Nuclear physics experiment simulation method and system

Abstract

The invention relates to the technical field of nuclear physics experiments, in particular to a nuclear physics experiment simulation method and system, and the method comprises the following steps: based on the physical characteristic information of a nuclear material, building a nuclear material performance prediction model through collecting the performance information of the nuclear material, and evaluating the performance of the nuclear material under various temperature and pressure conditions; and generating a material performance analysis result. According to the method, through physical characteristic information of the nuclear material, material performance is accurately evaluated, material behaviors are recognized in advance, the nuclear reaction process is calculated and simulated, experimenters are helped to understand nuclear division and nuclear fusion events, distribution of the fission products is accurately predicted by means of real-time behavior analysis of the fission products, and the performance of the nuclear material is accurately evaluated. The risk caused by unforeseen fission product behaviors is reduced, key parameters in the nuclear energy release process are monitored in real time, any condition causing unstable reaction is found and recorded in time, the safety and predictability of nuclear experiments are improved, and a comprehensive experimental analysis tool is provided for researchers.

Description

Technical Field

[0001] The present invention relates to the technical field of nuclear physics experiments, and particularly to a nuclear physics experiment simulation method and system. Background Art

[0002] The technical field of nuclear physics experiments involves the study of the structure, reactions, and interactions of atomic nuclei. By using a variety of high-precision instruments and methods, nuclear physics phenomena are detected and analyzed, including nuclear reactions, nuclear decays, nuclear fusion, fission processes, and radioactive phenomena. Accelerators, reactors, and various detectors are used to provide key data on the properties and behaviors of atomic nuclei. Nuclear physics experiments are applied in multiple aspects such as energy development, medical applications, and national security, and are crucial for basic scientific research.

[0003] Among them, the nuclear physics experiment simulation method and system refer to the technical solutions used to simulate nuclear physics experiments, aiming to reproduce the experimental environment and results through computer simulation, help scientists predict experimental results without conducting real physical experiments, reduce experimental costs, evaluate potential risks and safety before experiments, reduce dangerous and unstable factors, support researchers in validating theoretical models, and are applied in multiple aspects such as the design of experimental equipment, testing theoretical models, education, and training, helping scientists deeply understand complex nuclear phenomena, optimize experimental designs, and improve experimental safety.

[0004] Traditional nuclear physics experiment simulation methods have low efficiency in integrating and analyzing experimental data. Manual intervention is required when dealing with complex experimental data, increasing the time cost and human errors of the experiment. The behavior and distribution of fission products cannot be real-time feedback during the simulation of nuclear reaction processes, limiting the ability to respond promptly to potential risks under experimental conditions. The lack of real-time monitoring and prediction capabilities leads to the failure to detect unstable factors in a timely manner during actual nuclear reaction processes, increasing safety risks. There are also deficiencies in data management, with low efficiency in data classification and retrieval, affecting the usability of data and restricting the in-depth analysis and application of experimental data by researchers. Summary of the Invention

[0005] In order to solve the technical problem of the low efficiency in integrating and analyzing simulation experimental data existing in the prior art, embodiments of the present invention provide a nuclear physics experiment simulation method and system. The technical solutions are as follows:

[0006] On the one hand, a nuclear physics experiment simulation method is provided, and the method includes:

[0007] S1: Based on the physical property information of nuclear materials, by collecting the performance information of nuclear materials, constructing a nuclear material performance prediction model, evaluating the performance of nuclear materials under various temperature and pressure conditions, and generating a material performance analysis result;

[0008] S2: Based on the results of the material property analysis, by setting the initiation conditions for various nuclear reaction events, calculate the energy distribution, neutron flux, and spatial layout of the radiation field generated by nuclear fission, simulate nuclear fission and fusion events, and obtain the simulation results of the reaction process;

[0009] S3: Based on the simulation results of the reaction process, record and analyze the generation rate and path of fission products in real time, analyze and predict the behavior and distribution pattern of fission products under various experimental conditions, and generate the prediction results of product distribution;

[0010] S4: Utilize the prediction results of product distribution to simulate the energy release process during the nuclear reaction process, calculate the change rate of energy and material conversion during the release process, analyze the influence of changes in temperature, pressure, and radiation level on the energy conversion efficiency, and detect the conditions leading to reaction instability in real time to obtain the information on the nuclear energy release process;

[0011] S5: Based on the information on the nuclear energy release process, classify the experimental data according to the experimental conditions, experimental results, and experimental time, and match index labels to generate the experimental data management results.

