A method, system, apparatus, and storage medium for calculating magnetic confinement plasma turbulence characteristics
By calculating the diffusion coefficient using a magnetohydrodynamic model and iteratively solving the magnetohydrodynamic equations, the problem of low computational efficiency for plasma turbulence characteristics in the tokamak pedestal region is solved, achieving efficient and accurate simulation of turbulence characteristics, which is applicable to large-scale magnetically confined plasma devices.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SUN YAT SEN UNIV
- Filing Date
- 2023-03-24
- Publication Date
- 2026-04-17
AI Technical Summary
Existing technologies involve large computational loads when calculating plasma turbulence characteristics in the tokamak pedestal region, making it difficult to improve computational efficiency while maintaining high accuracy. Furthermore, the PIC method does not have an advantage when calculating large areas.
A magnetohydrodynamic (MHD) model-based approach is adopted. By setting initial simulation conditions, calculating the diffusion coefficient, and iteratively solving the MHD equations, the Langevin equation and Newton's equations of motion are combined to optimize particle motion simulation, reduce computational load, and improve efficiency.
While maintaining high computational accuracy, it significantly improves the computational efficiency of magnetically confined plasma turbulence, reduces computation time, and enhances the ability to describe turbulence characteristics, making it suitable for simulation of large-scale magnetically confined plasma devices.
Smart Images
Figure CN116484586B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of plasma technology, and more specifically, to a method, system, apparatus, and storage medium for calculating the turbulent characteristics of magnetically confined plasma. Background Technology
[0002] Achieving steady-state operation of high-temperature, high-density, high-parameter plasma under fusion reactor conditions is a crucial pathway to realizing magnetically confined nuclear fusion energy. To improve the operating parameters of the burning plasma, it is necessary to effectively enhance its confinement performance. In 1982, researchers discovered a high-confinement mode (H mode) using neutral beam injection (NBI) in the ASDEX experiment. This high-β... p The value mode can improve the confinement performance of the tokamak device. After the plasma is heated, it enters the H mode from the L mode, and the average electron density and specific pressure are increased, forming a region with a steep plasma parameter gradient at the interface. Under the conditions of H mode operation, the particle transport coefficient inside the boundary transport barrier will drop to a lower level, and a plasma density and temperature gradient will form in this region, causing the plasma density and temperature inside the boundary transport barrier to be raised to a higher level. It looks as if the plasma density and temperature distribution from the boundary transport barrier to the core under the L mode is placed on a base, so the boundary transport barrier region is also called the pedestal region (e.g., Figure 1 (As shown). According to existing theories, the confinement performance of burning plasma largely depends on the magnetically confined plasma turbulent transport characteristics in the slab region.
[0003] Under fusion reactor conditions, auxiliary heating methods such as neutral beam injection, ion cyclotron heating, and electron cyclotron heating are needed to further increase the plasma temperature and achieve high-parameter operation. Under these conditions, the characteristics of magnetically confined plasma turbulence in the tokamak base region are affected by many factors. How to effectively calculate the large-scale complex plasma turbulence characteristics, represented by the plasma turbulence in the tokamak base region, is of great significance for magnetically confined plasma physics research and is also one of the important research topics for large-scale tokamak fusion devices such as the International Thermonuclear Experimental Reactor (ITER).
[0004] Particle-in-cell (PIC) is a typical particle simulation method that simulates particle motion by starting with the interaction between microscopic charged particles and electromagnetic fields. Its basic idea is as follows: the simulation region is divided into a series of grids; an appropriate number of charged particles are scattered into the simulation region, with initial positions and velocities of the particles and an initial electromagnetic field distribution set; driven by the initial electromagnetic field, the charged particles move for one time step, while the electromagnetic field remains constant during the particle movement; the movement of the charged particles inevitably leads to changes in the charge density and current density in the plasma, which in turn react on the electromagnetic field, thus updating the electromagnetic field on the grid, resulting in a discrete updated electromagnetic field; the discrete electromagnetic field is then weighted by a certain weighting function and returned to the location of the charged particle, driving the particle again. This iterative process yields the simulation results of the plasma. PIC can accurately describe the kinetic behavior of magnetically confined plasmas; however, its computational cost is high, making it less advantageous for calculating large regions, such as tokamak pylons.
