Neutron tube performance optimization method

Abstract

The invention provides a neutron tube performance optimization method. The method comprises the following steps: determining a first distribution range of extraction configuration information of a deuterium ion extraction structure; based on the first distribution range and a preset ion source extraction electrode structure model, simulating and calculating optimal extraction performance information of the deuterium ions; setting extraction configuration information corresponding to the optimal extraction expression information as target configuration information of the deuterium ion extraction structure; determining a second distribution range of target configuration information of the target structure; based on the second distribution range and a preset neutron tube target model, simulating and calculating the optimal heat dissipation associated information of the target when the deuterium ion extraction structure applies the target configuration information; and setting the target configuration information corresponding to the optimal heat dissipation associated information as the target configuration information of the target. According to the technical scheme, the deuterium ion extraction structure and the target heat dissipation structure are synergistically optimized, and the performance of the neutron tube is remarkably improved.

Description

[Technical Field]

[0001] This application relates to the field of neutron tube technology, and in particular to a method for optimizing neutron tube performance. [Background Technology]

[0002] In the field of neutron tube technology, the extraction efficiency of deuterium ion beams and the heat dissipation performance of targets are key factors that determine the overall performance of the equipment; however, traditional design methods have significant limitations.

[0003] On the one hand, the design of existing deuterium ion extraction structures largely relies on empirical parameters, lacking a systematic analysis of electric field distribution, space charge effect, and beam transport characteristics. This leads to problems such as excessive divergence angle, uneven energy distribution, or low transport efficiency in the deuterium ion beam. On the other hand, the design of target heat dissipation structures often fails to dynamically adapt to the ion beam distribution, easily resulting in localized heat accumulation under high-temperature environments. This can cause deuterium-tritium desorption or thermal stress damage to the target material, thereby shortening the equipment's lifespan. Furthermore, the optimization processes for ion extraction and heat dissipation design in existing technologies are disconnected, making it difficult to achieve a synergistic improvement in overall performance.

[0004] Therefore, how to simultaneously solve the problems of efficient deuterium ion beam extraction and target heat dissipation uniformity through scientific modeling and multi-parameter collaborative optimization has become an urgent technical problem to be solved. [Summary of the Invention]

[0005] This application provides a method for optimizing the performance of a neutron tube, aiming to solve the technical problems affecting the working energy efficiency of neutron tubes, such as low deuterium beam transmission efficiency, uneven target heat dissipation, and insufficient optimization of extraction and heat dissipation.

[0006] In a first aspect, embodiments of this application provide a method for optimizing neutron tube performance, including:

[0007] Determine the first distribution range of the deuterium ion extraction configuration information;

[0008] Based on the first distribution range and the preset ion source extraction electrode structure model, the optimal extraction performance information of deuterium ions is simulated and calculated.

[0009] Set the extraction configuration information corresponding to the optimal extraction performance information as the target configuration information of the deuterium ion extraction structure;

[0010] When the target configuration information is applied to the deuterium ion extraction structure, a second distribution range of the target configuration information of the target structure is determined;

[0011] Based on the second distribution range and the preset neutron tube target model, the optimal heat dissipation correlation information of the target when the target configuration information is applied to the deuterium ion extraction structure is simulated and calculated.

[0012] Set the target configuration information corresponding to the optimal heat dissipation association information as the target configuration information of the target.

[0013] In one embodiment of this application, optionally, the extraction configuration information includes the shape, size, and electrode voltage distribution of the deuterium ion extraction structure, and the target configuration information includes the shape, size, material parameters, and boundary conditions of the target structure.

[0014] In one embodiment of this application, optionally, the step of simulating and calculating the optimal extraction performance information of deuterium ions based on the first distribution range and a preset ion source extraction electrode structure model includes:

[0015] Multiple sets of candidate extraction configuration information are dynamically combined within the first distribution range corresponding to the shape, size, and electrode voltage distribution of the deuterium ion extraction structure;

[0016] For each set of candidate extraction configuration information, based on the candidate extraction configuration information and the preset ion source extraction electrode structure model, the extraction performance information of the deuterium ion under the candidate extraction configuration information is simulated and calculated.

[0017] Based on the lead-out performance information under the candidate lead-out configuration information, determine the lead-out confidence level corresponding to the candidate lead-out configuration information;

[0018] The candidate extraction configuration information with the highest extraction confidence is determined as the optimal extraction performance information of the ion source extraction electrode structure model.

[0019] In one embodiment of this application, optionally, the extracted performance information includes deuterium ion current density, target surface energy density distribution, and deuterium ion divergence angle;

[0020] The step of determining the lead-out confidence level corresponding to the candidate lead-out configuration information based on the lead-out performance information under the candidate lead-out configuration information includes:

[0021] The deuterium ion current density, target surface energy density distribution, and deuterium ion divergence angle corresponding to the candidate extraction configuration information are encoded and normalized respectively to obtain the first feature value, the second feature value, and the third feature value.

[0022] Based on the first eigenvalue, the second eigenvalue, and the third eigenvalue, as well as the respective performance weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle, a deuterium ion extraction performance matrix is ​​constructed.

[0023] Based on the deuterium ion extraction performance matrix, the extraction confidence level corresponding to the candidate extraction configuration information is determined.

[0024] In one embodiment of this application, optionally, constructing a deuterium ion extraction performance matrix based on the first eigenvalue, the second eigenvalue, and the third eigenvalue, as well as the respective performance weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle, includes:

[0025] The element in the m-th row and n-th column of the deuterium ion extraction performance matrix is ​​set to the weighted average of the first and second specified parameters, where,

[0026] The first specified parameter is the difference between the m-th eigenvalue and the mean of the eigenvalues ​​among the first, second, and third eigenvalues, and the second specified parameter is the difference between the n-th weight and the mean of the weights of the respective weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle.

[0027] In one embodiment of this application, optionally, the step of simulating and calculating the optimal extraction performance information of deuterium ions based on the first distribution range and a preset ion source extraction electrode structure model includes:

[0028] Based on a preset genetic algorithm, the multi-objective optimization combination result of the ion source extraction electrode structure model is determined within the first distribution range, and is used as the optimal extraction performance information of the deuterium ion.

