Industrial ray radiation dose visual simulation method and system based on FLUKA

Abstract

The invention provides an industrial ray radiation dose visual simulation method and system based on FLUKA. The method comprises the following steps: creating and optimizing an X-ray machine model, setting radiation parameters, establishing an optimized radiation propagation model, carrying out simulation calculation, establishing the radiation intensity of a freely selected detection point or focus point according to a calculation result, and generating two-dimensional and three-dimensional dose and energy distribution diagrams. And establishing a dynamic radiation intensity calculation model and carrying out mistaken radiation accident simulation and evaluation. The system can accurately simulate and predict the dose of industrial ray radiation in real time, outputs a visual dose distribution diagram, provides a convenient and visual operation interface for workers, and is beneficial to improving the efficiency and safety of ray protection work. The method has wide application value in the aspects of industrial ray protection, mistaken irradiation accident early warning, ray device design optimization and the like.

Description

Technical Field

[0001] The present invention belongs to the field of radiation dose simulation, and more specifically relates to a FLUKA-based industrial ray radiation dose visualization simulation method and system. Background Art

[0002] Radioactive sources and radiation devices are increasingly used in industry, such as material detection, nondestructive testing, medical diagnosis, etc. However, the potential harm of radiation to humans and the environment has attracted widespread attention. Therefore, it is necessary to simulate and predict the radiation dose of industrial radiation machines to ensure their safe and compliant use.

[0003] At present, the simulation of industrial radiation mainly relies on physical calculation and experimental verification, which inevitably leads to some problems. First, physical calculation ignores the complexity of the environment and use conditions, and the results may be inaccurate. Second, experimental verification is time-consuming and laborious, and there are certain safety risks. Moreover, even after these simulations and verifications, it is impossible to visualize the radiation source exposure dose, making it impossible for users to intuitively understand the degree of danger of the radiation source and radiation device.

[0004] FLUKA (FLUktuierende KAskade) is a particle physics simulation software package based on the Monte Carlo method, which is widely used in high-energy physics, nuclear engineering, radiation protection, medical and biophysical research. FLUKA can simulate the transmission and interaction of various particles (including photons, neutrons, electrons, protons and heavy ions) generated by the interaction with materials. Therefore, using FLUKA for radiation dose simulation can not only improve the accuracy of the simulation, but also avoid the safety risks of the experiment, and can realize the visualization of the dose.

[0005] The points of interest in the X-ray machine workplace and the surrounding environment need to be calculated one by one, and each point of interest may also need to calculate the useful beam, leakage radiation or scattered radiation separately. The method is cumbersome and time-consuming;

[0006] Theoretical calculations can only calculate radiation levels, but cannot calculate and display the dose field distribution in the X-ray machine's workplace and external environment, nor can they calculate the X-ray energy generated by the X-ray machine, and cannot clearly visualize the dose distribution and energy distribution around the X-ray machine;

[0007] There may be a large error in the calculation of radiation dose outside the protective door of the X-ray room labyrinth, because after the X-rays are scattered multiple times, there is a large uncertainty in the selection of calculation parameters.

[0008] Therefore, to address this problem, the present invention proposes a FLUKA-based industrial radiation dose visualization simulation method and system, which can more accurately, comprehensively and intuitively simulate and display the radiation dose of industrial radiation machines, thereby improving the efficiency and safety of industrial radiation machines. Summary of the invention

[0009] The main technical problem to be solved by the present invention is the lack of comprehensiveness, flexibility and visualization in industrial ray radiation simulation. Specifically, the existing radiation simulation method is too simple, lacks a comprehensive representation of the actual working environment, and cannot effectively deal with mis-irradiation accidents, resulting in large errors in the simulation results; the existing radiation simulation method lacks flexibility, and users cannot set various parameters according to actual needs; the existing radiation simulation method cannot achieve visualization of radiation doses, making it impossible for users to intuitively understand the distribution of radiation levels of X-ray machines and radiation sources. Therefore, a FLUKA-based industrial ray radiation dose visualization simulation method and system are needed to solve the above problems and improve the accuracy, flexibility and ease of use of radiation dose simulation.