[0005] Therefore, developing a method that retains high computational accuracy while being capable of calculating magnetically confined plasma turbulence over large areas is of significant application value for studying the characteristics of magnetically confined plasma turbulence, exemplified by plasma turbulence in tokamak slab regions. Such efficient methods for calculating magnetically confined plasma turbulence can be readily extended to various application areas of plasma turbulence calculation, such as the simulation of E×B turbulence and the simulation of electric propulsion plasma turbulence, helping researchers conduct studies on the characteristics of magnetically confined plasma turbulence more efficiently. Summary of the Invention
[0006] In order to address the shortcomings and defects of the prior art, this invention provides a method, system, device, and storage medium for calculating the turbulence characteristics of magnetically confined plasma, which can effectively improve the calculation efficiency of magnetically confined plasma turbulence while maintaining high calculation accuracy.
[0007] To achieve the above-mentioned objectives of this invention, the technical solution adopted is as follows:
[0008] A method for calculating the turbulent characteristics of magnetically confined plasma, the method comprising the following steps:
[0009] S1: Set the initial conditions for the simulation, including the size and shape of the simulation space, the number of time steps N, the time step size, plasma parameters, initial conditions, boundary conditions, and mesh size;
[0010] S2: Determine if the current time step n is less than the time step N. If not, proceed to step S3; if yes, proceed to step S6.
[0011] S3: Based on the spatial electromagnetic field distribution, the particle motion within the grid is calculated to obtain the plasma diffusion coefficient within each grid.
[0012] S4: Solve the magnetohydrodynamic equations iteratively based on the diffusion coefficient obtained in step S3;
[0013] S5: Update the mesh information, n = n + 1, save the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations, and return to step S2;
[0014] S6: Output diffusion coefficient and calculation results of solving the magnetohydrodynamic equations.
[0015] Preferably, after step S1 and before step S2, the simulation space needs to be gridded to obtain the electromagnetic field distribution of each space based on the temporal and spatial distribution relationship of the electromagnetic field.
[0016] Furthermore, obtaining a grid-like spatial electromagnetic field distribution in magnetically confined plasma includes:
[0017] Based on the turbulent characteristics of magnetically confined plasma, the electric and magnetic fields are calculated using the corresponding magnetohydrodynamic equations.
[0018] Set the grid according to the grid size and interpolate the electric and magnetic fields to the grid points using polynomial interpolation.
[0019] Preferably, the calculation of particle motion within the grid to obtain the plasma diffusion coefficient within each grid includes:
[0020] Based on the distribution law of the electromagnetic field in space, a differential equation about velocity is obtained based on the Lagrange equation. The relationship between the velocity perturbation of particles in the grid and time is calculated by using analytical or numerical solutions.
[0021] By combining the relationship between velocity perturbation and time and the time step, the diffusion coefficient is obtained by solving the Langevin equation and the fluctuation-dissipation theorem.
[0022] Furthermore, based on the distribution law of the electromagnetic field in space, the Lagrangian function of a particle in the electromagnetic field can be written as:
[0023]
[0024] in, This represents the velocity component of the particle in the x-direction. Let m represent the velocity component of the particle in the y-direction, m represent the mass of the particle, q represent the charge of the particle, L is the Lagrangian function, and B0 represent the magnetic field strength at the corresponding point.