[0029] In one embodiment of this application, optionally, the step of simulating and calculating the optimal heat dissipation correlation information of the target when the target configuration information is applied to the deuterium ion extraction structure based on the second distribution range and a preset neutron tube target model includes:

[0030] Multiple sets of candidate target configuration information are dynamically combined within the second distribution range corresponding to the shape, size, material parameters and boundary conditions of the target structure;

[0031] For each set of target configuration information, based on the target configuration information and the preset neutron tube target model, the heat dissipation correlation information after deuterium ion target bombardment is simulated and calculated.

[0032] Based on the heat dissipation correlation information under the candidate target configuration information, the target heat dissipation confidence level corresponding to the candidate target configuration information is determined;

[0033] The target configuration information of the target heat dissipation confidence is determined as the optimal heat dissipation correlation information of the neutron tube target model.

[0034] Optionally, in one embodiment of this application, the heat dissipation-related information includes target temperature distribution information, target manufacturing cost information, and target usage reliability.

[0035] The step of determining the target heat dissipation confidence level corresponding to the target configuration information based on the heat dissipation correlation information under the target configuration information includes:

[0036] The target temperature distribution information, target manufacturing cost information, and target usage reliability corresponding to the candidate target configuration information are encoded and normalized respectively to obtain the fourth feature value, the fifth feature value, and the sixth feature value.

[0037] The temperature distribution difference parameter between the fourth characteristic value and the preset standard distribution characteristic value is determined; the cost difference parameter between the fifth characteristic value and the preset standard cost characteristic value is determined; and the reliability difference parameter between the sixth characteristic value and the preset standard reliability characteristic value is determined.

[0038] Based on the temperature distribution difference parameter, the cost difference parameter, and the reliability difference parameter, as well as the weights corresponding to the target temperature distribution information, target manufacturing cost information, and target usage reliability, a target heat dissipation performance matrix is ​​constructed.

[0039] Based on the target heat dissipation performance matrix, the target heat dissipation confidence level corresponding to the candidate target configuration information is determined.

[0040] In a second aspect, embodiments of this application provide a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being configured to perform the method described in the first aspect above.

[0041] Thirdly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions for performing the method described in the first aspect above.

[0042] The above technical solutions address the technical problems affecting the energy efficiency of neutron tubes, such as low deuterium ion beam transmission efficiency, uneven target heat dissipation, and insufficient synergistic optimization of extraction and heat dissipation. This solution proposes a method for overall neutron tube performance optimization. By optimizing the synergistic design of the deuterium ion extraction structure and the target heat dissipation structure in stages, the performance of key components of the neutron tube is improved. First, parametric modeling and multi-objective optimization algorithms are used to accurately design the extraction structure, ensuring high transmission efficiency and low divergence characteristics of the deuterium ion beam. Then, based on the optimized ion beam parameters, the heat dissipation performance of the target structure is matched through simulation, ultimately obtaining an overall solution that balances beam quality, heat dissipation efficiency, and structural reliability. This solution significantly improves neutron tube performance through the synergistic optimization of the deuterium ion extraction structure and the target heat dissipation structure. The optimized extraction structure results in higher beam transmission efficiency and a smaller divergence angle, while the improved heat dissipation design reduces target material temperature and extends service life. The combination of intelligent algorithms and numerical simulation shortens the design cycle, reduces development costs, and provides a reliable solution for the engineering application of high-performance neutron tubes. This approach solves the technical challenge of parameter fragmentation in traditional designs. The optimized extraction structure significantly improves beam transmission efficiency, markedly enhances target surface temperature uniformity, and greatly improves neutron yield stability. Simultaneously, the synergistically optimized heat dissipation design effectively reduces target operating temperature and thermal stress, significantly extending the lifespan of the neutron tube and its components. Furthermore, the combination of intelligent algorithms and numerical simulations significantly shortens the design cycle and reduces prototyping costs. This holistic optimization method not only overcomes the performance bottleneck of neutron tubes but also provides a standardized design paradigm for the engineering development of compact, long-life neutron tubes, holding significant value in various application fields. [Attached Image Description]

[0043] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A flowchart of a neutron tube performance optimization method according to an embodiment of this application is shown;

[0045] Figure 2 A schematic diagram simulating the equipotential line distribution of the extraction structure and the trajectory of deuterium ions using charged particle transport software is shown according to an embodiment of this application.

[0046] Figure 3 A schematic diagram of a temperature simulation of Gaussian-distributed deuterium ions bombarding a titanium target using computational fluid dynamics software is shown according to an embodiment of this application.

[0047] Figure 4 A block diagram of a computer device according to one embodiment of this application is shown;

[0048] Figure 5 A block diagram of a computer device according to another embodiment of this application is shown.

Detailed Implementation Methods

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Figure 1 A flowchart of a neutron tube performance optimization method according to an embodiment of this application is shown.

[0051] like Figure 1 As shown, a neutron tube performance optimization method according to an embodiment of this application includes:

[0052] Step 102: Determine the first distribution range of the deuterium ion extraction configuration information.

[0053] The deuterium ion extraction structure is the core component of the neutron tube. It is responsible for efficiently and controllably extracting deuterium ions generated by the ion source and forming a beam for subsequent acceleration and bombardment of the target material (such as a titanium-tritium target) to generate neutrons. It achieves the focusing, acceleration and transmission of deuterium ions through electric field control, which directly affects the beam quality, yield and stability of the neutron tube.

[0054] The extraction configuration information of the deuterium ion extraction structure is a set of key parameters that directly affect beam performance. This extraction configuration information includes the shape, size, and electrode voltage distribution of the deuterium ion extraction structure. The shape refers to the geometric contour of the extraction electrode, such as an arc or cone shape; the size involves specific physical quantities such as length, width, height, and aperture; and the electrode voltage distribution characterizes the configuration of the accelerating electric field gradient. These parameters directly determine the transmission characteristics of the deuterium ion beam. For example, an extraction outlet with a specific curvature can reduce electric field distortion, and a staged voltage gradient can suppress the space charge effect. By systematically incorporating these design elements into the optimization process, the electric field distribution and ion trajectory can be comprehensively controlled, thereby reducing the beam divergence angle while improving transmission efficiency, ultimately achieving high-quality extraction of the deuterium ion beam and providing a stable and uniform ion source for subsequent target bombardment.

