Method and system for evaluating irradiation damage effect of non-metallic material

Abstract

The invention relates to an evaluation method and system for a non-metallic material irradiation damage effect. The evaluation method comprises the following steps: constructing a geometric model according to material attributes of the non-metallic material, wherein the material attributes comprise chemical bonds; performing a simulation irradiation test on the geometric model by using a preset irradiation simulation environment and a preset irradiation physical model; calculating the bond breaking probability of the chemical bond according to the energy deposition information in the simulated irradiation test process; and obtaining the damage index of the non-metallic material according to the bond breaking probability. The evaluation efficiency and accuracy of the irradiation damage effect of the non-metallic material in the complex irradiation environment can be improved.

Description

Technical Field

[0001] This application mainly relates to the field of radiation damage evaluation technology for non-metallic materials, and specifically to an evaluation method and system for radiation damage effects on non-metallic materials. Background Technology

[0002] In the fields of aerospace and nuclear energy, the application of non-metallic materials often faces the challenge of high-energy particle irradiation in extreme environments. High-energy particle irradiation (such as beta rays, neutrons, and gamma rays) can cause microscopic damage such as molecular chain breakage and cross-linking, leading to degradation of the mechanical properties of the materials and resulting in low reliability.

[0003] Studying irradiation damage through real-world experiments is costly, time-consuming, and unsafe. Multi-scale simulations (such as simulations of atomic-level damage to macroscopic property evolution) can improve the efficiency of predicting material lifetime. Currently, Geant4 software can be used to simulate irradiation of non-metallic materials, but it requires manual processing of massive amounts of data and makes it difficult to directly obtain the desired irradiation damage results. Existing methods for simulating and evaluating irradiation damage to non-metallic materials are inefficient. Summary of the Invention

[0004] The technical problem to be solved by this application is to provide a method and system for evaluating the radiation damage effect of non-metallic materials, which can improve the efficiency and accuracy of evaluating the radiation damage effect of non-metallic materials under complex radiation environments.

[0005] The technical solution adopted in this application to solve the above-mentioned technical problems is a method for evaluating the irradiation damage effect of non-metallic materials, comprising: constructing a geometric model based on the material properties of the non-metallic material, the material properties including chemical bonds; conducting a simulated irradiation test on the geometric model using a preset irradiation simulation environment and a preset irradiation physical model; calculating the bond breakage probability of the chemical bonds based on the energy deposition information during the simulated irradiation test; and obtaining the damage index of the non-metallic material based on the bond breakage probability.

[0006] In one embodiment of this application, after the step of constructing a geometric model based on the material properties of the non-metallic material, the method further includes: dividing the geometric model into multiple grid regions according to a preset grid density; calculating the bond breaking probability of the chemical bonds based on the energy deposition information during the simulated irradiation test; and further includes: calculating the bond breaking probability of the corresponding chemical bonds in each grid region based on the energy deposition information in each grid region during the simulated irradiation test.

[0007] In one embodiment of this application, after the step of constructing a geometric model based on the material properties of the non-metallic material, the method further includes: dividing the geometric model into spatial regions to obtain multiple spatial regions and corresponding coordinate ranges; calculating the bond breaking probability of the chemical bonds based on the energy deposition information during the simulated irradiation test, and further includes: calculating the bond breaking probability of the chemical bonds within the corresponding coordinate range based on the energy deposition information within each spatial region during the simulated irradiation test.

[0008] In one embodiment of this application, the energy deposition information includes energy deposition density and energy deposition; the bond breakage probability is calculated using the following formula:

[0009] Where p represents the bond breakage probability; This represents the energy deposition density; This represents the critical energy density for breaking the chemical bond. Determined based on a preset bond energy database; m represents the number of effective energy depositions required to damage the chemical bond, where m is an integer greater than 1; The coordinates of the geometric model are represented; This indicates the energy deposition during the irradiation process; This represents the micro-element volume corresponding to the energy deposition.

[0010] In one embodiment of this application, the bond breakage probability is estimated based on the formula for the radiation chemical yield G; or the bond breakage probability is calculated based on a dynamic bond recombination model and the bond repair effect under irradiation.