[0025] By calculating the Lagrange equation:
[0026]
[0027] Where, q i Represents generalized coordinates. q i The first derivative with respect to time;
[0028] The differential equation for velocity is obtained as follows:
[0029]
[0030] in, These represent the second derivatives of x and y with respect to time, i.e., the accelerations at the corresponding positions;
[0031] Furthermore, if the differential equation concerning velocity has an analytical solution for the particle under initial conditions, then:
[0032]
[0033] Where JacobiCN represents the Jacobi ellipse CN function, JacobiDN represents the Jacobi ellipse DN function, c1 and c2 are two constants, and t is time;
[0034] If the differential equation concerning velocity has no analytical solution, then the particle's trajectory can be numerically solved using Newton's equations of motion:
[0035]
[0036] in, The magnetic field representing the particle's position is obtained by interpolating the position within the grid. and These represent the acceleration vector and the velocity vector, respectively.
[0037] After several iterations on a timescale smaller than the time step, the velocity perturbation of particles within the grid is calculated. The value at time t0+Δt t0 represents the time of a certain step.
[0038] Furthermore, by combining the relationship between velocity perturbation and time and the time step, the diffusion coefficient D is obtained by solving the Langevin equation and the fluctuation-dissipation theorem.
[0039]
[0040] Where <·> represents the average value calculation, and Δt represents the time step.
[0041] A system for calculating the turbulent characteristics of magnetically confined plasma, the system comprising:
[0042] The initial setup module is used to set the initial conditions for the simulation, including the size and shape of the simulation space, the number of time steps N, the time step size, plasma parameters, initial conditions, boundary conditions, and mesh size.
[0043] The judgment module is used to determine whether the current time step n is less than the time step N;
[0044] The diffusion coefficient calculation module is used to calculate the particle motion within the grid based on the spatial electromagnetic field distribution, and to obtain the diffusion coefficient of plasma within each grid.
[0045] The magnetohydrodynamic equations calculation module is used to iteratively solve the magnetohydrodynamic equations based on the obtained diffusion coefficient.
[0046] Update the storage module to update the mesh information, n = n + 1, and save the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations;
[0047] The results output module is used to output the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations.
[0048] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it performs the steps of the method described above.
[0049] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.
[0050] The beneficial effects of this invention are as follows:
[0051] This invention calculates the diffusion coefficient, a key parameter of plasma turbulence, and combines it with the magnetohydrodynamic equations to more accurately calculate the effects of turbulence under a magnetohydrodynamic model. The calculation method based on the magnetohydrodynamic model is more efficient than the PIC method, enabling its application in simulating large-scale magnetically confined plasma devices.
[0052] This invention effectively improves the computational efficiency of magnetically confined plasma turbulence while maintaining high computational accuracy. It demonstrates excellent computational performance for studying large-scale complex plasma turbulence characteristics, exemplified by plasma turbulence in tokamak pedestal regions. While exhibiting computational performance similar to particle simulations, it significantly reduces the computational load and effectively decreases computation time.
[0053] Furthermore, the diffusion coefficient obtained by iterating through the Langevin equation or Newton's equation can reflect the basic characteristics of plasma turbulence, making the simulation results more practical; by providing an iterative method for solving the diffusion coefficient using the Langevin equation or Newton's equation, the robustness of the diffusion coefficient solution process is enhanced.
[0054] Furthermore, this invention further enhances the method's ability to describe the turbulent characteristics of magnetically confined plasmas by coupling the real-time updated turbulence diffusion coefficient into the magnetohydrodynamic equations. Attached Figure Description
[0055] Figure 1 This is a schematic diagram of an existing technology platform structure.
[0056] Figure 2 This is a flowchart of the steps in the method for calculating the turbulent characteristics of magnetically confined plasma according to the present invention.
[0057] Figure 3 This is a flowchart illustrating the steps of obtaining the diffusion coefficient of plasma within each grid in this invention. Detailed Implementation
[0058] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.
[0059] Example 1
[0060] Imagine a scenario where a plasma is subjected to a magnetic field perturbation distributed along the z-direction of space in a non-relativistic case.