[0055] The first distribution range of the extraction configuration information refers to the possible value range of key parameters of the deuterium ion extraction structure, such as the range of the radius of curvature of the extraction port or the range of the voltage gradient of the accelerating electrode. More specifically, for example, the radius of curvature of the extraction port shape ranges from five millimeters to fifteen millimeters to ensure a balance between electric field uniformity and structural strength; the electrode spacing ranges from two millimeters to ten millimeters to precisely control the acceleration gradient and avoid high-voltage breakdown; the voltage gradient range is selected from three kilovolts per millimeter to ten thousand volts per millimeter to achieve the best match between efficient ion focusing and energy transfer; the electrode aperture range is limited to one millimeter to five millimeters to adapt to different beam current density requirements and ensure transmission efficiency. These parameter ranges are all determined based on the theoretical calculations of the limiting electromagnetic field of materials physics and actual test data, providing a scientifically feasible search space for subsequent optimization, while avoiding performance degradation or structural failure caused by unreasonable parameter combinations.

[0056] This range defines the search space for subsequent optimizations, ensuring that the design parameters remain within physically realizable limits. By clearly defining the reasonable variation range of each parameter, scientific constraints are provided for subsequent simulation calculations, avoiding the waste of computational resources caused by blind simulations, thereby improving optimization efficiency and ensuring the feasibility of the results.

[0057] Step 104: Based on the first distribution range and the preset ion source extraction electrode structure model, simulate and calculate the optimal extraction performance information of deuterium ions.

[0058] Using IBSimu software, a model of the ion source extraction electrode structure can be established through precise electromagnetic field simulation and particle tracking technology. This modeling process involves first constructing a two-dimensional or three-dimensional model based on the actual electrode geometry. Then, the spatial potential distribution is calculated by solving the Poisson equation, taking into account the space charge effect. The Runge-Kutta method is used to track the trajectory of deuterium ions in the electromagnetic field. Key parameters such as beam envelope, divergence angle, and energy distribution are analyzed. Through parametric scanning and iterative optimization, the electrode shape, size, and voltage configuration are optimized to obtain an optimized design scheme with minimum beam divergence and highest transmission efficiency. This provides a reliable theoretical basis and performance prediction for the actual ion source extraction structure.

[0059] The optimal extraction performance information is the optimal solution of the deuterium ion beam characteristics obtained by simulation calculation through the ion source extraction electrode structure model. It includes indicators such as deuterium ion current density, target surface energy density distribution and deuterium ion divergence angle. For example, the beam current density reaches a uniform distribution at the microampere level per square millimeter.

[0060] Simulations based on the ion source extractor structure model within the first distribution range can comprehensively evaluate the impact of different parameter combinations on beam quality. By replacing the traditional trial-and-error method with numerical simulation, the mapping relationship between parameters and performance can be accurately revealed, thereby quickly identifying the parameter combination that maximizes beam transmission efficiency and significantly improving design accuracy.

[0061] In one possible design, multiple sets of candidate extraction configuration information are dynamically combined within a first distribution range corresponding to the shape, size, and electrode voltage distribution of the deuterium ion extraction structure. For each set of candidate extraction configuration information, the extraction performance information of the deuterium ions under the candidate extraction configuration information is simulated and calculated based on the candidate extraction configuration information and a preset ion source extraction electrode structure model. Based on the extraction performance information under the candidate extraction configuration information, the extraction confidence level corresponding to the candidate extraction configuration information is determined. The candidate extraction configuration information with the highest extraction confidence level is determined as the optimal extraction performance information of the ion source extraction electrode structure model.

[0062] In the optimization design of deuterium ion extraction structures, multiple sets of candidate extraction configurations can be dynamically combined within reasonable ranges of their shape, size, and electrode voltage distribution. Shape includes the curvature of the extraction port, size encompasses electrode spacing and aperture, and electrode voltage distribution relates to the configuration of the acceleration gradient. These parameters combine to form different design schemes, such as using an extraction port with a specific curvature and a staged voltage gradient. Simulation calculations are performed on each candidate configuration based on a pre-defined ion source extraction electrode structure model, accurately evaluating the transmission characteristics of the deuterium ion beam, including key indicators such as flux density, divergence angle, and energy distribution. By analyzing this extraction performance information and calculating its corresponding extraction confidence level, the performance of each configuration can be quantified. This confidence level reflects the reliability of the extraction performance information in practical applications. Finally, the candidate configuration with the highest confidence level is determined as the optimal extraction performance information. This process realizes the transformation from theoretical simulation to engineering design, ensuring that the obtained optimized scheme has both high transmission efficiency and stability, laying the foundation for subsequent performance improvements of the neutron tube.

[0063] The specific calculation method for the extraction confidence is as follows: the deuterium ion current density, target surface energy density distribution, and deuterium ion divergence angle corresponding to the candidate extraction configuration information are encoded and normalized respectively to obtain a first feature value, a second feature value, and a third feature value; based on the first feature value, the second feature value, and the third feature value, as well as the performance weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle, a deuterium ion extraction performance matrix is ​​constructed; based on the deuterium ion extraction performance matrix, the extraction confidence corresponding to the candidate extraction configuration information is determined.

[0064] In the optimization of the deuterium ion extraction structure, the extraction confidence is calculated by quantifying key performance indicators. Among them, the deuterium ion current density reflects the beam intensity, the target surface energy density distribution characterizes the bombardment uniformity, and the deuterium ion divergence angle reflects the beam focusing effect. These indicators are converted into comparable first, second, and third eigenvalues ​​after encoding and normalization.