[0010] In order to achieve the above object, the present invention is implemented by adopting the following technical scheme: the method comprises:

[0011] Create and optimize the X-ray machine model, and build a mathematical model in the FLUKA software environment, including the machine structure, internal key components, and target materials; making the model closer to the performance of the actual X-ray machine;

[0012] Personalized setting of radiation parameters, introduction of user-defined function, allowing users to set various parameters, target materials, and electron target energy according to actual needs, improving the flexibility and accuracy of simulation;

[0013] Establish optimized radiation propagation model and perform simulation calculations;

[0014] According to the simulation calculation results, the radiation intensity technology of freely selecting the detection point or the point of interest is established;

[0015] Develop 2D and 3D dose and energy distribution maps: Generate 2D and 3D dose and energy distribution maps;

[0016] According to the simulation calculation results, a dynamic radiation intensity calculation model is established;

[0017] Simulation and assessment of accidental irradiation accidents: Rapid simulation and assessment of accidental irradiation accidents.

[0018] In one embodiment, creating and optimizing an X-ray machine model includes:

[0019] Construct the basic model: According to the actual size and structure of the X-ray machine, set the model space and initialize the X-ray machine model. In the FLUKA software, first set the size of the main structure to 10cm×10cm×40cm and determine the target material to be tungsten; at the same time, set the focus size to 2mm x 3mm to achieve the basic mathematical model construction;

[0020] Setting environmental parameters: By setting the inside of the X-ray machine to a vacuum, setting the filter material and thickness model parameters, the filter material is set to 3mm aluminum or 3mm copper; constructing a collimator model, set it to a truncated cone with an inner diameter of 0.6cm, an outer diameter of 4.6cm, a height of 4cm, and a beam angle of 45°; the 1000mm around the X-ray machine is set to spherical air.

[0021] Determine the radiation source: set the initial energy distribution of the X-ray source, and set the energy of the electron target to 0-500keV, which is adjustable. The corresponding X-ray machine can select all voltages from 0-500kV;

[0022] In one embodiment, the step of establishing an optimized radiation propagation model and performing simulation includes:

[0023] Setting radiation source parameters: The initial energy distribution of the radiation source has been determined, and the emission direction of the radiation source needs to be further set, and the electrons are set to hit the target vertically upwards;

[0024] Setting the radiation propagation environment: including the medium through which the radiation propagates, such as air, aluminum, copper, and lead shielding, and the physical properties of the medium, such as density;

[0025] The Monte Carlo method is introduced into the dynamic simulation process; a random variable E is set, and E obeys a specific probability distribution function, which is the energy distribution function f(E); then the energy distribution of the simulated radiation source is obtained by sampling this random variable E in large quantities;

[0026] E_i~f(E)

[0027] In each simulation i (i = 1, 2, ..., n), the energy E is randomly sampled according to the function f(E); then, all simulation results are counted, and the average value and standard deviation of the energy E are calculated to obtain the simulated radiation source energy distribution.

[0028] In one embodiment, generating two-dimensional and three-dimensional dose and energy distribution maps includes:

[0029] First, based on the radiation source and environmental parameters obtained by simulation, the radiation dose and energy of all points in the model are calculated;

[0030] After calculating the energy and dose of all points, the energy and dose information of these points are converted into colors and shapes in the chart;

[0031] Interpolation algorithms are used to smooth neighboring points. If it is a two-dimensional image, a color gradient from low to high is used to represent the size of the energy or dose. If it is a three-dimensional image, the size of the shape or transparency is used to represent the size of the energy or dose.

[0032] Finally, the obtained two-dimensional or three-dimensional distribution map is rendered to generate a high-definition image for users to view and analyze.