[0061] like Figure 1 As shown, a method for calculating the turbulent characteristics of magnetically confined plasma includes the following steps:
[0062] S1: Set the initial conditions for the simulation, including the size and shape of the simulation space, the number of time steps N, the time step size, plasma parameters, initial conditions, boundary conditions, and mesh size. In this embodiment, the size and shape of the simulation space represent the spatial size and shape of the geometric model of the problem under study. This embodiment uses these as the initial and boundary conditions for the simulation.
[0063] S2: Determine if the current time step n is less than the time step N. If not, proceed to step S3; if yes, proceed to step S6.
[0064] S3: Based on the spatial electromagnetic field distribution, the particle motion within the grid is calculated to obtain the plasma diffusion coefficient within each grid.
[0065] S4: Solve the magnetohydrodynamic equations iteratively based on the diffusion coefficient obtained in step S3;
[0066] S5: Update the mesh information, n = n + 1, save the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations, and return to step S2;
[0067] S6: Output diffusion coefficient and calculation results of solving the magnetohydrodynamic equations.
[0068] Based on the magnetohydrodynamic equations, the electromagnetic field and parameters such as plasma temperature, density, and velocity for the next simulation step are solved iteratively according to the input plasma diffusion coefficient, and the plasma temperature, density, and velocity parameters obtained in this simulation step are stored in temporary variables.
[0069] After the calculation is completed, the simulation results such as plasma temperature, density, and velocity are output, and the simulation results are plotted and visualized.
[0070] In a specific embodiment, after step S1 and before step S2, the simulation space needs to be gridded to obtain the electromagnetic field distribution of each space based on the temporal and spatial distribution relationship of the electromagnetic field.
[0071] This embodiment obtains a spatial electromagnetic field distribution that conforms to a grid pattern in magnetically confined plasma, including:
[0072] Based on the turbulent characteristics of magnetically confined plasma, the electric and magnetic fields are calculated using the corresponding magnetohydrodynamic equations.
[0073] Set the grid according to the grid size and interpolate the electric and magnetic fields to the grid points using polynomial interpolation.
[0074] In one specific embodiment, the calculation of particle motion within the grid to obtain the plasma diffusion coefficient within each grid is described, such as... Figure 3 As shown, it includes:
[0075] Based on the distribution law of the electromagnetic field in space, a differential equation about velocity is obtained based on the Lagrange equation. The relationship between the velocity perturbation of particles in the grid and time is calculated by using analytical or numerical solutions.
[0076] By combining the relationship between velocity perturbation and time and the time step, the diffusion coefficient is obtained by solving the Langevin equation and the fluctuation-dissipation theorem.
[0077] In this embodiment, based on the distribution law of the spatial electromagnetic field, the Lagrangian function of a particle in the spatial electromagnetic field is written as:
[0078]
[0079] in, This represents the velocity component of the particle in the x-direction. Let m represent the velocity component of the particle in the y-direction, m represent the mass of the particle, q represent the charge of the particle, L is the Lagrangian function, and B0 represent the magnetic field strength at the corresponding point.
[0080] By calculating the Lagrange equation:
[0081]
[0082] Where, q i Represents generalized coordinates. This represents the first derivative of qi with respect to time.
[0083] The differential equation for velocity is obtained as follows:
[0084]
[0085] in, These represent the second derivatives of x and y with respect to time, i.e., the accelerations at the corresponding positions;
[0086] Furthermore, if the differential equation concerning velocity has an analytical solution for the particle under initial conditions, then:
[0087]
[0088] Where JacobiCN represents the Jacobi ellipse CN function, JacobiDN represents the Jacobi ellipse DN function, c1 and c2 are two constants, and t is time;
[0089] If the differential equation concerning velocity has no analytical solution, then the particle's trajectory can be numerically solved using Newton's equations of motion:
[0090]
[0091] in, The magnetic field representing the particle's position is obtained by interpolating the position within the grid. and These represent the acceleration vector and the velocity vector, respectively.