[0012] As a further solution of the present invention, the results of the material property analysis include multi-condition material strength information, material ductility information, and material heat resistance data. The simulation results of the reaction process include nuclear event initiation threshold parameters, reaction duration, energy and neutron release rates. The prediction results of product distribution include the spatial distribution pattern of fission products, product migration speed, and product aggregation regions. The information on the nuclear energy release process includes energy conversion efficiency, records of safety threshold exceeding events, and information on the process of material state change. The experimental data management results include experimental data classification results, experimental data index labels, and retrieval efficiency evaluation information.

[0013] As a further solution of the present invention, based on the nuclear material physical property information, by collecting the property information of nuclear materials, constructing a nuclear material property prediction model, and evaluating the performance of nuclear materials under various temperature and pressure conditions, the steps for generating the results of material property analysis are specifically as follows:

[0014] S101: Based on the nuclear material physical property information, collect the nuclear material property data under various temperature and pressure conditions, record the thermal conductivity, compressive strength, and radiation damage data of the material, and generate a material property data set;

[0015] S102: Based on the material property data set, perform data cleaning on the performance data, including removing invalid and abnormal data, and performing formatting and standardization processing on the data to generate a performance data processing record;

[0016] S103: Based on the processing record of the performance data, predict the performance of various nuclear materials under different temperature and pressure conditions, and generate a material performance analysis result.

[0017] As a further solution of the present invention, based on the material performance analysis result, by setting the start conditions of various nuclear reaction events, calculate the energy distribution, neutron flux and spatial layout of the radiation field generated by nuclear fission, and simulate nuclear fission and nuclear fusion events. The steps to obtain the reaction process simulation result are specifically as follows:

[0018] S201: Based on the material performance analysis result, set the initial conditions for nuclear reaction simulation, including the concentration of reactants, ambient temperature and pressure, and generate a set of simulation initial conditions;

[0019] S202: Based on the set of simulation initial conditions, calculate the energy distribution state generated during the nuclear reaction process, including nuclear fission and nuclear fusion, record the energy release and the change of neutron flux, and generate an energy distribution prediction result;

[0020] S203: Based on the energy distribution prediction result, simulate nuclear fission and nuclear fusion events, analyze the trigger conditions and duration of nuclear reaction events under various conditions, and generate a reaction process simulation result.

[0021] As a further solution of the present invention, based on the reaction process simulation result, record and analyze the generation rate and path of fission products in real time, analyze and predict the behavior and distribution pattern of fission products under various experimental conditions, and the steps to generate a product distribution prediction result are specifically as follows:

[0022] S301: Based on the reaction process simulation result, evaluate the generation path of nuclear fission products by analyzing the movement trajectory of nuclear fission products, and generate a fission product generation path;

[0023] S302: Based on the fission product generation path, consider the fission chain reaction rate and its influence on the reaction conditions, calculate the generation rate of various nuclear fission products, and generate a generation rate simulation result;

[0024] S303: Based on the generation rate simulation result, evaluate the influence of temperature and pressure on the behavior of products, analyze and predict the distribution pattern of fission products under various reaction conditions, and generate a product distribution prediction result.

[0025] As a further solution of the present invention, the specific formula for calculating the generation rate of various nuclear fission products is:

[0026]

[0027] Wherein, R is the generation rate of fission products, R 0is the initial fission reaction rate, representing the fission product generation rate under standard conditions, k is the rate constant of the fission reaction, t is the reaction time, e is the base of the natural logarithm, P is the pressure in the current reaction environment, and P 0 is the standard pressure.

[0028] As a further aspect of the present invention, using the predicted product distribution result, simulating the energy release process during the nuclear reaction, calculating the change rate of energy and material conversion during the release process, analyzing the influence of temperature, pressure, and radiation level changes on the energy conversion efficiency, and detecting in real time the conditions that cause the reaction to be unstable, the steps for obtaining the nuclear energy release process information are specifically as follows:

[0029] S401: Based on the predicted product distribution result, by tracking the mass and energy changes of reactants and products, calculating the change rate of the energy and material states in the nuclear reaction, and generating the analysis result of the material change rate;

[0030] S402: Based on the analysis result of the material change rate, evaluating the influence of various temperatures, pressures, and radiation levels on the energy conversion efficiency, calculating the influence degree of various environmental parameter changes on the reaction, and generating the calculation result of the influencing factors;

[0031] S403: Based on the calculation result of the influencing factors, tracking the reaction conditions in real time, detecting and recording the conditions that cause the reaction to be unstable, including exceeding the standard temperature and pressure, and generating the nuclear energy release process information.