[0033] In one embodiment, the step of establishing the radiation intensity of a freely selectable detection point or point of interest comprises:

[0034] First, freely select a detection point, anywhere in three-dimensional space, called P(x,y,z), where (x,y,z) are the coordinates of the point;

[0035] Calculate the distance r between this point and the radiation source, which is calculated by the Pythagorean theorem:

[0036] When the state of the radiation source changes, the intensity changes, and the position moves, the above process is updated in real time, and the radiation dose of each point of interest is recalculated as the source changes.

[0037] In one embodiment, the simulation and assessment of the accident includes:

[0038] Define accident scenarios: Define the scenarios that may occur and predict possible accidental lighting accidents by simulating and analyzing these scenarios;

[0039] Accident simulation: Under the defined accident scenario, the accident is simulated first. During the simulation, the Monte Carlo simulation method is used to obtain the dose distribution and energy distribution in this case.

[0040] The evaluation process uses the absorption equivalent formula:

[0041] D=dε / dm

[0042] Where D is the absorption equivalent, dε is the average energy given by ionizing radiation to the material in a certain volume element, and dm is the mass in this volume element;

[0043] Realize dynamic radiation dose calculation: According to the set radiation source, calculate the radiation intensity or absorbed dose of the real-time detection point or focus point for different source strengths in each time period.

[0044] According to the results of simulation and evaluation, corresponding preventive measures or emergency treatment plans can be formulated in advance to reduce the impact of mislighting accidents.

[0045] On the other hand, an industrial radiation dose visualization simulation system based on FLUKA, the simulation system is applicable to the simulation method, and the simulation system comprises:

[0046] FLUKA model building and optimization module: This module is used to create and optimize the X-ray machine model, including the modeling and optimization of the X-ray machine structure, internal key components, and target materials;

[0047] Radiation parameter setting module: This module is used to set radiation parameters, such as target material and electron target energy;

[0048] Radiation propagation dynamic simulation module: Based on the physical process module, this module is used to realize the dynamic simulation of radiation propagation;

[0049] Dose and energy distribution map generation module: Generate two-dimensional and three-dimensional dose and energy distribution maps;

[0050] Intelligent point selection module: This module is used to automatically select representative and valuable detection points in the radiation field;

[0051] Mis-lighting accident simulation and assessment module: Rapid simulation and assessment of mis-lighting accidents, providing real-time and accurate data support;

[0052] Data visualization module: used to generate visualized charts and results from the simulated data, so as to facilitate analysis and evaluation by engineers and technicians.

[0053] Beneficial effects of the present invention:

[0054] The present invention can effectively prevent the occurrence of radiation accidents. Once an accident occurs, the method can quickly simulate and evaluate, provide effective protective measures, and effectively protect the safety of station personnel and equipment. At the same time, the simulation results can be updated in real time, which is closely related to the actual working status, providing real-time and accurate radiation data support, which plays a vital role in ensuring the safety of radiation operations.

[0055] Through two-dimensional and three-dimensional dose and energy distribution diagrams, engineers and technicians can have an intuitive understanding of the radiation field distribution, which helps them to conduct scientific analysis and decision-making, thereby improving work efficiency and reducing work difficulty.

[0056] The present invention can establish a digital X-ray machine model of all voltage types from 0 to 500 kV; obtain the dose distribution of the X-ray machine workplace and the surrounding environment, which is used to estimate the exposure dose of workers under normal working conditions or accident conditions. The X-ray energy distribution generated by the X-ray machine is obtained; it can be used for the accurate calculation of the conversion coefficient between the ambient dose equivalent and the air kerma in the radiation field and other related research. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flow chart of the method of the present invention;

[0058] Figure 2 Create and optimize the X-ray machine model flow chart for the present invention;

[0059] Figure 3 Establish a radiation propagation dynamic simulation flow chart for the present invention;

[0060] Figure 4 A flow chart of the present invention using a machine learning algorithm to automatically select the most representative and valuable detection points in a radiation field;

[0061] Figure 5 A flow chart of simulation and evaluation of mis-lighting accidents according to the present invention;