[0092] After several iterations on a timescale smaller than the time step, the velocity perturbation of particles within the grid is calculated. The value at time t0+Δt t0 represents the time of a certain step.
[0093] Furthermore, by combining the relationship between velocity perturbation and time and the time step, the diffusion coefficient D is obtained by solving the Langevin equation and the fluctuation-dissipation theorem.
[0094]
[0095] Where <·> represents the average value calculation, and Δt represents the time step.
[0096] In this embodiment, the calculated diffusion coefficient D is used as a plasma parameter and input into the magnetohydrodynamic equations for iterative solution.
[0097] In this example, the nonideal single-fluid magnetohydrodynamic equations with Hall terms are used to solve for plasma motion. The magnetohydrodynamic equations can be written as:
[0098]
[0099] in, These are the plasma velocity, current density, resistance, frequency, thermal conductivity, kinematic viscosity, density, pressure, and speed of light, respectively; the subscript 0 represents the equilibrium value of the physical quantity. It is the gradient operator. For current vector, It is the electric field intensity vector.
[0100] The motion state of the plasma at the next moment can be obtained through explicit iteration based on the first four equations.
[0101] In this embodiment, the magnetohydrodynamic equations are solved iteratively based on the updated diffusion coefficient, and then iterated according to the time step until the plasma simulation results are obtained.
[0102] The method described in this embodiment effectively improves the computational efficiency of magnetically confined plasma turbulence while maintaining high computational accuracy. This method demonstrates excellent computational performance for studying large-scale complex plasma turbulence characteristics, exemplified by tokamak slab-based plasma turbulence. It exhibits computational performance similar to particle simulations while significantly reducing computational load and time. Furthermore, the method in this embodiment further enhances its ability to describe the characteristics of magnetically confined plasma turbulence by coupling the real-time updated turbulence diffusion coefficient into the magnetohydrodynamic equations.
[0103] Example 2
[0104] Based on the method for calculating the turbulent characteristics of magnetically confined plasma provided in Embodiment 1, this embodiment also provides a system for calculating the turbulent characteristics of magnetically confined plasma, the system comprising:
[0105] The initial setup module is used to set the initial conditions for the simulation, including the size and shape of the simulation space, the number of time steps N, the time step size, plasma parameters, initial conditions, boundary conditions, and mesh size.
[0106] The judgment module is used to determine whether the current time step n is less than the time step N;
[0107] The diffusion coefficient calculation module is used to calculate the particle motion within the grid based on the spatial electromagnetic field distribution, and to obtain the diffusion coefficient of plasma within each grid.
[0108] The magnetohydrodynamic equations calculation module is used to iteratively solve the magnetohydrodynamic equations based on the obtained diffusion coefficient.
[0109] Update the storage module to update the mesh information, n = n + 1, and save the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations;
[0110] The results output module is used to output the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations.
[0111] In this embodiment, a visualization module may also be included to output the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations as data files or images, thereby obtaining the data results of the corresponding plasma parameters changing over time.
[0112] Example 3
[0113] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the steps of the method for calculating the turbulent characteristics of magnetically confined plasma as described in Embodiment 1.
[0114] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.
[0115] Example 4
[0116] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for calculating the turbulent characteristics of magnetically confined plasma as described in Example 1.
[0117] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
[0118] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the claims of the present invention.