[0065] Next, by combining the performance weights of each indicator, a deuterium ion extraction performance matrix is ​​constructed. For example, a higher weight is given to flux density, which has a greater impact on overall performance. This matrix comprehensively reflects the overall performance characteristics of the beam under different configurations. Determining the extraction confidence level based on matrix analysis allows for an objective evaluation of the merits of each candidate configuration, thus avoiding biases caused by subjective judgment. Ultimately, the extraction structure design scheme with the best performance in beam intensity, bombardment uniformity, and focusing effect is selected, significantly improving the ion transport efficiency of the neutron tube and the lifespan of the target material.

[0066] Furthermore, the element in the m-th row and n-th column of the deuterium ion extraction performance matrix can be set as the weighted average of the first specified parameter and the second specified parameter. The first specified parameter is the difference between the m-th eigenvalue and the mean of the eigenvalues ​​among the first, second, and third eigenvalues. The second specified parameter is the difference between the n-th weight and the mean of the weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle.

[0067] In the deuterium ion extraction performance evaluation process, the deuterium ion extraction performance matrix is ​​constructed, where the matrix elements are calculated from two key parameters. The first parameter reflects the degree to which a specific characteristic value deviates from the overall average level; for example, if the current density characteristic value of a certain configuration is significantly higher than the average, it indicates excellent beam intensity. The second parameter reflects the relative importance of the weights of each performance indicator; for example, if the weight of the divergence angle is significantly higher than the average, it indicates that the focusing effect is more critical in this design.

[0068] By weighting the differences in eigenvalues ​​and weights, the matrix elements can capture the outstanding performance of each configuration on a single metric while also taking into account the differences in importance of different metrics. This dynamic balance calculation method enables the performance matrix to reflect the overall performance level of each set of derived configurations more comprehensively and accurately.

[0069] Therefore, based on the confidence level determined by this matrix, the evaluation results are more objective and reliable. It can identify configuration schemes that perform well in key indicators, and avoid ignoring the overall performance balance due to the advantage of a single indicator. Ultimately, it helps to select the best extraction structure design that coordinates and optimizes various aspects such as beam intensity, energy distribution uniformity and focusing effect, and provides a scientific basis for improving the overall performance of neutron tubes.

[0070] Step 106: Set the extraction configuration information corresponding to the optimal extraction performance information as the target configuration information of the deuterium ion extraction structure.

[0071] The target configuration information is the optimal set of parameters determined through optimization, such as using an extraction outlet with a specific curvature and a staged voltage gradient configuration. The simulated optimal results are then translated into actual structural parameters, completing the transition from theory to design. This ensures that the optimization results directly guide production, enabling the extraction structure to possess high beam current density and low divergence angle characteristics, ultimately achieving efficient and stable deuterium ion extraction and laying the foundation for subsequent target heat dissipation design.

[0072] In another possible design, a multi-objective optimization combination result of the ion source extraction electrode structure model can be determined within the first distribution range based on a preset genetic algorithm, which can be used as the optimal extraction performance information of the deuterium ions.

[0073] In the optimized design of deuterium ion extraction structures, genetic algorithms can be used as intelligent search tools. This method simulates the biological evolution process, efficiently exploring the parameter space through operations such as selection, crossover, and mutation. The first distribution range defines the feasible domain of key parameters such as electrode shape, size, and voltage; for example, the radius of curvature of the extraction outlet varies within a reasonable range. Genetic algorithms can simultaneously consider multiple optimization objectives, such as maximizing beam density and minimizing divergence angle, gradually approaching the optimal solution set through iterative evolution, avoiding the limitations of traditional methods that get stuck in local optima.

[0074] Thus, this optimization process based on the principle of natural selection has greatly improved design efficiency, enabling the rapid locking of the globally optimal or near-optimal extraction structure configuration in a complex multi-parameter space. This not only ensures that the deuterium ion beam has high transmission efficiency and low divergence characteristics, but also provides a design scheme that combines performance and feasibility for engineering practice, effectively promoting the overall performance improvement of neutron tubes.

[0075] like Figure 2 As shown in the figure, the optimized extraction structure characteristics of this invention are visually demonstrated using charged particle transport software. The equipotential lines in the figure clearly demonstrate the uniformity of the electric field under the optimized geometry, avoiding the edge distortion phenomenon commonly seen in traditional designs. The deuterium ion trajectory simulation results show that the ion beam has a highly concentrated motion path and a very small divergence angle, verifying the precise control capability of the optimized extraction structure over the beam. This demonstrates that the technical solution of this application has significant effects in improving the electric field distribution and enhancing beam quality.

[0076] Step 108: When the target configuration information is applied to the deuterium ion extraction structure, determine the second distribution range of the target configuration information of the target structure.

[0077] The target structure is the core component of the neutron tube, usually composed of metals such as titanium and magnesium and their deuterides / tritides. Its main function is to receive high-energy deuterium ion beams and trigger nuclear reactions (DD or DT reactions) to produce neutrons. Its performance directly determines the neutron yield, energy distribution and equipment lifespan.

[0078] Target configuration information includes target shape (e.g., planar / curved), dimensions (thickness and area), material parameters (thermal conductivity, deuterium loading), and boundary conditions (cooling method, thermal contact interface). These parameters collectively reflect factors that influence the neutron tube's operating efficiency, such as heat dissipation efficiency, resistance to radiation damage, and neutron yield stability. Optimized configuration can balance thermal management requirements with nuclear reaction efficiency, ensuring long-term stable operation of the neutron tube under high temperature and high radiation conditions.

[0079] The target configuration information includes the shape, size, material parameters, and boundary conditions of the target structure. The second distribution range of the target configuration information covers the feasible domain of parameters such as shape, size, material parameters, and boundary conditions. For example, the target material thickness ranges from 0.1 mm to 1 mm to balance neutron yield and heat dissipation efficiency; the cooling channel spacing is set from 0.5 mm to 3 mm to optimize heat exchange area and fluid resistance; and the target surface curvature radius is selected from 5 mm to 20 mm to accommodate the uniformity of heat distribution at different beam bombardment angles. These parameter ranges comprehensively consider the thermophysical properties, hydrodynamic performance, and actual process limitations of the materials, ensuring that the heat dissipation design meets thermal management requirements while maintaining structural reliability and neutron generation efficiency.