[0062] Figure 6 is a system block diagram of the present invention;

[0063] Figure 7 A model diagram of a digital X-ray machine of the present invention;

[0064] Figure 8 This is the irradiation model of the present invention. DETAILED DESCRIPTION

[0065] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Typical embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in the present invention. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0066] Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0067] Embodiment 1

[0068] like Figure 1 As shown, the FLUKA-based industrial radiation dose visualization simulation method includes:

[0069] like Figure 2 As shown, S1, create and optimize the X-ray machine model, build a mathematical model in the FLUKA software environment, including the X-ray machine body structure, internal key components and target materials; introduce an optimization algorithm to make the model closer to the performance of the X-ray machine actually used.

[0070] The process of creating and optimizing an X-ray machine model can be broken down into the following steps:

[0071] S101. Construct the basic model: According to the actual size and structure of the X-ray machine, set the model space and initialize the X-ray machine model. In the FLUKA software, first set the size of the main structure to 10cm×10cm×40cm, and then determine the target material to be tungsten. At the same time, set the focus size to 2mm x 3mm to achieve the basic mathematical model construction.

[0072] S102, setting environmental parameters: the model is further refined by setting the X-ray machine to be vacuum inside, setting model parameters such as filter material and thickness, for example, the filter material is set to 3mm aluminum or 3mm copper. Construct a collimator model, set to a truncated cone, with an inner diameter of 0.6cm, an outer diameter of 4.6cm, a height of 4cm, and a beam angle of 45°.

[0073] S103, determine the radiation source: set the initial energy distribution of the X-ray source, and set the energy of the electron target to 0-500keV, so the corresponding X-ray machine can select all voltages of 0-500kV. By adjusting the voltage, the electrons hit the tungsten target to generate X-rays of different energies.

[0074] like Figure 7 As shown, the X-ray machine (radiation source) model and irradiation model are constructed using FLUKA software. The digital X-ray machine model is constructed with reference to the structure and related parameters of a typical X-ray machine. The specific setting parameters are as follows:

[0075] (1) The overall size of the X-ray machine is set to 10cm×10cm×40cm;

[0076] (2) The target material is set to tungsten;

[0077] (3) The focal size is 2 mm × 3 mm;

[0078] (4) The energy of electron target shooting is adjustable from 0 to 500 keV;

[0079] (5) The interior of the X-ray machine is set to a vacuum;

[0080] (6) Filter material and thickness settings are optional, including typical setting parameters such as 3mm aluminum or 3mm copper;

[0081] (7) A 3 mm thick plexiglass is installed at the beam outlet of the X-ray machine as the wall of the X-ray tube;

[0082] (8) The collimator is set as a truncated cone with an inner diameter of 0.6 cm, an outer diameter of 4.6 cm, a height of 4 cm, and a beam angle of 45°;

[0083] (9) The shielding material of the X-ray machine itself is conservatively set to 4cmPb.

[0084] S2. Personalized setting of radiation parameters. The introduction of user-defined functions allows users to set various parameters according to actual needs, such as target materials and electron target energy, to improve the flexibility and accuracy of simulation.

[0085] 1) Create a user interface: Add a user interface design to the software to allow users to enter or select parameter values ​​in real time. The interface is clear and intuitive, and users can easily adjust parameters, improving the user experience.

[0086] 2) Set the target material and target energy: Users can select the target material in the software according to actual needs, and then set the size of the electron target energy according to actual needs. The range of this parameter can be 0 to 500 keV.

[0087] 3) Set other parameters: In addition to the basic target material and target energy, users can also set other important parameters, such as the size of the device, the inner and outer diameters of the collimator, the beam angle, etc.

[0088] 4) Save and call parameters: After the user sets all parameters, the system will automatically save these parameters. When simulating, the software will call these parameters to ensure the accuracy of the simulation.