Claims
1. A method for calculating the turbulent characteristics of magnetically confined plasma, characterized in that: The method includes The steps are as follows: S1: Set initial conditions for the simulation, including the size and shape of the simulation space, and the number of time steps. N, time step, plasma parameters, initial conditions, boundary conditions, mesh size; S2: Determine if the current time step n is less than the time step N. If not, proceed to step S3; if yes, proceed to step S6. S3: Based on the spatial electromagnetic field distribution, the particle motion within the grid is calculated to obtain the plasma's... The diffusion coefficient within each grid cell; specifically including: Based on the distribution law of the electromagnetic field in space, a differential equation for velocity is obtained based on the Lagrange equation. The relationship between the velocity perturbation of particles within the grid and time is calculated using analytical or numerical methods. Combining the relationship between velocity perturbation and time step, and using Langevin's equation and fluctuation- The diffusion coefficient is obtained by solving the dissipation theorem. D : Where <> represents the average operation. Δ t Indicates the time step. Indicates a certain step taking a long time. Indicates at time The velocity disturbance, Indicates in The velocity disturbance at any given moment; S4: Solve the magnetohydrodynamic equations iteratively based on the diffusion coefficient obtained in step S3; S5: Update mesh information, n=n+1, save diffusion coefficient and calculation results of solving the magnetohydrodynamic equations. Return to step S2; S6: Output diffusion coefficient and calculation results of solving the magnetohydrodynamic equations.
2. The method for calculating the turbulent characteristics of magnetically confined plasma according to claim 1, characterized in that: After step S1 and before step S2, the simulation space needs to be gridded to obtain the electromagnetic field distribution in each space based on the temporal and spatial distribution relationship of the electromagnetic field.
3. The method for calculating the turbulent characteristics of magnetically confined plasma according to claim 2, characterized in that... At: Obtaining a grid-like spatial electromagnetic field distribution in magnetically confined plasma includes: Based on the turbulent characteristics of magnetically confined plasma, the electric and magnetic fields are calculated using the corresponding magnetohydrodynamic equations. Set the grid according to the grid size and interpolate the electric and magnetic fields into the grid using polynomial interpolation. On the grid points.
4. The method for calculating the turbulent characteristics of magnetically confined plasma according to claim 3, characterized in that... According to the distribution law of the electromagnetic field in space, the Lagrangian function of a particle in the electromagnetic field is written as: ， in, Indicates that the particle is in x The velocity component in the direction, Indicates that the particle is in y The velocity component in the direction, Indicates the mass of the particle. This represents the amount of charge on a particle. L For Lagrange functions, B 0 represents the magnetic field strength at the corresponding point; By calculating the Lagrange equation: in, Represents generalized coordinates. express The first derivative with respect to time; The differential equation for velocity is obtained as follows: in, , Represent x , y The second derivative with respect to time is the acceleration at the corresponding position.
5. The method for calculating the turbulent characteristics of magnetically confined plasma according to claim 4, characterized in that: If the differential equation concerning velocity has an analytical solution for the particle under initial conditions, then: ， Where JacobiCN represents the Jacobi elliptic CN function, and JacobiDN represents the Jacobi elliptic DN function. They are two constants. For time; If the differential equation concerning velocity has no analytical solution, then the particle's trajectory can be numerically solved using Newton's equations of motion: in, The magnetic field representing the particle's position is obtained by interpolating the position within the grid. and These represent the acceleration vector and the velocity vector, respectively. After several iterations on a timescale smaller than the time step, the velocity perturbation of particles within the grid is calculated. exist Value of time , It indicates a certain step that takes a long time.
6. A system for calculating the turbulent characteristics of magnetically confined plasma, characterized in that, The system is based on the method according to any one of claims 1-5, and the system comprises: The initial setup module is used to set the initial conditions for the simulation, including the size and shape of the simulation space, the number of time steps N, the time step size, plasma parameters, initial conditions, boundary conditions, and mesh size. The judgment module is used to determine whether the current time step n is less than the time step N; The diffusion coefficient calculation module is used to calculate the particle motion within the grid based on the spatial electromagnetic field distribution, and to obtain the diffusion coefficient of plasma within each grid. The magnetohydrodynamic equations calculation module is used to iteratively solve the magnetohydrodynamic equations based on the obtained diffusion coefficient. Update the storage module to update the mesh information, n=n+1, and save the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations; The results output module is used to output the diffusion coefficient and the calculation results of solving the magnetohydrodynamic equations.
7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5.
8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5.