[0011] In one embodiment of this application, the preset irradiation simulation environment includes irradiated particles; the preset irradiation physics model includes a list of physical processes, which is used to simulate the interaction between the irradiated particles and the non-metallic material; the list of physical processes includes at least one of the following physical reactions: if the irradiated particles are charged particles, the corresponding physical reactions include electron ionization and bremsstrahlung; if the irradiated particles are... The physical reactions for the particles include the photoelectric effect, Compton scattering, and electron-electron pair generation; if the irradiated particle is a neutron, the corresponding physical reactions include elastic collisions, inelastic collisions, and neutron capture between the neutron and the target atomic nucleus.

[0012] In one embodiment of this application, the preset irradiation simulation environment includes irradiated particles; the simulated irradiation experiment includes: constructing the irradiation reaction of each irradiated particle as an irradiation event; in the pre-reaction step region and the post-reaction step region, simulating the trajectory, energy deposition, and absorbed dose distribution of each irradiated particle under irradiation using the Monte Carlo method based on the irradiation event; obtaining irradiation event information corresponding to each step of the reaction of each irradiated particle, wherein the irradiation event information includes the energy deposition information.

[0013] In one embodiment of this application, after obtaining the damage index of the non-metallic material based on the bond breakage probability, the method further includes: generating a bond breakage probability distribution map and / or a material damage cloud map based on the damage index; and / or analyzing the damage condition of the non-metallic material based on the damage index, wherein the damage condition includes at least one of irradiation damage, damage evolution relationship, performance degradation trend, and lifetime damage.

[0014] In one embodiment of this application, the non-metallic material includes polyetheretherketone; the material properties also include at least one of the following: three-dimensional shape, size, molecular formula, density, molecular structure, average molecular chain length, arrangement, crystal structure, and chemical bond energy; the preset irradiation simulation environment includes at least one of the following: environmental medium, irradiated particle source, irradiated particle flux, irradiated particle energy, irradiated particle incident direction, irradiated particle momentum direction, boundary conditions, initial conditions, and step size.

[0015] To address the aforementioned technical problems, this application also proposes an evaluation system for the irradiation damage effect of non-metallic materials, comprising: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the above-mentioned evaluation method for the irradiation damage effect of non-metallic materials.

[0016] The technical solution of this application constructs a geometric model of non-metallic materials, conducts simulated experiments under simulated irradiation conditions, calculates the probability of chemical bond breakage based on energy deposition data, and obtains the damage index, thereby achieving a quantitative assessment of irradiation damage to non-metallic materials. This application improves the efficiency and accuracy of assessing the irradiation damage effects of non-metallic materials under complex irradiation environments, while avoiding the high cost and radiation risks of traditional experimental methods. Attached Figure Description

[0017] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for evaluating the irradiation damage effect of non-metallic materials according to an embodiment of this application; Figure 2This is a flowchart of simulating energy deposition and calculating molecular structural damage of PEEK material using Geant4 in one embodiment of this application; Figure 3 This is a flowchart of irradiation conditions and model settings in one embodiment of this application; Figure 4 This is a flowchart of an embodiment of the present application using Geant4 to simulate an irradiation process; Figure 5 This is a flowchart of damage calculation for PEEK material in one embodiment of this application; Figure 6 This is a schematic diagram of a non-metallic material calculation example during an experiment in one embodiment of this application; Figure 7 This is a schematic diagram of the spatial distribution of energy deposition under coarse and fine grids during an experiment in one embodiment of this application; Figure 8 This is a schematic diagram of geometrically modeling a non-metallic material example as a thin film during an experiment in one embodiment of this application; Figure 9 In one embodiment of this application, the electron flux was 1e4 / cm during the experiment. 2 A schematic diagram illustrating the relationship between energy deposition and incident distance; Figure 10 In one embodiment of this application, the electron flux was 1e4 / cm during the experiment. 2 A schematic diagram illustrating the function of absorbed dose versus incident distance; Figure 11 In one embodiment of this application, the electron flux was 1e4 / cm during the experiment. 2 A schematic diagram illustrating the relationship between the probability of chemical bond breaking and the incident distance. Figure 12 This is a schematic diagram of the corresponding information of proton irradiation during an experiment in one embodiment of this application; Figure 13 This is a schematic diagram of the corresponding information of photon irradiation during an experiment in one embodiment of this application; Figure 14 This is a system block diagram of an embodiment of the evaluation system for the irradiation damage effect of non-metallic materials. Detailed Implementation

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0019] Many specific details are set forth in the following description in order to provide a full understanding of this application. However, this application may also be implemented in other ways different from those described herein, and therefore this application is not limited to the specific embodiments disclosed below.