[0089] like Figure 3 As shown, S3. Establish an optimized radiation propagation model and perform simulation calculations: Based on the preset physical process module, an optimization algorithm is introduced to describe the particle transport and interaction process.

[0090] S301, setting radiation source parameters: the initial energy distribution of the radiation source has been determined in the previous step. Now it is necessary to further set the emission direction of the radiation source, which can usually be set to uniform distribution or non-uniform distribution considering the actual situation.

[0091] S302, setting the radiation propagation environment: This includes the medium for radiation propagation, such as air, water, metal, etc., and the physical properties of the medium, such as density, temperature, etc. Setting environmental parameters requires not only considering the actual environment, but also the effects of the medium on radiation absorption, scattering, etc.

[0092] S303, implement dynamic simulation: according to the set radiation source and propagation environment, calculate the changes in radiation intensity and position for each time period.

[0093] The process of dynamic simulation introduces the Monte Carlo method; the process of dynamic simulation can introduce the Monte Carlo method, which is to achieve the purpose of numerical simulation of a system by simulating and counting a series of random processes. The Monte Carlo simulation method is a random sampling technique that models and estimates the behavior of complex systems by repeatedly random sampling within the range of possible output results. The key steps of this method include determining possible inputs, defining the method and range of random sampling, so that the results of each simulation are based on a possible input selected randomly.

[0094] The energy distribution of the radiation source is simulated by using the Monte Carlo simulation method. A random variable E is set, and E obeys a specific probability distribution function, which is the energy distribution function f(E). Then, a large number of samples are taken from this random variable E to obtain the simulated energy distribution of the radiation source.

[0095] E_i~f(E)

[0096] In each simulation i (i = 1, 2, ..., n), the energy E is randomly sampled according to the function f(E); then, all simulation results are counted, and the average value and standard deviation of the energy E are calculated to obtain the simulated radiation source energy distribution. f(E) is an energy distribution function that needs to be fitted by experimental data.

[0097] The entire process is a dynamic simulation based on time, in which all parameters involved need to be set with initial values, and then continuously updated during the simulation. This is the only way to more accurately simulate the radiation propagation process in real situations. Then, after the simulation is completed, the radiation dose distribution at different time points can be obtained, which can be provided to the user for corresponding control and adjustment.

[0098] like Figure 4 As shown in S4, based on the simulation calculation results, a radiation intensity technology for freely selecting detection points or focus points is established.

[0099] The method of establishing the radiation intensity of a freely selectable detection point or a point of interest includes:

[0100] When simulating radiation dose, a common problem is how to accurately calculate the radiation dose at a specific detection point or point of interest. The key to this problem is how to calculate the radiation intensity or radiation dose at a given distance from the radiation source. From a physical point of view, the radiation intensity obeys the inverse square law of distance, which can be expressed as: I = P / (4πr 2 ).

[0101] in:

[0102] I: Radiation intensity

[0103] P: total radiation power of the radiation source

[0104] r: distance from the radiation source to the detection point

[0105] However, in actual environments, the results obtained by such direct calculations will be affected by various factors, such as the attenuation of the air, the absorption and scattering of radiation by other substances, etc.

[0106] S401. First, freely select a detection point at any position in three-dimensional space, called P(x, y, z), where (x, y, z) is the coordinate of the point.

[0107] S402, calculate the distance r between this point and the radiation source, and calculate it by the Pythagorean theorem, that is,

[0108] When the state of the radiation source changes, the intensity changes, and the position moves, the above process is updated in real time, and the radiation dose of each point of interest is recalculated as the source changes.

[0109] S5. Develop 2D and 3D dose and energy distribution maps: Generate 2D and 3D dose and energy distribution maps.

[0110] The energy and dose information of these points are converted into colors and shapes in the chart. Visualization technology and graphics rendering technology in graphics are used. Interpolation algorithms are used to smooth neighboring points to make the resulting image more coherent. If it is a two-dimensional image, a color gradient from low to high can be used to represent the size of the energy or dose; if it is a three-dimensional image, the size of the shape or transparency can also be used to represent the size of the energy or dose.

