Neutralization gas supply control method based on Monte Carlo algorithm and related product

Abstract

The invention relates to the technical field of neutral beam injection heating in the field of magnetic confinement fusion, in particular to a neutral gas supply control method based on a Monte Carlo algorithm and a related product, and the method comprises the steps: determining a target thickness, determining an initial gas target thickness, judging whether the initial gas target thickness reaches the target thickness or not, and if yes, judging that the gas supply amount is zero; if the target thickness does not reach the target thickness, gradually simulating gas supply to the neutralizer for multiple times, iteratively calculating the supplementary target thickness until the gas target thickness reaches the target thickness, obtaining the total gas supply amount, determining the total gas supply amount, and outputting the corresponding control amount; according to the method, the target thickness is obtained, the initial target thickness is calculated, then neutral supplied gas is added step by step, the supplementary target thickness is calculated iteratively in a stepping mode until the accumulated gas target thickness reaches the target thickness, and finally the control quantity is output. According to the invention, the neutralization efficiency of each ion beam can reach the optimal state by accurately controlling the air supply amount for neutralization, and the transmission efficiency of the beam is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of neutral beam injection heating technology in the field of magnetic confinement fusion, and in particular to a neutralization gas supply control method based on a Monte Carlo algorithm and related products. Background Art

[0002] Neutral beam injection heating is an important auxiliary heating technology used in magnetic confinement nuclear fusion experiments. Its basic principle is to ionize the gas in the discharge chamber to form plasma, and then accelerate it through an electric field to form a high-energy ion beam. These high-energy ion beams pass through the neutralizer, collide with the gas target, capture electrons and convert them into high-energy neutral particle beams, which are finally injected into the plasma in the tokamak device to increase the temperature and energy of the plasma.

[0003] Due to the strong magnetic field in the tokamak device, charged ions cannot be directly injected into the plasma, so the ion beam must be neutralized. The neutralization efficiency (i.e., the proportion of high-energy ion beam converted into neutral particles) is a key factor affecting the injection power and heating effect. For a gas target neutralizer, the neutralization efficiency mainly depends on the gas molecule density and the target thickness. The neutralization efficiency of the positive ion beam increases with the increase of the gas target thickness, and there is a maximum value, while the neutralization efficiency of the negative ion beam increases first and then decreases with the increase of the gas target thickness, and there is an optimal value.

[0004] The traditional neutralization gas supply method usually presets a certain amount of gas supply based on experience to achieve the purpose of increasing the gas target thickness and improving the neutralization efficiency. However, this method has some shortcomings. For example, the preset gas supply volume is difficult to ensure the optimal neutralization efficiency; excessive gas supply will lead to increased stripping loss of the beam at the extraction electrode and increased reionization loss in the subsequent transmission path; insufficient gas supply will fail to achieve the optimal neutralization efficiency, resulting in beam power loss.

[0005] In summary, the existing technology has certain limitations in the neutralization gas supply control. How to achieve the best neutralization efficiency through precise calculation and control methods is a problem that needs to be solved urgently. Summary of the invention

[0006] The technical problem to be solved by the present invention is that the preset neutralization gas supply cannot achieve the optimal neutralization efficiency of the beam. The purpose is to provide a neutralization gas supply control method and related products based on the Monte Carlo algorithm, which realizes real-time optimization of the neutralization gas supply volume, so that the ion beam can achieve the optimal neutralization efficiency under different energy parameters, thereby improving the beam transmission efficiency and reducing the re-ionization loss and stripping loss.

[0007] The present invention is achieved through the following technical solutions:

[0008] A neutralization air supply control method based on Monte Carlo algorithm, comprising:

[0009] The gas target thickness required to achieve the best neutralization efficiency is determined by the energy of the high-energy ion beam and is used as the target target thickness;

[0010] According to the amount of unionized gas in the ion source and the structure of the neutralizer, the Monte Carlo method is used to simulate the motion trajectory of gas molecules, calculate the distribution of unionized gas in the neutralizer, and determine the initial gas target thickness;

[0011] Determine whether the initial gas target thickness reaches the target target thickness. If it has reached it, the gas supply volume is determined to be zero; if it has not reached it, simulate gas supply to the neutralizer step by step for multiple times, and iteratively calculate the supplementary target thickness until the gas target thickness reaches the target target thickness, and obtain the total gas supply volume;

[0012] Determine the total air delivery volume and output the corresponding control volume.