[0020] As illustrated in this application, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0021] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0022] The following section will first introduce the situation of non-metallic materials under irradiation, as well as some of the technical concepts of irradiation simulation in this application.

[0023] Non-metallic materials, such as polyetheretherketone (PEEK), are high-performance polymers widely used in extreme or special environments such as aerospace, nuclear power, medical devices, electronics, and automotive industries due to their excellent mechanical strength, high-temperature resistance, chemical corrosion resistance, low flammability, and superior electrical insulation properties. In some specific applications, PEEK components are inevitably exposed to radiation from various high-energy particles. These particles include, but are not limited to: charged particles (such as beta rays, protons, alpha particles, and heavy ions); neutral particles (such as neutrons); and electromagnetic radiation (such as gamma rays). When these high-energy particles interact with PEEK materials, they transfer energy to the material's molecular structure, triggering a series of complex physicochemical processes that alter the microstructure and chemical composition of the PEEK material, thereby affecting its macroscopic properties, such as mechanical degradation and decreased physicochemical stability.

[0024] Therefore, understanding how microscopic damage (such as defect generation, chain breakage, crosslinking, etc.) of PEEK materials under high-energy particle irradiation accumulates and evolves over time, ultimately leading to the degradation of their macroscopic properties (i.e., damage evolution relationship), is crucial for assessing their long-term reliability in irradiated environments, predicting their service life, guiding material selection and structural design, and developing novel radiation-resistant polymer materials.

[0025] Considering that practical experimental studies of irradiation damage (especially the high-dose irradiation required to achieve significant performance degradation) are often time-consuming, expensive, and difficult and dangerous to operate in highly radioactive environments, simulation models based on physical mechanisms can simulate damage evolution processes across multiple timescales (e.g., from picosecond-level cascade damage to years of long-term aging) in a shorter time. Furthermore, simulations can predict the long-term performance degradation trends and lifetimes of materials under specific irradiation conditions, providing crucial data for engineering design. Therefore, multi-scale simulations (e.g., from atomic and molecular scales to continuous medium scales) of the damage evolution process of PEEK materials under high-energy particle irradiation have significant theoretical and practical implications.

[0026] Geant4 (Geometry and Tracking 4) is a simulation software used to simulate the motion, interaction, and energy deposition processes of high-energy particles in matter. Existing methods for simulating polymer materials using Geant4 lack specific data processing solutions for radiation damage analysis. Users need to manually write complex ROOT macros or analysis scripts to sift through massive amounts of Hit or Step information, a tedious and error-prone process. Furthermore, simulation outputs typically only include physical quantities (such as dose and energy deposition), lacking an automated process for directly converting them into parameters of interest in practical engineering applications (such as the probability of chemical bond breaking). Therefore, a simulation method is needed that can efficiently, accurately, and quantitatively predict the performance evolution of PEEK materials under complex irradiation environments.

[0027] To address the aforementioned problems, this application proposes a method for assessing the irradiation damage effects of non-metallic materials, applicable to scenarios requiring rapid assessment of the irradiation damage effects on non-metallic materials (such as PEEK). This method can run on a local computer, such as within the computer's controller, or on a cloud platform. When running on a cloud platform, data from the local computer interacts with cloud platform data via a wireless network. For example, the cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, interconnected cloud, and multiple clouds, or any combination thereof. This application does not impose any limitations on the operating environment of this method for assessing the irradiation damage effects of non-metallic materials.

[0028] Figure 1 This is a flowchart of a method for evaluating the irradiation damage effect of non-metallic materials according to an embodiment of this application, with reference to... Figure 1 As shown, the method for evaluating the irradiation damage effect of non-metallic materials in this embodiment includes the following steps: Step S110: Construct a geometric model based on the material properties of the non-metallic material, including chemical bonds.

[0029] Step S120: Conduct a simulated irradiation test on the geometric model using a preset irradiation simulation environment and a preset irradiation physical model.

[0030] Step S130: Calculate the probability of chemical bond breaking based on the energy deposition information during the simulated irradiation test.

[0031] Step S140: Obtain the damage index of non-metallic materials based on the bond breakage probability.

[0032] The following details steps S110 to S140 described above: In step S110, a geometric model is constructed based on the material properties of the non-metallic material, including chemical bonds. In some embodiments, the non-metallic material includes polyetheretherketone (PEEK).

[0033] For example, this application models the geometric properties of PEEK polymer materials based on their macroscopic molecular formula and density to obtain a geometric model. In practical applications, non-metallic materials can also be polytetrafluoroethylene, polyimide, polyphenylene sulfide, etc., and this application does not limit the type of non-metallic material. The overall technical solution will be illustrated later using PEEK material as an example.