[0032] As a further aspect of the present invention, the specific formula for calculating the influence degree of various environmental parameter changes on the reaction is:

[0033]

[0034] where r is the correlation coefficient, representing the strength of the linear relationship between the environmental parameter and the reaction sensitivity, x i is the environmental parameter value in a single measurement, y i is the corresponding reaction sensitivity measurement value, is the average value of the environmental parameter, is the average value of the reaction sensitivity, and i represents the index of the data point.

[0035] As a further aspect of the present invention, based on the nuclear energy release process information, classifying the experimental data according to the experimental conditions, experimental results, and experimental time, and matching index labels, the steps for generating the experimental data management result are specifically as follows:

[0036] S501: Based on the nuclear energy release process information, collecting a number of experimental data during the nuclear test simulation, including experimental conditions, experimental results, and experimental time, and generating an experimental record data set;

[0037] S502: Based on the experimental record dataset, classify the data according to experimental conditions, experimental results, and experimental time to generate a data classification record;

[0038] S503: Based on the data classification record, match index tags for multiple experimental events, optimize the retrieval efficiency of experimental data, and generate an experimental data management result.

[0039] On the other hand, a nuclear physics experiment simulation system is provided. This system is applied to the nuclear physics experiment simulation method and includes:

[0040] The performance data acquisition module collects response data of various nuclear materials under different temperatures and pressures based on nuclear material physical property information to obtain nuclear material response data;

[0041] The material performance evaluation module analyzes the response data of the nuclear materials based on the nuclear material response data, evaluates the performance of the nuclear materials under various temperature and pressure conditions, and obtains a nuclear material performance analysis result;

[0042] The reaction process simulation module uses the nuclear material performance analysis result to set the start conditions of nuclear fission and nuclear fusion, including reactant concentration and environmental conditions, and simulates nuclear fission and nuclear fusion events to obtain a reaction process simulation result;

[0043] The product behavior analysis module analyzes the generation speed and path of fission products based on the reaction process simulation result, analyzes the behavior and distribution pattern of products under various conditions, and generates a product distribution prediction result;

[0044] The reaction energy monitoring module uses the product distribution prediction result to monitor the changes of multiple key parameters during the energy release process, including temperature and pressure, and real-time detects the conditions causing reaction instability to obtain nuclear energy release process information;

[0045] The data classification management module classifies the experimental data according to experimental conditions, results, and experimental time based on the nuclear energy release process information, matches index tags, optimizes the data retrieval efficiency, and generates an experimental data management result.

[0046] The beneficial effects brought by the technical solution provided by the embodiments of the present invention at least include:

[0047] By using the physical property information of nuclear materials, the material performance can be accurately evaluated, the material behavior can be identified in advance, the nuclear reaction process can be calculated and simulated, which helps the experimenters to deeply understand nuclear fission and fusion events. By using the real-time behavior analysis of fission products, the distribution of fission products can be accurately predicted, reducing the risks caused by unforeseen fission product behaviors. By real-time monitoring of the key parameters during the nuclear energy release process, any conditions leading to reaction instability can be timely detected and recorded, improving the safety and predictability of nuclear experiments, and providing a comprehensive experimental analysis tool for scientific researchers. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0049] Figure 1 It is a schematic diagram of the working process of the present invention;

[0050] Figure 2 It is a detailed flowchart of S1 of the present invention;

[0051] Figure 3 It is a detailed flowchart of S2 of the present invention;

[0052] Figure 4 It is a detailed flowchart of S3 of the present invention;

[0053] Figure 5 It is a detailed flowchart of S4 of the present invention;

[0054] Figure 6 It is a detailed flowchart of S5 of the present invention;

[0055] Figure 7 It is a system flowchart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] The following will describe the technical solutions in the present invention with reference to the drawings.

[0057] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "example" in the present invention should not be construed as more preferred or more advantageous than other embodiments or design solutions. Exactly speaking, the use of the word "example" aims to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0058] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same. "Of", "corresponding", and "corresponding to" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same.

[0059] In the embodiments of the present invention, sometimes subscripts such as W 1 may be written in a non-subscript form such as W1. When the difference is not emphasized, their intended meanings are the same.