[0080] Thus, this range, combined with the optimized ion beam characteristics, ensures that the heat dissipation design matches the actual heat source distribution. By defining the boundaries of target parameter variations, targeted constraints are provided for thermal management optimization, avoiding a decrease in heat dissipation efficiency due to parameter conflicts, making subsequent thermal analysis more engineering-oriented.

[0081] Step 110: Based on the second distribution range and the preset neutron tube target model, simulate and calculate the optimal heat dissipation correlation information of the target when the target configuration information is applied to the deuterium ion extraction structure.

[0082] The heat dissipation-related information includes target temperature distribution information, target manufacturing cost information, and target reliability.

[0083] The target temperature distribution information reflects the thermal management efficiency of the target material under continuous bombardment by deuterium ions, and directly determines the risk of local overheating and the level of thermal stress. Uneven distribution may lead to local ablation of the target material or deuterium-tritium desorption, affecting the stability of neutron yield.

[0084] The cost information for target manufacturing reflects the economics of material selection and processing technology, including the amount of rare materials used and the difficulty of precision machining. Only by achieving a balance between performance and cost can production feasibility be ensured.

[0085] The reliability of the target is comprehensively evaluated by assessing the fatigue resistance and performance degradation of the target structure under long-term irradiation and thermal cycling, which is related to the maintenance cycle and service life of the neutron tube.

[0086] These three factors together constitute the core dimensions for evaluating the quality of a target structure: temperature distribution ensures short-term operational safety, cost control affects the possibility of mass production, and reliability determines long-term stability. By synergistically optimizing these indicators, the optimal configuration of neutron tubes in terms of performance, economy, and durability can be achieved.

[0087] Optimal heat dissipation correlation information represents the comprehensive optimal solution for the target structure in terms of thermal uniformity, reliability, and cost, such as the temperature field distribution of a specific honeycomb heat dissipation structure. Based on ion beam parameters, the thermal behavior of the target can be simulated, allowing for a quantitative assessment of the performance differences between different heat dissipation schemes. Therefore, through multiphysics coupling analysis, heat dissipation efficiency and structural reliability can be optimized simultaneously, effectively suppressing thermal damage to the target material and extending the neutron tube's lifespan while controlling costs.

[0088] Specifically, multiple sets of candidate target configuration information can be dynamically combined within the second distribution range corresponding to the shape, size, material parameters, and boundary conditions of the target structure. For each set of candidate target configuration information, the heat dissipation correlation information after deuterium ion bombardment is simulated and calculated based on the candidate target configuration information and the preset neutron tube target model. Based on the heat dissipation correlation information under the candidate target configuration information, the target heat dissipation confidence level corresponding to the candidate target configuration information is determined. The candidate target configuration information with the target heat dissipation confidence level is determined as the optimal heat dissipation correlation information of the neutron tube target model.

[0089] In target structure optimization design, multiple sets of target configuration information can be obtained by dynamically combining the target's shape, size, material parameters, and boundary conditions within their respective reasonable ranges of variation. The shape includes planar or curved structures, the size encompasses thickness and area specifications, the material parameters involve thermal conductivity and heat capacity characteristics, and the boundary conditions consider factors such as cooling methods and contact thermal resistance. These parameter combinations form different design schemes.

[0090] The neutron tube target model is a digital model established through computer simulation to simulate and optimize the target structure performance. The model is built based on the actual physical properties of the target material and the working environment, and includes key elements such as geometric structure, material parameters and boundary conditions. Among them, the geometric structure covers the target surface, with shapes such as planes or curved surfaces, and dimensional parameters such as thickness and area. Material parameters include thermophysical properties such as thermal conductivity, specific heat capacity and radiation resistance. Boundary conditions involve external constraints such as cooling methods such as liquid cooling or gas cooling and thermal contact conditions.

[0091] By incorporating the energy distribution of the deuterium ion beam as the heat source input, this model can accurately calculate key indicators such as the temperature field distribution, thermal stress state, and heat dissipation efficiency of the target under ion bombardment. Furthermore, it combines multiphysics coupling analysis to evaluate the heat dissipation performance and structural reliability of different target configurations. Using this model, target structures can be parametrically designed and optimized, ultimately selecting target structure schemes that maintain stable performance under high-temperature and high-irradiation environments. This provides a scientific basis for extending the lifespan of neutron tubes and increasing neutron yield.

[0092] Furthermore, based on a pre-defined neutron tube target model, simulations are performed on each candidate configuration to comprehensively evaluate the heat dissipation performance after deuterium ion bombardment, including key indicators such as temperature distribution, thermal stress, and cooling efficiency. By analyzing this heat dissipation correlation information and calculating its corresponding target heat dissipation confidence level, the heat dissipation efficiency of each configuration can be quantified. This target heat dissipation confidence level reflects the reliability of the configuration in actual operation. Finally, the candidate configuration with the highest target heat dissipation confidence level is determined as the optimal heat dissipation correlation information. This process realizes the transformation from numerical simulation to engineering application, ensuring that the obtained optimized scheme has both efficient heat dissipation and structural stability, thus providing a guarantee for improving the reliability and service life of the neutron tube.

[0093] In one possible design, the target heat dissipation confidence level is calculated as follows: The target temperature distribution information, target manufacturing cost information, and target usage reliability corresponding to the candidate target configuration information are encoded and normalized to obtain a fourth feature value, a fifth feature value, and a sixth feature value; a temperature distribution difference parameter between the fourth feature value and a preset standard distribution feature value is determined; a cost difference parameter between the fifth feature value and a preset standard cost feature value is determined; and a reliability difference parameter between the sixth feature value and a preset standard reliability feature value is determined; based on the temperature distribution difference parameter, the cost difference parameter, and the reliability difference parameter, as well as the respective weights of the target temperature distribution information, target manufacturing cost information, and target usage reliability, a target heat dissipation performance matrix is ​​constructed; and based on the target heat dissipation performance matrix, the target heat dissipation confidence level corresponding to the candidate target configuration information is determined.