[0013] Specifically, the method for determining the initial gas target thickness includes:

[0014] Determine boundary conditions;

[0015] A random number that satisfies the cosine theorem is used as the emission direction, so that the simulated particles fly along the emission direction;

[0016] Determine whether the simulated particle collides with a certain boundary. If no collision occurs, emit the next simulated particle.

[0017] If a simulated particle collides with a certain boundary, it is determined whether the flight time is greater than the calculation time. If the flight time is greater than the calculation time, the next simulated particle is emitted;

[0018] If the flight time is less than the calculation time, a new emission direction is assigned to the simulated particle at the collision point, so that the simulated particle flies along the new emission direction;

[0019] Repeat the above two judgments until the flight time of the simulated particle is equal to the calculation time, record the position of the simulated particle, and generate the next simulated particle;

[0020] Complete the emission of all simulated particles, statistically calculate the position and number of all particles in the area, and integrate to obtain the initial gas target thickness.

[0021] Optionally, the boundary conditions include: structural parameters of the neutralizer, the amount of unionized gas in the ion source, gas supply position, calculation time and background vacuum value.

[0022] Specifically, the initial gas target thickness is obtained by statistically calculating the positions and numbers of particles in the region and integrating them over the length of the neutralizer.

[0023] Specifically, the air inlet position for supplementing the neutralizer is different from the air inlet position for the initial gas; the air inlet position for supplementing the neutralizer is set in the middle of the neutralizer.

[0024] Optionally, the method of iteratively superimposing gas target thickness to reach the target target thickness includes:

[0025] Set the air intake volume of the step;

[0026] Simulate input of a step-length neutralization air supply volume into the neutralizer;

[0027] A random number satisfying the cosine theorem is used as the emission direction, so that the simulated particles in the supplementary gas fly along the emission direction;

[0028] Determine whether the simulated particle collides with a certain boundary. If no collision occurs, emit the next simulated particle.

[0029] If the simulated particle collides with a certain boundary, it is determined whether the flight time is greater than the calculation time. If the flight time is greater than the calculation time, the next simulated particle is emitted;

[0030] If the flight time is less than the calculation time, a new emission direction is assigned to the simulated particle at the collision point, so that the simulated particle flies along the new emission direction;

[0031] Repeat the above two judgments until the flight time of the simulated particle is equal to the calculation time, record the position of the simulated particle, and generate the next simulated particle;

[0032] Complete the emission of all simulated particles in the supplementary gas, statistically calculate the positions and quantities of all particles in the area, and integrate to obtain the supplementary target thickness;

[0033] The supplementary target thickness and the initial gas target thickness are superimposed, and it is determined whether the superimposed gas target thickness reaches the target target thickness; if not, a step-length neutralization gas supply volume is simulated and input into the neutralizer again, and a new gas target thickness is iteratively calculated;

[0034] If the gas target thickness reaches the target target thickness, the total gas delivery volume is obtained according to the number of iterations.

[0035] Optionally, the step size of the stepwise gas supply is 1 sccm.

[0036] A neutralization air supply control terminal based on Monte Carlo algorithm comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the neutralization air supply control method based on Monte Carlo algorithm as described above is implemented.

[0037] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the neutralization air supply control method based on the Monte Carlo algorithm as described above is implemented.

[0038] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the neutralization air supply control method based on the Monte Carlo algorithm as described above.

