over time; where: e and i are the generalized distribution functions for electrons and ions, respectively; are: the generalized distribution velocities of the electrons and ions, respectively; R is: an electronic and ionic related resistance correlation coefficient; is the curl of the generalized distribution function of the electrons and ions; are: the characteristics of the generalized distribution functions of electrons and ions as a function of momentum; Coulomb: collision number associated with electrons and ions; are: electronic and ionic momentum gradients; are: the gradients of the electron and ion generalized distribution functions with respect to momentum; F = generalized force associated with electrons and ions.

5. The large-scale kinetic-macrodynamic-microdynamic coupling numerical simulation method based on plasma statistical physics theory according to claim 1, characterized in that, The comprehensive processing by using the cross-scale coupling algorithm adopts a multi-scale statistical average method and an error control technology to jointly update and feed back the average flow field information, the coupling intermediate result and the refined particle kinetic simulation result, and to statistically average and correct the refined result.

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