[0060] To make the technical problems to be solved, technical solutions, and advantages of the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0061] The embodiments of the present invention provide a nuclear physics experiment simulation method, such as Figure 1 shown in the flowchart of the nuclear physics experiment simulation method. The processing flow of this method may include the following steps:

[0062] S1: Based on the physical property information of nuclear materials, by collecting the performance information of nuclear materials, constructing a nuclear material performance prediction model, evaluating the performance of nuclear materials under various temperature and pressure conditions, and generating a material performance analysis result;

[0063] S2: Based on the material performance analysis result, by setting the start conditions of various nuclear reaction events, calculating the energy distribution, neutron flux, and spatial layout of the radiation field generated by nuclear fission, simulating nuclear fission and nuclear fusion events, and obtaining a reaction process simulation result;

[0064] S3: Based on the reaction process simulation result, record and analyze the generation speed and path of fission products in real time, analyze and predict the behavior and distribution pattern of fission products under various experimental conditions, and generate a product distribution prediction result;

[0065] S4: Using the product distribution prediction result, simulate the energy release process in the nuclear reaction process, calculate the change rate of energy and material conversion during the release process, analyze the influence of changes in temperature, pressure, and radiation level on the energy conversion efficiency, and detect the conditions leading to reaction instability in real time to obtain the nuclear energy release process information;

[0066] S5: Based on the nuclear energy release process information, classify the experimental data according to the experimental conditions, experimental results, and experimental time, and match index labels to generate an experimental data management result.

[0067] The results of material property analysis include multi-condition material strength information, material ductility information, and material heat resistance data. The results of reaction process simulation include nuclear event initiation threshold parameters, reaction duration, energy, and neutron release rate. The results of product distribution prediction include the spatial distribution pattern of fission products, product migration speed, and product aggregation area. The information on the nuclear energy release process includes energy conversion efficiency, records of safety threshold exceedance events, and information on the process of substance state change. The results of experimental data management include experimental data classification results, experimental data index labels, and retrieval efficiency evaluation information.

[0068] Please refer to Figure 2 , based on the physical property information of nuclear materials, by collecting the performance information of nuclear materials, the steps to construct a nuclear material performance prediction model, evaluate the performance of nuclear materials under various temperature and pressure conditions, and generate the results of material property analysis are specifically as follows:

[0069] S101: Based on the physical property information of nuclear materials, collect the performance data of nuclear materials under various temperature and pressure conditions, record the thermal conductivity, compressive strength, and radiation damage data of the materials, and generate a material property dataset;

[0070] In sub-step S101, the collection of nuclear material performance data is carried out, including setting different temperature and pressure environments in the laboratory, measuring the thermal conductivity of the material using a thermistor, determining the compressive strength of the material using a pressure sensor, and at the same time using a radiation detector to record the radiation damage data. Through the readings of the target instrument, the data is automatically entered into the database to create a material property dataset containing timestamps, environmental conditions, and test results. The target dataset provides the necessary input source for the model in subsequent steps. Each piece of data in the dataset is directly associated with the temperature and pressure of its test environment, ensuring the integrity and traceability of the data.

[0071] S102: Based on the material property dataset, perform data cleaning on the performance data, including removing invalid and abnormal data, and formatting and standardizing the data to generate a performance data processing record;

[0072] In sub-step S102, execute the data cleaning process, including identifying and removing invalid data in the dataset, such as abnormal readings outside the measurement range, using statistical analysis methods such as standard deviation and quartile method to identify outliers, then formatting the data, converting all data into a unified format, for example, converting temperature from Fahrenheit to Celsius, pressure from Pascal to standard atmospheric pressure, performing data standardization, using the Z-score method to adjust the data values to meet the input standards required by the model. The processing process ensures the consistency and usability of the data. The generated performance data processing record details the execution details and processing results of each step, providing an accurate and reliable data source for the next step of data analysis.

[0073] S103: Predict the performance of multiple nuclear materials under different temperature and pressure conditions based on the performance data processing records, and generate the material performance analysis results;

[0074] In the above content, based on the performance data processing records, a linear regression model is used to predict the performance of nuclear materials. According to the formula y = β 0 +β 1 T + β 2 P, calculate the performance score of nuclear materials under specific conditions;

[0075] In the formula, -y represents the predicted performance score, -T represents the temperature, -P represents the pressure, -β 0 represents the model intercept, -β 1 represents the regression coefficient of temperature, -β 2 represents the regression coefficient of pressure;

[0076] Detailed explanation of the formula and the derivation process of formula calculation:

[0077] Assume that the model intercept β 0 = 0.5, the temperature coefficient β 1 = 0.05, the pressure coefficient β 2 = 0.07, T = 2500, P = 15:

[0078] y = 0.5 + 0.05 × 2500 + 0.07 × 15;

[0079] y = 0.5 + 125 + 1.05;

[0080] y = 126.55;

[0081] The results show that the obtained performance score of nuclear materials is 126.55, reflecting the predicted performance of nuclear materials under high temperature and pressure conditions.