[0039] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0040] The present invention obtains the target target thickness and calculates the initial target thickness, then gradually adds neutralizing gas supply, iteratively calculates the supplementary target thickness in a step-by-step manner until the accumulated gas target thickness reaches the target target thickness, and finally outputs the control amount; the present invention accurately controls the neutralizing gas supply amount, so that the neutralization efficiency of each ion beam can reach the optimal state, thereby significantly improving the beam transmission efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings illustrate exemplary embodiments of the present invention and, together with the description thereof, are used to explain the principles of the present invention. These drawings are included to provide a further understanding of the present invention, and the accompanying drawings are included in and constitute a part of this specification and do not constitute a limitation of the embodiments of the present invention.

[0042] Figure 1 It is a flow chart of a neutralization air supply control method based on Monte Carlo algorithm according to the present invention.

[0043] Figure 2 It is a schematic flow chart of the method for obtaining the gas target thickness according to the present invention. DETAILED DESCRIPTION

[0044] To make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and implementation methods. It is understood that the specific implementation methods described herein are only used to explain the relevant content, rather than to limit the present invention.

[0045] It should also be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings.

[0046] In the absence of conflict, the embodiments and features of the embodiments of the present invention may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0047] Embodiment 1

[0048] like Figure 1As shown, a neutralization air supply control method based on Monte Carlo algorithm includes:

[0049] The gas target thickness required to achieve the best neutralization efficiency is determined by the energy of the high-energy ion beam and is used as the target target thickness.

[0050] In the neutral beam injection heating technology, the neutralization efficiency of the high energy ion beam is a key factor in determining the injection power and heating effect. In order to achieve the best neutralization efficiency, it is necessary to determine the appropriate gas target thickness. The gas target thickness refers to the product of the gas molecule density and the length of the target. In the present invention, the law of change of the neutralization efficiency of ion beams of different energies in the gas target is calculated by the energy of the high energy ion beam and the law of collision reaction between ions and gas molecules in the gas target, so as to determine the gas target thickness required for the best neutralization efficiency and use it as the target target thickness.

[0051] According to the amount of unionized gas in the ion source and the structure of the neutralizer, the Monte Carlo method was used to simulate the motion trajectory of gas molecules, the distribution of unionized gas in the neutralizer was calculated, and the initial gas target thickness was determined.

[0052] The Monte Carlo method is a numerical calculation method based on random sampling and statistical analysis, which is used to simulate complex systems and processes. In this embodiment, the Monte Carlo method is used to simulate the motion trajectory of unionized gas in the neutralizer to calculate the initial gas target thickness. First, the boundary conditions of the simulation are set according to the structural parameters of the neutralizer and the amount of unionized gas in the ion source. Then, by randomly generating particle emission directions that satisfy the cosine theorem, the motion trajectories of gas molecules are simulated one by one to determine whether they collide with the wall of the neutralizer or fly out of the boundary, and under specific conditions, new emission directions are reassigned to the particles to continue simulating their motion. By statistically analyzing the motion trajectories of a large number of particles, the distribution of unionized gas in the neutralizer is calculated, thereby determining the initial gas target thickness.

[0053] It is determined whether the initial gas target thickness reaches the target target thickness. If so, the gas supply volume is determined to be zero. If not, the gas supply to the neutralizer is simulated step by step for multiple times, and the supplementary target thickness is iteratively calculated until the gas target thickness reaches the target target thickness to obtain the total gas supply volume.

[0054] After determining the initial gas target thickness, it is necessary to determine whether it has reached the target target thickness. If the initial gas target thickness has reached the target target thickness, no additional gas supply is required and the gas supply volume is zero. If the target target thickness has not been reached, the gas target thickness is increased by gradually adding neutralizing gas to the neutralizer. After each addition of gas supply, the target thickness of the supplementary gas is calculated using the Monte Carlo method and added to the initial target thickness. This process is performed iteratively, gradually increasing the gas supply volume multiple times until the accumulated gas target thickness reaches the target target thickness, thereby obtaining the final total gas supply volume.

[0055] Determine the total gas delivery volume and output the corresponding control volume. According to the total gas delivery volume determined in the above steps, output the corresponding control volume to the gas mass flow controller to achieve real-time adjustment of the neutralizer target thickness. Ensure that the ion beam can achieve the best neutralization efficiency under different energy parameters, thereby improving the effect and energy efficiency of the neutral beam injection heating technology.