[0094] In the target structure optimization design, the calculation of target heat dissipation confidence is achieved by systematically evaluating key performance indicators. Among them, the target temperature distribution information reflects the heat dissipation uniformity, the target manufacturing cost information reflects economic feasibility, and the target use reliability characterizes long-term stability. These indicators are converted into quantifiable fourth, fifth, and sixth characteristic values ​​after encoding and normalization.

[0095] Next, by comparing each characteristic value with a preset standard value, the temperature distribution difference parameter, cost difference parameter, and reliability difference parameter are obtained. These parameters represent the degree of deviation between the actual performance and the ideal target. For example, the smaller the temperature difference parameter, the more uniform the heat dissipation.

[0096] By combining the weighting of various indicators—for example, prioritizing temperature control when heat dissipation performance is given a higher weight—a target heat dissipation performance matrix is ​​constructed to comprehensively evaluate the advantages and disadvantages of different configurations. This matrix integrates the differences across various dimensions through weighted calculations to form a comprehensive evaluation of the target structure's performance, thereby calculating the target heat dissipation confidence level. This quantitative result objectively reflects the comprehensive performance of each configuration in terms of heat dissipation efficiency, cost control, and operational reliability. Ultimately, the optimal solution is selected based on the target heat dissipation confidence level, ensuring that the target structure meets the heat dissipation requirements under high-temperature environments while also considering production costs and service life, providing a scientific basis for improving the overall performance of neutron tubes.

[0097] like Figure 3 As shown, computational fluid dynamics simulations visually demonstrate the optimized thermal management performance of the titanium target. The temperature field distribution in the figure shows uniform heat diffusion in the deuterium ion beam bombardment region, with no localized high-temperature hotspots, verifying the effectiveness of the target structure optimization. The simulation results clearly demonstrate the energy deposition characteristics of the ion beam on the target surface, as well as the improved temperature gradient resulting from the optimized heat dissipation structure. This indicates that the technical solution of this application has significant effects in controlling the operating temperature of the target material and avoiding thermal stress concentration.

[0098] Step 112: Set the target configuration information corresponding to the optimal heat dissipation association information as the target configuration information of the target.

[0099] The target configuration information is the final design scheme after heat dissipation optimization, such as using gradient porous materials in conjunction with directional cooling channels. At this point, the optimal simulation solution is transformed into actual target structural parameters, realizing the embedding of the thermal management scheme. This ensures that the target body has a uniform temperature distribution and controllable thermal stress when subjected to the optimized ion beam, ultimately achieving the best balance between efficiency, stability, and lifespan for the overall neutron tube performance.

[0100] In summary, this technical solution proposes a method for optimizing the overall performance of a neutron tube. By optimizing the deuterium ion extraction structure and the target heat dissipation structure in stages, the performance of key components of the neutron tube is improved.

[0101] First, parametric modeling and multi-objective optimization algorithms are used to accurately design the extraction structure to ensure that the deuterium ion beam has high transmission efficiency and low divergence characteristics. Then, based on the optimized ion beam parameters, the heat dissipation performance of the target structure is matched through simulation, and finally an overall solution that takes into account beam quality, heat dissipation efficiency and structural reliability is obtained.

[0102] This scheme solves the technical challenge of parameter fragmentation in traditional designs by establishing an integrated optimization system for neutron tube extraction and heat dissipation. The optimized extraction structure significantly improves beam transmission efficiency, markedly enhances target surface temperature uniformity, and greatly improves neutron yield stability. Simultaneously, the synergistically optimized heat dissipation design effectively reduces the target material's operating temperature and thermal stress, significantly extending the service life of the neutron tube and its components. Furthermore, the combination of intelligent algorithms and numerical simulations significantly shortens the design cycle and reduces prototyping costs.

[0103] In the technical solution of this application, regarding the optimized design of the ion extraction structure, numerical simulation and modeling analysis are first used to lay a theoretical foundation for subsequent optimization. A precise ion source extraction electrode structure model is established using professional simulation software such as IBSimu, and combined with advanced particle tracking algorithms, the entire process of deuterium ion generation and extraction is simulated with high precision. The simulation process focuses on examining the influence of the extraction structure on beam characteristics, including the variation characteristics of key performance indicators such as beam density distribution, divergence angle, and energy uniformity.

[0104] In terms of specific optimization measures, a systematic parameter adjustment strategy is adopted to improve beam quality. The exit point, as a key part for ion extraction, directly determines the uniformity of the electric field distribution through its geometric configuration. Optimizing the exit point shape using smooth curves or symmetrical structures can effectively suppress electric field distortion caused by edge effects. This distortion often disrupts ion trajectories, leading to increased beam divergence angle and reduced transmission efficiency. An optimized exit point structure ensures efficient extraction of deuterium ions at the optimal divergence angle, significantly improving beam quality. Simultaneously, the voltage gradient configuration of the accelerating electrodes has a decisive impact on ion acceleration and focusing. Scientifically setting the voltage distribution of the accelerating electrodes provides an ideal acceleration and focusing environment for deuterium ions. Specifically, appropriately increasing the electric field strength near the exit point helps improve the initial kinetic energy of the ions, while gradually decreasing the field strength in the subsequent transmission region effectively alleviates the space charge effect and prevents excessive beam diffusion due to interparticle repulsion. This optimized voltage gradient configuration also minimizes energy loss, further improving beam transmission efficiency.

[0105] In terms of performance evaluation, three key indicators were examined: the uniformity of deuterium ion distribution to avoid local over-density or sparseness; the beam divergence angle to ensure it is controlled within the optimal range to improve transmission efficiency; and the energy distribution characteristics to minimize energy loss caused by uneven electric field. These simulation data clearly reveal the intrinsic relationship between the extraction structure design parameters and beam transmission performance, providing a solid theoretical basis for subsequent optimization work.

[0106] Through synergistic optimization of the aforementioned key parameters, the overall performance of the extraction structure was improved. The core objective of the optimization was to enable the deuterium ion beam to possess three main characteristics: high beam density (manifested as a uniform ion distribution, avoiding local concentration anomalies), small divergence angle (ensuring concentrated ion trajectories and reducing energy dissipation), and stable energy distribution (ensuring the consistency of ion energy during extraction). This systematic optimization strategy significantly improved the transmission efficiency and quality of the deuterium ion beam, providing a stable and reliable ion source for subsequent target bombardment.