[0082] Please refer to Figure 3 , based on the material performance analysis results, by setting the starting conditions of multiple nuclear reaction events, calculate the energy distribution, neutron flux, and spatial layout of the radiation field generated by nuclear fission, and simulate nuclear fission and fusion events. The specific steps to obtain the reaction process simulation results are as follows:

[0083] S201: Based on the material performance analysis results, set the initial conditions for nuclear reaction simulation, including the reactant concentration, environmental temperature, and pressure, and generate the set of simulation initial conditions;

[0084] In sub-step S201, based on the obtained material property analysis results, the initial conditions for nuclear reaction simulation are set, including the detailed setting of reactant concentration, environmental temperature, and pressure. The determination of the target conditions is based on previous material test results to ensure that the simulation environment matches the actual working conditions that may be encountered. The setting of environmental parameters uses the control system software to precisely adjust the operating conditions of experimental equipment such as reactors, including the feedback mechanism for automatically adjusting the temperature controller and pressure sensor, ensuring that the environmental settings for each simulation can reproduce the same conditions. The generated set of simulation initial conditions details the specific parameters of each simulation, and this record is crucial for the subsequent simulation accuracy and repeatability, ensuring that the simulation experiments can be precisely carried out under the predetermined conditions.

[0085] S202: Based on the set of simulation initial conditions, calculate the energy distribution state generated during the nuclear reaction process, including nuclear fission and nuclear fusion, record the energy release and neutron flux changes, and generate the energy distribution prediction results.

[0086] In sub-step S202, a physical simulation software is used to calculate the energy distribution during the nuclear reaction process. According to the basic equations of nuclear physics, the energy release state during nuclear fission and nuclear fusion processes is calculated, including the energy release rate and the change in neutron flux. The target calculation uses a high-performance computer for large-scale numerical simulation to ensure the accuracy of the results. During the calculation process, the software automatically records all the change data of energy and particle flux, generating the energy distribution prediction results. The target results not only show the energy output under different reactant concentrations and operating conditions but also simulate the possible energy peaks and potential instability factors under specific conditions, providing a basis for the analysis of reaction safety.

[0087] S203: Based on the energy distribution prediction results, simulate nuclear fission and nuclear fusion events, analyze the triggering conditions and duration of nuclear reaction events under various conditions, and generate the reaction process simulation results.

[0088] In sub-step S203, a nuclear event simulation software is used in the process. According to the input energy distribution data, physical events of nuclear fission and nuclear fusion are simulated. By setting different environmental and reactant parameters, the triggering probability and duration of nuclear events under different conditions are shown. The simulation results include a detailed analysis of event triggering conditions and the time series of the reaction process. The target data is crucial for understanding the dynamic changes and potential risks of nuclear reactions. The reaction process simulation results provide a visual means to observe and evaluate the behavior and impact of nuclear events, providing experimental data and theoretical support for the design of nuclear reaction control and safety warning systems.

[0089] Please refer to Figure 4, based on the simulation results of the reaction process, the generation rate and path of fission products are recorded and analyzed in real time, and the behaviors and distribution patterns of fission products under various experimental conditions are analyzed and predicted. The specific steps for generating the product distribution prediction results are as follows:

[0090] S301: Based on the simulation results of the reaction process, by analyzing the movement trajectories of nuclear fission products, evaluate the generation paths of nuclear fission products, and generate the fission product generation paths;

[0091] In sub-step S301, the particle tracking algorithm is used to analyze the movement trajectories of nuclear fission products. During the process, the generation and movement paths of each fission product are accurately recorded. The algorithm meticulously simulates the entire process from the nuclear fission point to the stopping position, tracks and evaluates the specific paths of each product within the reactor, including the speed and trajectory changes as it passes through different parts of the reactor. The analysis results of the fission product generation paths help identify possible accumulation areas or potential hazard points. This target information is crucial for optimizing the design of nuclear reactors and enhancing their safety. By having a deeper understanding of the fission product paths, the use and handling of nuclear materials can be better controlled, and the efficiency and safety of nuclear waste management can be improved.