[0056] Embodiment 2

[0057] like Figure 2 As shown, a method for determining an initial gas target thickness is provided, comprising:

[0058] Determine the boundary conditions; boundary conditions include known parameters such as neutralizer structural parameters, amount of unionized gas in the ion source, gas supply position, calculation time, and background vacuum value, which are used to define the spatial and temporal scope of the simulation process.

[0059] A random number that satisfies the cosine theorem is used as the emission direction to make the simulated particles fly along the emission direction.

[0060] According to the law of cosines, a random number is assigned to each simulated particle as its emission direction, so that the particles can be emitted evenly in three-dimensional space and start flying along this emission direction.

[0061] During the particle flight, determine whether the simulated particle collides with a certain boundary. If no collision occurs (i.e., the simulated particle flies out of the boundary), emit the next simulated particle.

[0062] If the simulated particle collides with a certain boundary (i.e., does not fly out of the boundary), it is determined whether the flight time is greater than the set calculation time. If the flight time is greater than the calculation time, the next simulated particle is emitted;

[0063] If the flight time is less than the calculation time, a new emission direction is assigned to the simulated particle at the collision point, so that the simulated particle flies along the new emission direction; the new emission direction is also randomly generated according to the cosine theorem to ensure the diversity of the particle's flight direction and the accuracy of the simulation.

[0064] Repeat the above two judgments until the flight time of the simulated particle is equal to the calculation time, record the position of the simulated particle, and generate the next simulated particle;

[0065] The above simulated flight operation is performed on all simulated particles until the emission of all simulated particles is completed, and the positions and quantities of all particles in the area are statistically calculated, and the initial gas target thickness (integrated over the neutralizer length) is obtained by integration.

[0066] By simulating the motion trajectories of a large number of gas molecules, the distribution of unionized gas in the neutralizer is accurately calculated. Using the Monte Carlo method, the emission direction of particles is randomly generated and their flight process is simulated. By repeatedly judging and recording the position of particles, the initial gas target thickness is finally obtained.

[0067] Embodiment 3

[0068] The gas inlet position for replenishing the neutralizer is different from the gas inlet position for the initial gas; in order to increase the thickness of the gas target, the gas replenishment position is set in the middle of the neutralizer.

[0069] The method of iteratively superimposing the gas target thickness to reach the target target thickness is similar to the method of obtaining the initial gas target thickness in Example 2, and both are simulated and calculated by the Monte Carlo method. The specific steps mainly include:

[0070] Set the gas intake volume (small step size is better), and gradually approach the target thickness through multiple small step gas replenishments.

[0071] A neutralization gas supply volume of 1 step length is simulated and inputted into the neutralizer, and the subsequent operation calls the Monte Carlo method similar to that in the second embodiment.

[0072] A random number satisfying the cosine theorem is used as the emission direction, so that the simulated particles in the supplementary gas fly along the emission direction;

[0073] Determine whether the simulated particle collides with a certain boundary. If no collision occurs, emit the next simulated particle.

[0074] If the simulated particle collides with a certain boundary, it is determined whether the flight time is greater than the calculation time. If the flight time is greater than the calculation time, the next simulated particle is emitted;

[0075] If the flight time is less than the calculation time, a new emission direction is assigned to the simulated particle at the collision point, so that the simulated particle flies along the new emission direction;

[0076] Repeat the above two judgments until the flight time of the simulated particle is equal to the calculation time, record the position of the simulated particle, and generate the next simulated particle;

[0077] Complete the emission of all simulated particles in the supplementary gas, statistically calculate the positions and quantities of all particles in the area, and integrate to obtain the supplementary target thickness;

[0078] The supplementary target thickness and the initial gas target thickness are superimposed, and it is determined whether the superimposed gas target thickness reaches the target target thickness; if not, a step-length neutralization gas supply volume is simulated and input into the neutralizer again, and a new gas target thickness is iteratively calculated;

[0079] If the gas target thickness reaches the target target thickness, the total gas supply volume is calculated based on the number of iterations and the gas supply volume in each step, and the corresponding control volume is output to achieve accurate neutral gas supply control.