[0107] Specifically, in establishing the structural model of the ion source extractor, professional simulation software such as IBSimu is used for precise modeling. During modeling, the specific geometric dimensions of the extractor must first be determined. This can be achieved in two ways: first, by directly importing a pre-designed 3D or 2D CAD model of the extractor into the software; second, by describing the surface contour of the extractor through mathematical equations within the software interface, thus constructing a closed 2D or 3D geometric structure. After completing the geometric modeling, the system will perform high-precision tracking simulation of the complete trajectory of deuterium ions from generation to extraction.

[0108] In electric field calculations, the voltage distribution applied to the extraction poles is determined by solving the Poisson equation. To determine, where φ represents the spatial potential distribution, ρ is the charge density, and ε is the vacuum permittivity.

[0109] For the trajectory of charged particles in an electromagnetic field, the Lorentz force equation F = q(E + v × B) is solved using the Runge-Kutta numerical iteration method. Here, F represents the electromagnetic force on the ion, q is the ion charge, E is the electric field strength, and v and B represent the ion velocity and magnetic induction intensity, respectively.

[0110] To accurately simulate the space charge effect, the computational domain is discretized into a grid using the PIC (particle mesh) method, and the charge density generated by ion motion is distributed to the corresponding grid nodes for self-consistent calculation.

[0111] By adjusting the geometric dimensions and shape parameters of the extraction structure, the electric field distribution characteristics of the extraction region can be systematically altered. Numerical simulations are then performed based on these adjustments to calculate the beam envelope of ions under electromagnetic field influence, thereby optimizing the configuration to achieve maximum beam transmission efficiency. The simulation process meticulously records information such as the spatial position, kinetic energy, and incident angle of the particles upon reaching the target surface. This data allows for statistical analysis of the particle distribution characteristics on the target surface. A key focus is evaluating the uniformity of the energy density distribution on the target surface to prevent excessively high local energy deposition that could lead to abnormally high target temperatures and subsequently desorption of adsorbed deuterium or tritium atoms. Simultaneously, the influence of the extraction structure on the divergence angle of the deuterium ion beam is investigated in depth. The full width at half maximum (FWHM) index is used to quantitatively characterize the divergence angle, ensuring that the optimized beam neither collides with the tube wall during transmission nor is effectively focused entirely onto the target working area. This systematic optimization method significantly improves the transmission efficiency and quality of the deuterium ion beam.

[0112] In the optimized design of the neutron tube target heat dissipation structure, a precise thermal analysis model of the target is first established using finite element analysis software. This modeling process includes three key steps: geometric modeling, which constructs a three-dimensional solid model containing all detailed features based on the actual structural dimensions of the neutron tube target; material parameter setting, which assigns accurate thermophysical parameters to each component in the model, including key parameters such as thermal conductivity, specific heat capacity, and density, and considers the variation characteristics of these parameters at actual operating temperatures; and boundary condition definition, which realistically simulates the operating conditions of the neutron tube, including input power parameters, cooling conditions, and the spatial distribution characteristics of the heat source, where the heat source distribution data is directly derived from the ion distribution results obtained in the previous beam simulation.

[0113] Based on the finite element analysis results, all design schemes were systematically evaluated and optimized. The evaluation process strictly followed multi-objective optimization criteria, balancing requirements from multiple dimensions such as heat dissipation performance, economic cost, and structural reliability, ultimately selecting the balanced scheme with the best overall performance. To ensure the feasibility of the design schemes, several optimized schemes were selected and physical prototypes were fabricated. Operational data was obtained through actual measurements and compared with simulation results for verification. Based on this, model parameters were adjusted and the design schemes were further optimized.

[0114] The optimized heat dissipation system effectively controls the temperature of the core working area of ​​the neutron tube, significantly extending the equipment's service life. The improved temperature field distribution is more uniform, significantly reducing the risk of thermal stress concentration and structural deformation, thereby improving the reliability of the neutron tube under long-term continuous operation.

[0115] In summary, this technical solution effectively solves the key challenges of beam extraction efficiency and target heat dissipation in neutron tube design by establishing a scientific synergistic optimization method for ion beam extraction structure and target heat dissipation structure, and by adopting a technical route that combines precise modeling, multi-scheme comparison and experimental verification, thereby significantly improving the overall performance of the equipment.

[0116] In another embodiment, this application provides a computer device, which may be a server, and its internal structure diagram may be as follows. Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it can implement the methods described in any of the above embodiments.

[0117] In one embodiment, this application also provides a computer device, which can be a client, and its internal structure diagram can be as follows: Figure 5 As shown, the computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it can implement the methods described in any of the above embodiments.

[0118] Any of the computer devices described in the embodiments of this application exist in various forms, including but not limited to:

[0119] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include smartphones, multimedia phones, feature phones, and low-end phones.

[0120] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access features. These terminals include PDAs, MIDs, and UMPCs, etc.

[0121] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes: audio and video players, handheld game consoles, e-books, as well as smart toys, wearable devices, and portable car navigation devices.

[0122] (4) Server: A device that provides computing services. The components of a server include a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0123] (5) Other electronic devices with data interaction functions.

[0124] Additionally, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which are used to perform the following steps:

[0125] Determine the first distribution range of the deuterium ion extraction configuration information;

[0126] Based on the first distribution range and the preset ion source extraction electrode structure model, the optimal extraction performance information of deuterium ions is simulated and calculated.

[0127] Set the extraction configuration information corresponding to the optimal extraction performance information as the target configuration information of the deuterium ion extraction structure;

[0128] When the target configuration information is applied to the deuterium ion extraction structure, a second distribution range of the target configuration information of the target structure is determined;

[0129] Based on the second distribution range and the preset neutron tube target model, the optimal heat dissipation correlation information of the target when the target configuration information is applied to the deuterium ion extraction structure is simulated and calculated.

[0130] Set the target configuration information corresponding to the optimal heat dissipation association information as the target configuration information of the target.