[0092] S302: Based on the fission product generation paths, considering the fission chain reaction rate and its influence on the reaction conditions, calculate the generation rates of various nuclear fission products, and generate the rate simulation results;

[0093] The specific formula for calculating the generation rates of various nuclear fission products is:

[0094]

[0095] Among them, R is the generation rate of fission products, R 0 is the initial fission reaction rate, representing the generation rate of fission products under standard conditions, k is the rate constant of the fission reaction, t is the reaction time, e is the base of the natural logarithm, P is the pressure in the current reaction environment, and P 0 is the standard pressure.

[0096] Formula:

[0097]

[0098] Detailed explanation of the formula and the formula calculation derivation process:

[0099] The formula is used to calculate the generation rate of nuclear fission products, providing a data basis for nuclear physics experimental simulations; Parameter meanings and set values:

[0100] R 0 is the initial fission reaction rate, assumed to be 10 units / second;

[0101] k is the fission reaction rate constant, assumed to be 0.03;

[0102] t is the time, assumed to be 5 seconds, recorded by the monitoring device;

[0103] P is the pressure under the current reaction environment, assumed to be 150;

[0104] P 0 is the standard pressure, assumed to be 100 atm;

[0105] Substitute the parameters into the formula for calculation:

[0106]

[0107] R = 10·e -0.03 ·(1 + 1.5);

[0108] R = 10·0.86·2.5 = 21.517;

[0109] The result 21.517 indicates that under the current experimental conditions, the generation rate of nuclear fission products is 21.517 units per second. The rate reflects the activity degree of the fission reaction under specific time and pressure conditions. The value provides a data basis for simulating the simulation experiment.

[0110] S303: Based on the simulation results of the generation rate, evaluate the effects of temperature and pressure on the behavior of the products, analyze and predict the distribution patterns of fission products under various reaction conditions, and generate the prediction results of the product distribution;

[0111] In sub-step S303, use the thermodynamic analysis method to evaluate the effects of changes in environmental temperature and pressure on the behavior of fission products, understand how temperature and pressure affect the distribution and stability of fission products, predict various complex situations encountered in actual operations by simulating the fission product distribution under different environmental conditions. The analysis results provide the potential distribution patterns of fission products inside the reactor, revealing the areas that cause safety problems under extreme conditions. The target information is crucial for the safe operation of nuclear facilities and the formulation of emergency response plans. By predicting and analyzing the distribution of fission products, measures can be taken before actual problems occur to avoid or mitigate potential nuclear accidents.

[0112] Please refer to Figure 5 , using the prediction results of the product distribution, simulate the energy release process during the nuclear reaction process, calculate the change rate of energy and material conversion during the release process, analyze the effects of changes in temperature, pressure, and radiation level on the energy conversion efficiency, and detect in real time the conditions that cause reaction instability. The specific steps to obtain the information on the nuclear energy release process are as follows:

[0113] S401: Based on the product distribution prediction results, by tracking the mass and energy changes of reactants and products, calculate the change rates of energy and material states in nuclear reactions, and generate the analysis results of material change rates;

[0114] In sub-step S401, the law of conservation of mass and energy is adopted to track and analyze the mass and energy of reactants and products in nuclear reactions. The process involves calculating the incident and released energy of substances and the material states changing over time. By precisely measuring the mass and energy of substances at each time point, the change rates of material states are calculated. The process depends on continuously monitored and recorded data. The generated analysis results of material change rates provide basic data for understanding nuclear reactions. The data is crucial for adjusting the material input in the reaction process and the strategy for handling nuclear waste, ensuring the continuous monitoring and real-time adjustment capabilities of nuclear reactions, and enhancing the efficiency and effectiveness of nuclear reaction safety management.

[0115] S402: Based on the analysis results of material change rates, evaluate the effects of various temperature, pressure, and radiation levels on the energy conversion efficiency, calculate the influence degrees of changes in various environmental parameters on the reaction, and generate the calculation results of influencing factors;

[0116] The specific formula for calculating the influence degrees of changes in various environmental parameters on the reaction is:

[0117]

[0118] where r is the correlation coefficient, representing the strength of the linear relationship between environmental parameters and reaction sensitivity, x i is the value of the environmental parameter in a single measurement, y i is the corresponding measured value of reaction sensitivity, is the average value of the environmental parameter, is the average value of reaction sensitivity, and i represents the index of the data point.