[0111] Finally, the obtained two-dimensional or three-dimensional distribution map is rendered to generate a high-definition image for users to view and analyze.

[0112] S6. Based on the radiation intensity technology of freely selecting detection points or focus points, a dynamic radiation intensity calculation model is established.

[0113] The specific implementation process is as follows:

[0114] (1) Model parameter setting: Determine the environmental parameters, radiation source parameters and location information of the selected detection points in the model.

[0115] (2) Time period division: According to actual needs, the total simulation time is divided into several time periods.

[0116] (3) Dynamic calculation: In each time period, the radiation intensity of each point of interest is calculated according to the current model parameters and radiation source parameters based on the technology in S5.

[0117] (4) Repeat 3: Execute (3) for all time periods to obtain the radiation intensity of each time period.

[0118] Output dynamic results: Summarize the radiation intensity results of the detection points in each time period and output dynamic radiation intensity calculation results.

[0119] In this way, changes in radiation intensity can be dynamically calculated and presented under changing environmental or radiation source parameters, which helps monitor and manage the radiation environment.

[0120] S7. Simulation and assessment of accidental irradiation: Rapid simulation and assessment of accidental irradiation accidents.

[0121] like Figure 5 As shown, S7, simulation and evaluation of mis-lighting accidents: for mis-lighting accidents that occur, rapid simulation and evaluation can be performed to provide real-time and accurate data support for accident response and post-processing.

[0122] The simulation and assessment of accidental lighting is to predict and estimate possible accidents so as to make adequate preparations in advance. The detailed implementation steps are as follows:

[0123] S701. Define accident scenarios: There are many scenarios that may be involved in accidental lighting accidents, such as radiation leakage caused by equipment failure, human operation errors, etc. It is necessary to define possible scenarios and simulate and analyze these scenarios to predict possible accidental lighting accidents.

[0124] S702, accident simulation: In the defined accident scenario, the accident needs to be simulated first. When an accident occurs, the radiation dose calculation using the digital X-ray machine can also calculate the radiation dose generated by the exposed personnel at different positions, providing key dose data for radiation dose estimation and personnel treatment of accident personnel. The personnel exposure diagram established by the digital X-ray machine model is shown below Figure 8 During the simulation process, the Monte Carlo simulation method can be used to obtain the dose distribution and energy distribution that may occur in this case.

[0125] S703, Data analysis and evaluation: After the simulation is completed, a large amount of data will be obtained, including dose distribution, energy distribution, etc. These data need to be analyzed to evaluate the impact of possible mis-exposure accidents on the human body and equipment.

[0126] For example, we can calculate the dose that the human body may receive in the event of an accidental exposure. Based on the dose, the absorption equivalent formula is used in the evaluation process:

[0127] D=dε / dm

[0128] Where D is the absorption equivalent, dε is the average energy given by ionizing radiation to matter in a certain volume element, and dm is the mass of this volume element.

[0129] S704. Formulate preventive measures and emergency rescue plans: Based on the results of simulation and evaluation, corresponding preventive measures or emergency plans can be formulated in advance to reduce the impact of mis-lighting accidents.

[0130] During the whole process, it is necessary to correctly define the accident scenario, adopt the correct simulation method, and make corresponding response strategies based on the simulation and evaluation results, so as to replace the actual accident test and reduce the impact of accident on personnel and equipment.

[0131] Embodiment 2:

[0132] like Figure 6 As shown, the FLUKA-based industrial radiation dose visualization simulation system includes:

[0133] FLUKA model building and optimization module: This module is used to create and optimize the X-ray machine model, including the modeling and optimization of the X-ray machine body structure, internal key components, and target materials.

[0134] Radiation parameter setting module: This module is used to set radiation parameters, such as target material, electron target energy, etc., to improve the flexibility and accuracy of the simulation.

[0135] Radiation propagation dynamic simulation module: Based on the physical process module, this module is used to realize the dynamic simulation of radiation propagation.