[0080] Optionally, the step size of the stepwise gas supply is 1 sccm, where sccm is the abbreviation of Standard Cubic Centimeters per Minute, which stands for standard cubic centimeters per minute and is a unit of measurement for gas flow, used to describe the volume of gas passing through per minute under standard conditions (usually 0°C and 1 atmosphere). This unit is commonly used in gas flow controllers and other devices that require precise measurement and control of gas flow.

[0081] By setting different gas inlet positions and using the Monte Carlo method to accurately simulate the movement trajectory of the supplementary gas, the neutralization gas supply volume can be gradually and accurately controlled to achieve the best neutralization efficiency. The supplementary target thickness is calculated through multiple iterations and added to the initial target thickness to ensure that the final gas target thickness reaches the preset target value, thereby improving the effect and efficiency of neutral beam injection.

[0082] Embodiment 4

[0083] A neutralization air supply control terminal based on Monte Carlo algorithm includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the neutralization air supply control method based on Monte Carlo algorithm is implemented.

[0084] The memory can be used to store software programs and modules. The processor executes various functional applications and data processing of the terminal by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an execution program required for at least one function, etc.

[0085] The data storage area can store data created according to the use of the terminal, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0086] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the neutralization air supply control method based on the Monte Carlo algorithm is implemented.

[0087] Without loss of generality, computer readable media may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer readable instruction data structures, program modules or other data. Computer storage media include RAM, ROM, EPROM, EEPROM, flash memory or other solid-state storage technology, CD-ROM, DVD or other optical storage, cassettes, magnetic tapes, disk storage or other magnetic storage devices. Of course, those skilled in the art will appreciate that computer storage media are not limited to the above. The above-mentioned system memory and mass storage devices can be collectively referred to as memory.

[0088] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the above-mentioned neutralization air supply control method based on the Monte Carlo algorithm.

[0089] The program can accurately control the neutralization gas supply volume, so that each shot can achieve the best neutralization efficiency, thereby improving the beam transmission efficiency; the neutralization gas supply volume is supplied on demand according to the program calculation, reducing the gas load of the injector vacuum chamber, and reducing the gas molecule density in the subsequent beam transmission path, thereby reducing re-ionization losses; the neutralization gas supply is supplied on demand according to the program calculation, which also reduces the gas molecule density at the extraction electrode, thereby reducing the stripping loss at the electrode; the input boundary conditions are few, and the input variables are only the beam energy parameters, which can be associated with the experimental parameter settings.

[0090] A computer program product includes a computer program or set of instructions for performing specific tasks or implementing specific functions. These programs or instructions are designed to be executed by a processor to implement a series of predefined steps or operations. The program product may be stored in various forms of computer storage media, such as memory, hard disk, solid-state drive, optical disk or other forms of digital storage devices. It may exist in the form of compiled binary code or in the form of scripts or bytecodes that can be executed by an interpreter. The program product uses carefully designed algorithms and logical instructions to enable the processor to process data in a specific order and manner to complete various functions such as data analysis, user interaction, device control, etc.

[0091] In the description of this specification, the description with reference to the terms "one embodiment / method", "some embodiments / methods", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment / method or example are included in at least one embodiment / method or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment / method or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments / methods or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments / methods or examples described in this specification and the features of the different embodiments / methods or examples, unless they are contradictory.

[0092] It should be understood by those skilled in the art that the above embodiments are only for the purpose of clearly illustrating the present invention, and are not intended to limit the scope of the present invention. For those skilled in the art, other changes or modifications may be made based on the above invention, and these changes or modifications are still within the scope of the present invention.