[0119] Formula:

[0120]

[0121] Detailed explanation of the formula and the derivation process of formula calculation:

[0122] The formula is used to calculate the correlation coefficient between temperature, pressure, radiation levels and reaction sensitivity, and the result is used to evaluate the influence degrees of various environmental parameters on the nuclear reaction process;

[0123] Meaning and set values of parameters:

[0124] x i is the value of the environmental parameter in a single experiment. Assuming it is temperature, it is set as 2300 °C, 2400 °C, 2500 °C, 2300 °C, 2400 °C;

[0125] y i For the corresponding reaction sensitivity values, set to 0.5, 0.7, 0.7, 0.6, 0.5;

[0126] is the average value of all temperature observations, calculated as 2380 °C;

[0127] is the average value of all reaction sensitivity observations, calculated as 0.6;

[0128] Substitute the parameters into the formula for calculation:

[0129]

[0130] The result 0.598 indicates a positive correlation between temperature and reaction sensitivity, indicating that temperature changes are positively correlated with reaction sensitivity to a certain extent. The result is used to understand various factors that need to be considered when controlling experimental conditions, ensuring the accuracy and reproducibility of the experiment.

[0131] S403: Based on the calculation results of influencing factors, track the reaction conditions in real time, detect and record the conditions that cause reaction instability, including excessive temperature and pressure, and generate nuclear energy release process information;

[0132] In sub-step S403, implement a real-time monitoring strategy to track nuclear reaction conditions, and detect any conditions that cause reaction instability through the monitoring system, including continuous monitoring of temperature and pressure. By analyzing whether the established safety thresholds are exceeded, use a real-time data analysis system to quickly identify the exceeded conditions and trigger an early warning mechanism. The generated nuclear energy release process information provides real-time feedback for reaction safety, supports the implementation of emergency response measures, ensures that the operation of nuclear facilities is within the safety boundaries, and reduces the risks caused by improper operation or external condition changes.

[0133] Please refer to Figure 6 , based on the nuclear energy release process information, classify the experimental data according to experimental conditions, experimental results, and experimental time, and match index tags. The specific steps for generating the experimental data management result are as follows:

[0134] S501: Based on the nuclear energy release process information, collect multiple experimental data during the nuclear test simulation process, including experimental conditions, experimental results, and experimental time, and generate an experimental record dataset;

[0135] In sub-step S501, the system collection work of experimental data is carried out, including obtaining various data such as experimental conditions, experimental results, and experimental time from the nuclear test simulation system, using data acquisition software to automatically record the detailed information of each experiment, and transmitting the target information to the central database through the network. The database is managed by an efficient data management system to ensure the integrity and accessibility of the data. The generated experimental record dataset provides rich raw data for subsequent data analysis and scientific research. Each record clearly marks the specific conditions of the experiment, the obtained results, and the specific time points when the experiment is carried out, providing a basic guarantee for the reproduction and subsequent analysis of the experimental process.

[0136] S502: Based on the experimental record dataset, classify the data according to the experimental conditions, experimental results, and experimental time to generate data classification records;

[0137] In sub-step S502, the classification process of the data is carried out. The process uses the clustering analysis technology in machine learning to automatically distinguish different types of experimental data. The clustering algorithm groups the data according to the similarity of experimental conditions, results, and time to optimize the subsequent data access and analysis efficiency. Each category is labeled according to the nature and purpose of the experiment. The results of the classification process are stored in the data management system and are called data classification records. The target records provide a structured way for the quick retrieval and systematic analysis of experimental data. The classified data can be retrieved and cited faster, supporting researchers to quickly find the required data when conducting similar experiments or analyses.

[0138] S503: Based on the data classification records, match index tags for multiple experimental events to optimize the retrieval efficiency of experimental data and generate the experimental data management results;

[0139] In sub-step S503, the work of matching index tags is carried out. An automated tagging system is used to generate a unique index tag for each experimental data. The target tags are based on the main features of the experiment, such as reaction type, materials used, experimental purpose, etc. Natural language processing technology is used in the tag generation process to parse the text content of the experimental records, automatically identify key information, and generate corresponding tags. The generated experimental data management results significantly improve the retrieval efficiency of experimental data, enabling users to quickly find the required experimental data through simple keyword searches. Each tag is closely associated with specific experimental data and classification results, providing an effective tool for the collation, management, and utilization of experimental data.