[0136] Intelligent point selection module: This module is used to automatically select the most representative and valuable detection points in the radiation field to improve simulation efficiency and result accuracy.

[0137] Dose and energy distribution map generation module: Generate two-dimensional and three-dimensional dose and energy distribution maps.

[0138] Mistaken lighting accident simulation and assessment module: Rapid simulation and assessment of any mistaken lighting accidents, providing real-time and accurate data support.

[0139] Data visualization module: used to generate visualized charts and results from the simulated data, so as to facilitate analysis and evaluation by engineers and technicians.

[0140] In this FLUKA-based industrial radiation dose visualization simulation system, the FLUKA model building and optimization module first creates and optimizes the X-ray machine model, including the modeling and optimization of the X-ray machine body structure, internal key components, and target materials. Then, the radiation parameters are set through the radiation parameter setting module, including target materials, electron target energy, etc., to improve the flexibility and accuracy of the simulation. Next, the radiation propagation dynamic simulation module performs a dynamic simulation of radiation propagation based on the above set parameters and physical process models. During the dynamic simulation process, the intelligent point selection module automatically selects the most representative and valuable detection points in the radiation field to improve the simulation efficiency and the accuracy of the results. Then, the dose and energy distribution map generation module generates two-dimensional and three-dimensional dose and energy distribution maps based on the results of the dynamic simulation. The mis-exposure accident simulation and evaluation module quickly simulates and evaluates possible mis-exposure accidents based on the above simulation results, providing real-time and accurate data support for accident response and post-processing.

[0141] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0142] It should be understood that the detailed description of the technical solutions of the present invention with the help of the preferred embodiments is illustrative rather than restrictive. A person skilled in the art may modify the technical solutions described in the embodiments, or replace some of the technical features therein by equivalents, based on reading the specification of the present invention; and these modifications or replacements do not make the essence of the technical solutions of the corresponding specifications deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A visualization simulation method of industrial radiation dose based on FLUKA, characterized by: The method includes: Create and optimize the X-ray machine model, and build a mathematical model in the FLUKA software environment, including the machine structure, internal key components, and target materials; making the model closer to the performance of the actual X-ray machine; Personalized setting of radiation parameters, introduction of user-defined function, allowing users to set various parameters, target materials, and electron target energy according to actual needs, improving the flexibility and accuracy of simulation; Establish optimized radiation propagation model and perform simulation calculations; According to the simulation calculation results, the radiation intensity technology of freely selecting the detection point or the point of interest is established; Develop 2D and 3D dose and energy distribution maps: Generate 2D and 3D dose and energy distribution maps; A dynamic radiation intensity calculation model is established based on the radiation intensity technology of freely selecting detection points or focus points; Simulation and assessment of accidental irradiation accidents: Rapid simulation and assessment of accidental irradiation accidents.

2. The method for visualizing and simulating industrial radiation dose based on FLUKA according to claim 1, characterized in that: The method of creating and optimizing an X-ray machine model includes: Construct the basic model: According to the actual size and structure of the X-ray machine, set the model space and initialize the X-ray machine model. In the FLUKA software, first set the size of the main structure to 10cm×10cm×40cm and determine the target material to be tungsten; at the same time, set the focus size to 2mm x 3mm to achieve the basic mathematical model construction; Setting environmental parameters: By setting the inside of the X-ray machine to a vacuum, setting the filter material and thickness model parameters, the filter material is set to 3mm aluminum or 3mm copper; constructing a collimator model, set it to a truncated cone with an inner diameter of 0.6cm, an outer diameter of 4.6cm, a height of 4cm, and a beam angle of 45°; the 1000mm around the X-ray machine is set to spherical air. Determine the radiation source: set the initial energy distribution of the X-ray source. When the electron is shooting, the energy is set to be adjustable from 0 to 500 keV. The corresponding X-ray machine can select all voltages from 0 to 500 kV.