Claims

1. A neutralization air supply control method based on Monte Carlo algorithm, characterized in that: include: The gas target thickness required to achieve the best neutralization efficiency is determined by the energy of the high-energy ion beam and is used as the target target thickness; According to the amount of unionized gas in the ion source and the structure of the neutralizer, the Monte Carlo method is used to simulate the motion trajectory of gas molecules, calculate the distribution of unionized gas in the neutralizer, and determine the initial gas target thickness; Determine whether the initial gas target thickness reaches the target target thickness. If it has reached it, the gas supply volume is determined to be zero; if it has not reached it, simulate gas supply to the neutralizer step by step for multiple times, and iteratively calculate the supplementary target thickness until the gas target thickness reaches the target target thickness, and obtain the total gas supply volume; Determine the total air delivery volume and output the corresponding control volume.

2. A neutralization air supply control method based on Monte Carlo algorithm according to claim 1, characterized in that: Methods for determining the initial gas target thickness include: Determine boundary conditions; A random number that satisfies the cosine theorem is used as the emission direction, so that the simulated particles fly along the emission direction; Determine whether the simulated particle collides with a certain boundary. If no collision occurs, emit the next simulated particle. If a simulated particle collides with a certain boundary, it is determined whether the flight time is greater than the calculation time. If the flight time is greater than the calculation time, the next simulated particle is emitted; If the flight time is less than the calculation time, a new emission direction is assigned to the simulated particle at the collision point, so that the simulated particle flies along the new emission direction; Repeat the above two judgments until the flight time of the simulated particle is equal to the calculation time, record the position of the simulated particle, and generate the next simulated particle; Complete the emission of all simulated particles, statistically calculate the position and number of all particles in the area, and integrate to obtain the initial gas target thickness.

3. A neutralization air supply control method based on Monte Carlo algorithm according to claim 2, characterized in that: The boundary conditions include: structural parameters of the neutralizer, the amount of unionized gas in the ion source, gas supply position, calculation time and background vacuum value.

4. A neutralization air supply control method based on Monte Carlo algorithm according to claim 2, characterized in that: The initial gas target thickness is obtained by statistically calculating the position and number of particles in the region and integrating them over the length of the neutralizer.

5. The neutralization air supply control method based on Monte Carlo algorithm according to claim 2 is characterized in that: The air inlet position for replenishing air to the neutralizer is different from the air inlet position of the initial gas; the air inlet position for replenishing air is set in the middle of the neutralizer.

6. A neutralization air supply control method based on Monte Carlo algorithm according to claim 2, characterized in that: The method of iteratively superimposing gas target thickness to reach the target target thickness includes: Set the air intake volume of the step; Simulate input of a step-length neutralization air supply volume into the neutralizer; A random number satisfying the cosine theorem is used as the emission direction, so that the simulated particles in the supplementary gas fly along the emission direction; Determine whether the simulated particle collides with a certain boundary. If no collision occurs, emit the next simulated particle. If the simulated particle collides with a certain boundary, it is determined whether the flight time is greater than the calculation time. If the flight time is greater than the calculation time, the next simulated particle is emitted; If the flight time is less than the calculation time, a new emission direction is assigned to the simulated particle at the collision point, so that the simulated particle flies along the new emission direction; Repeat the above two judgments until the flight time of the simulated particle is equal to the calculation time, record the position of the simulated particle, and generate the next simulated particle; Complete the emission of all simulated particles in the supplementary gas, statistically calculate the positions and quantities of all particles in the area, and integrate to obtain the supplementary target thickness; The supplementary target thickness and the initial gas target thickness are superimposed, and it is determined whether the superimposed gas target thickness reaches the target target thickness; if not, a step-length neutralization gas supply volume is simulated and input into the neutralizer again, and a new gas target thickness is iteratively calculated; If the gas target thickness reaches the target target thickness, the total gas delivery volume is obtained according to the number of iterations.

7. A neutralization air supply control method based on Monte Carlo algorithm according to claim 6, characterized in that: The step size of the step-by-step gas supply is 1 sccm.

8. A neutralization gas supply control terminal based on Monte Carlo algorithm, 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, the neutralization air supply control method based on the Monte Carlo algorithm as described in any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the neutralization gas supply control method based on the Monte Carlo algorithm as described in any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the neutralization gas supply control method based on the Monte Carlo algorithm as described in any one of claims 1 to 7 is implemented.

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