[0140] Please refer to Figure 7 , a nuclear physics experiment simulation system. The nuclear physics experiment simulation system is used to execute the above nuclear physics experiment simulation method. The system includes:

[0141] Based on the physical property information of nuclear materials, the performance data acquisition module collects the response data of various nuclear materials under different temperatures and pressures to obtain the nuclear material response data;

[0142] Based on the nuclear material response data, the material performance evaluation module analyzes the response data of nuclear materials, evaluates the performance of nuclear materials under various temperature and pressure conditions, and obtains the nuclear material performance analysis results;

[0143] Using the nuclear material performance analysis results, the reaction process simulation module sets the initiation conditions for nuclear fission and fusion, including reactant concentrations and environmental conditions, and simulates nuclear fission and fusion events to obtain the reaction process simulation results;

[0144] Based on the reaction process simulation results, the product behavior analysis module analyzes the generation rate and path of fission products, analyzes the behavior and distribution patterns of products under various conditions, and generates the product distribution prediction results;

[0145] Using the product distribution prediction results, the reaction energy monitoring module monitors the changes in multiple key parameters during the energy release process, including temperature and pressure, and real-time detects the conditions that cause reaction instability to obtain the nuclear energy release process information;

[0146] Based on the nuclear energy release process information, the data classification and management module classifies the experimental data according to experimental conditions, results, and experimental time, matches index tags, optimizes the data retrieval efficiency, and generates the experimental data management results.

[0147] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that contains one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0148] It should be understood that the term "and / or" in this text is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. Additionally, the character " / " in this text generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship. The specific meaning can be understood by referring to the context before and after.

[0149] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0150] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0151] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0152] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0153] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0154] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0155] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0156] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0157] As described above, the above are only the specific implementation manners of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A nuclear physics experiment simulation method, characterized in that: The method comprises: Based on the physical property information of nuclear materials, by collecting the performance information of nuclear materials, a nuclear material performance prediction model is constructed to evaluate the performance of nuclear materials under various temperature and pressure conditions and generate material performance analysis results; Based on the material performance analysis results, by setting the start-up conditions of various nuclear reaction events, calculating the energy distribution, neutron flux and spatial layout of the radiation field generated by nuclear fission, simulating nuclear fission and nuclear fusion events, and obtaining reaction process simulation results; Based on the simulation results of the reaction process, the generation speed and path of fission products are recorded and analyzed in real time, the behavior and distribution pattern of fission products under various experimental conditions are analyzed and predicted, and product distribution prediction results are generated; Using the product distribution prediction results, simulate the energy release process in the nuclear reaction process, calculate the rate of change of energy and material conversion in the release process, analyze the impact of temperature, pressure, and radiation level changes on energy conversion efficiency, detect the conditions that lead to reaction instability in real time, and obtain nuclear energy release process information; Based on the nuclear energy release process information, the experimental data is classified according to the experimental conditions, experimental results, and experimental time, and index tags are matched to generate experimental data management results.

2. The nuclear physics experiment simulation method according to claim 1, characterized in that: The material performance analysis results include multi-condition material strength information, material ductility information, and material heat resistance data; the reaction process simulation results include nuclear event initiation threshold parameters, reaction duration, energy and neutron release rate; the product distribution prediction results include the spatial distribution pattern of fission products, product migration speed, and product aggregation area; the nuclear energy release process information includes energy conversion efficiency, safety threshold exceeding event records, and material state change process information; the experimental data management results include experimental data classification results, experimental data index tags, and retrieval efficiency evaluation information.

3. A nuclear physics experiment simulation system, characterized in that: According to the nuclear physics experiment simulation method according to any one of claims 1-2, the system comprises: The performance data acquisition module collects the response data of various nuclear materials under different temperatures and pressures based on the physical property information of nuclear materials to obtain the nuclear material response data; The material performance evaluation module analyzes the response data of the nuclear material based on the nuclear material response data, evaluates the performance of the nuclear material under various temperature and pressure conditions, and obtains the nuclear material performance analysis results; The reaction process simulation module uses the nuclear material performance analysis results to set the start-up conditions of nuclear fission and nuclear fusion, including reactant concentrations and environmental conditions, simulate nuclear fission and nuclear fusion events, and obtain reaction process simulation results; The product behavior analysis module analyzes the generation speed and path of fission products based on the simulation results of the reaction process, analyzes the behavior and distribution pattern of the products under various conditions, and generates product distribution prediction results; The reaction energy monitoring module uses the product distribution prediction results to monitor the changes of multiple key parameters in the energy release process, including temperature and pressure, to detect the conditions that lead to reaction instability in real time, and obtain nuclear energy release process information; The data classification management module classifies the experimental data based on the nuclear energy release process information according to the experimental conditions, results and experimental time, matches the index tags, optimizes the data retrieval efficiency, and generates the experimental data management results.

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