[0131] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0132] The technical solution of this application has been described in detail above with reference to the accompanying drawings. This solution solves the technical problem of parameter fragmentation in traditional designs. The optimized extraction structure significantly improves beam transmission efficiency, markedly enhances target surface temperature uniformity, and greatly improves neutron yield stability. Simultaneously, the synergistically optimized heat dissipation design effectively reduces the target material's operating temperature and thermal stress, significantly extending the service life of the neutron tube and its components. Furthermore, the combination of intelligent algorithms and numerical simulation significantly shortens the design cycle and reduces prototyping costs. This holistic optimization method not only overcomes the performance bottleneck of neutron tubes but also provides a standardized design paradigm for the engineering development of compact, long-life neutron tubes, possessing significant value in various application fields.

[0133] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0134] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0136] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0137] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0138] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for optimizing the performance of a neutron tube, characterized in that, include: Determine the first distribution range of the deuterium ion extraction configuration information; Based on the first distribution range and the preset ion source extraction electrode structure model, the optimal extraction performance information of deuterium ions is simulated and calculated. Set the extraction configuration information corresponding to the optimal extraction performance information as the target configuration information of the deuterium ion extraction structure; When the target configuration information is applied to the deuterium ion extraction structure, a second distribution range of the target configuration information of the target structure is determined; Based on the second distribution range and the preset neutron tube target model, the optimal heat dissipation correlation information of the target when the target configuration information is applied to the deuterium ion extraction structure is simulated and calculated. Set the target configuration information corresponding to the optimal heat dissipation association information as the target configuration information of the target.

2. The method according to claim 1, characterized in that, The extraction configuration information includes the shape, size, and electrode voltage distribution of the deuterium ion extraction structure, and the target configuration information includes the shape, size, material parameters, and boundary conditions of the target structure.

3. The method according to claim 2, characterized in that, The simulation calculation of optimal deuterium ion extraction performance information based on the first distribution range and the preset ion source extraction electrode structure model includes: Multiple sets of candidate extraction configuration information are dynamically combined within the first distribution range corresponding to the shape, size, and electrode voltage distribution of the deuterium ion extraction structure; For each set of candidate extraction configuration information, based on the candidate extraction configuration information and the preset ion source extraction electrode structure model, the extraction performance information of the deuterium ion under the candidate extraction configuration information is simulated and calculated. Based on the lead-out performance information under the candidate lead-out configuration information, determine the lead-out confidence level corresponding to the candidate lead-out configuration information; The candidate extraction configuration information with the highest extraction confidence is determined as the optimal extraction performance information of the ion source extraction electrode structure model.

4. The method according to claim 3, characterized in that, The extracted performance information includes deuterium ion current density, target surface energy density distribution, and deuterium ion divergence angle. The step of determining the lead-out confidence level corresponding to the candidate lead-out configuration information based on the lead-out performance information under the candidate lead-out configuration information includes: The deuterium ion current density, target surface energy density distribution, and deuterium ion divergence angle corresponding to the candidate extraction configuration information are encoded and normalized respectively to obtain the first feature value, the second feature value, and the third feature value. Based on the first eigenvalue, the second eigenvalue, and the third eigenvalue, as well as the respective performance weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle, a deuterium ion extraction performance matrix is ​​constructed. Based on the deuterium ion extraction performance matrix, the extraction confidence level corresponding to the candidate extraction configuration information is determined.

5. The method according to claim 4, characterized in that, The deuterium extraction performance matrix is ​​constructed based on the first, second, and third eigenvalues, and the respective performance weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle, including: The element in the m-th row and n-th column of the deuterium ion extraction performance matrix is ​​set to the weighted average of the first and second specified parameters, where, The first specified parameter is the difference between the m-th eigenvalue and the mean of the eigenvalues ​​among the first, second, and third eigenvalues, and the second specified parameter is the difference between the n-th weight and the mean of the weights of the respective weights of the deuterium ion current density, the target surface energy density distribution, and the deuterium ion divergence angle.

6. The method according to claim 2, characterized in that, The simulation calculation of optimal deuterium ion extraction performance information based on the first distribution range and the preset ion source extraction electrode structure model includes: Based on a preset genetic algorithm, the multi-objective optimization combination result of the ion source extraction electrode structure model is determined within the first distribution range, and is used as the optimal extraction performance information of the deuterium ion.

7. The method according to any one of claims 2 to 6, characterized in that, Based on the second distribution range and a preset neutron tube target model, the optimal heat dissipation correlation information of the target when the target configuration information is applied to the deuterium ion extraction structure is simulated and calculated, including: Multiple sets of candidate target configuration information are dynamically combined within the second distribution range corresponding to the shape, size, material parameters and boundary conditions of the target structure; For each set of target configuration information, based on the target configuration information and the preset neutron tube target model, the heat dissipation correlation information after deuterium ion target bombardment is simulated and calculated. Based on the heat dissipation correlation information under the candidate target configuration information, the target heat dissipation confidence level corresponding to the candidate target configuration information is determined; The target configuration information of the target heat dissipation confidence is determined as the optimal heat dissipation correlation information of the neutron tube target model.

8. The method according to claim 7, characterized in that, The heat dissipation-related information includes target temperature distribution information, target manufacturing cost information, and target reliability. The step of determining the target heat dissipation confidence level corresponding to the target configuration information based on the heat dissipation correlation information under the target configuration information includes: The target temperature distribution information, target manufacturing cost information, and target usage reliability corresponding to the candidate target configuration information are encoded and normalized respectively to obtain the fourth feature value, the fifth feature value, and the sixth feature value. The temperature distribution difference parameter between the fourth characteristic value and the preset standard distribution characteristic value is determined; the cost difference parameter between the fifth characteristic value and the preset standard cost characteristic value is determined; and the reliability difference parameter between the sixth characteristic value and the preset standard reliability characteristic value is determined. Based on the temperature distribution difference parameter, the cost difference parameter, and the reliability difference parameter, as well as the weights corresponding to the target temperature distribution information, target manufacturing cost information, and target usage reliability, a target heat dissipation performance matrix is ​​constructed. Based on the target heat dissipation performance matrix, the target heat dissipation confidence level corresponding to the candidate target configuration information is determined.

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