3. The method for visualizing and simulating industrial radiation dose based on FLUKA according to claim 1, characterized in that: The establishment of an optimized radiation propagation model and simulation includes: Setting radiation source parameters: The initial energy distribution of the radiation source has been determined, and the emission direction of the radiation source needs to be further set, and the electrons are set to hit the target vertically upwards; Setting the radiation propagation environment: including the medium through which the radiation propagates, such as air, aluminum, copper, and lead shielding, and the physical properties of the medium, such as density; The Monte Carlo method is introduced into the dynamic simulation process; a random variable E is set, and E obeys a specific probability distribution function, which is the energy distribution function f(E); then the energy distribution of the simulated radiation source is obtained by sampling this random variable E in large quantities; E_i~f(E) In each simulation i (i = 1, 2, ..., n), the energy E is randomly sampled according to the function f(E); then, all simulation results are counted, and the average value and standard deviation of the energy E are calculated to obtain the simulated radiation source energy distribution.

4. The method for visualizing and simulating industrial radiation dose based on FLUKA according to claim 1, characterized in that: The generating of two-dimensional and three-dimensional dose and energy distribution maps comprises: First, based on the radiation source and environmental parameters obtained by simulation, the radiation dose and energy of all points in the model are calculated; After calculating the energy and dose of all points, the energy and dose information of these points are converted into colors and shapes in the chart; Interpolation algorithms are used to smooth neighboring points. If it is a two-dimensional image, a color gradient from low to high is used to represent the size of the energy or dose. If it is a three-dimensional image, the size of the shape or transparency is used to represent the size of the energy or dose. Finally, the obtained two-dimensional or three-dimensional distribution map is rendered to generate a high-definition image for users to view and analyze.

5. The method for visualizing and simulating industrial radiation dose based on FLUKA according to claim 1, characterized in that: The method of establishing the radiation intensity of a freely selectable detection point or a point of interest includes: First, freely select a detection point, anywhere in three-dimensional space, called P(x,y,z), where (x,y,z) are the coordinates of the point; Calculate the distance r between this point and the radiation source, which is calculated by the Pythagorean theorem:

6. The method for visualizing and simulating industrial radiation dose based on FLUKA according to claim 1, characterized in that: The simulation and evaluation of the accidental lighting accident includes: Define accident scenarios: Define the scenarios that may occur and predict possible accidental lighting accidents by simulating and analyzing these scenarios; Accident simulation: Under the defined accident scenario, the accident is simulated first. During the simulation, the Monte Carlo simulation method is used to obtain the dose distribution and energy distribution in this case. The evaluation process uses the absorption equivalent formula: D=dε / dm Where D is the absorption equivalent, dε is the average energy given by ionizing radiation to the material in a certain volume element, and dm is the mass in this volume element; Realize dynamic radiation dose calculation: According to the set radiation source, calculate the radiation intensity or absorbed dose of the real-time detection point or focus point for different source strengths in each time period. According to the results of simulation and evaluation, corresponding preventive measures or emergency treatment plans can be formulated in advance to reduce the impact of mislighting accidents.

7. A visualization simulation system for industrial radiation dose based on FLUKA, wherein the simulation system is applicable to the simulation method according to any one of claims 1 to 6, characterized in that: The simulation system comprises: FLUKA model building and optimization module: This module is used to create and optimize the X-ray machine model, including the modeling and optimization of the X-ray machine structure, internal key components, and target materials; Radiation parameter setting module: This module is used to set radiation parameters, such as target material and electron target energy; Dose and energy distribution map generation module: generates two-dimensional and three-dimensional dose and energy distribution maps; Intelligent point selection module: this module is used to automatically select the most representative and valuable detection points in the radiation field; Mis-lighting accident simulation and assessment module: Rapid simulation and assessment of mis-lighting accidents, providing real-time and accurate data support; Data visualization module: used to generate visualized charts and results from the simulated data, so as to facilitate analysis and evaluation by engineers and technicians.

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