[0034] In some embodiments, the material properties further include at least one of the following: three-dimensional shape, size, molecular formula, density, molecular structure, average molecular chain length, arrangement, crystal structure, and chemical bond energy. For example, in practical applications, different material properties can be selected as needed to construct geometric models to match performance requirements under different irradiation environments.

[0035] To obtain the spatial distribution of polymer damage, this application designs two processing methods for the geometric model. The first method involves geometrically dividing the model into regions (similar to meshing in the finite element method), storing the energy deposition in each region, and then calculating the bond breakage probability. This method is suitable for geometrically simple materials. The second method involves mathematically dividing the model into regions, determining the coordinate range of each small spatial region, and then statistically analyzing the position and energy deposition information at each reaction step within this spatial range to calculate the bond breakage probability. This method is suitable for geometrically complex materials. These two division methods are described below.

[0036] For the first geometric region division method, in some embodiments, after step S110 of constructing a geometric model based on the material properties of non-metallic materials, step S110a is further included: dividing the geometric model into meshes according to a preset mesh density to obtain multiple mesh regions.

[0037] For example, the geometric model can be modeled as a cube and divided into 2... 2 In region 2, each region's grid is assigned a corresponding number. After meshing the geometric model, the probability of bond breaking in each grid region can be calculated based on the energy deposition information within each grid region during the simulated irradiation experiment.

[0038] This application refines the geometric model into multiple grid regions, enabling energy deposition information to be accurately mapped to micro-units. This allows for the localized calculation of chemical bond breaking probability and improves the accuracy of irradiation damage assessment, facilitating the accurate identification of irradiation-sensitive areas of materials.

[0039] For the second method of mathematically dividing the region, in some embodiments, after step S110 of constructing a geometric model based on the material properties of the non-metallic material, step S110b is further included: performing spatial region division processing on the geometric model to obtain multiple spatial regions and corresponding coordinate ranges.

[0040] For example, after mathematically dividing the region, spatially resolved multi-scale damage statistics can be performed. This can be achieved by using geometric or mathematical partitioning to statistically analyze energy deposition and mapping the results to the molecular structural scale of PEEK (such as monomer units, crystalline regions, or amorphous regions), thus resolving the problem of indistinguishable local damage differences. After spatially dividing the geometric model, the probability of bond breakage within the corresponding coordinate range can be calculated based on the energy deposition information within each spatial region during the simulated irradiation experiment.

[0041] This application divides the geometric model into spatial regions, establishing a correspondence between energy deposition information and specific coordinate ranges. This enables the localized calculation of the probability of chemical bond breaking, more accurately reflecting the microscopic distribution characteristics of internal material damage and improving the accuracy of irradiation damage assessment.

[0042] In step S120, a simulated irradiation test is conducted on the geometric model using a preset irradiation simulation environment and a preset irradiation physical model.

[0043] In some embodiments, the preset irradiation simulation environment includes at least one of the following: environmental medium (such as air or vacuum), irradiated particle source, irradiated particle fluence, irradiated particle energy, irradiated particle incident direction, irradiated particle momentum direction, boundary conditions, initial conditions, and step size.

[0044] For example, the environmental medium surrounding the PEEK material can be set to air or vacuum as needed. The irradiation particle source is created in the form of a particle gun, and the position of the particle gun, the particle incident direction, and the momentum direction can be set as needed. During the simulation, particles are emitted from the particle gun; the default particles can be gamma photons with an energy of 6 MeV. The particle source can be placed directly above the PEEK model, and the particle incident direction is random in the xy plane. This application can flexibly simulate material damage under real irradiation scenarios by adjusting the parameters in the preset irradiation simulation environment.

[0045] In some embodiments, the preset irradiation simulation environment includes irradiated particles; the preset irradiation physics model includes a list of physical processes, which is used to simulate the interaction between irradiated particles and non-metallic materials; the list of physical processes includes at least one of the following physical reactions (1)-(3).

[0046] (1) If the irradiated particles are charged particles, the corresponding physical reactions include electron ionization and bremsstrahlung.

[0047] (2) If the irradiated particles are Particles, and the corresponding physical reactions include the photoelectric effect, Compton scattering, and electron pair formation.

[0048] (3) If the irradiated particle is a neutron, the corresponding physical reactions include elastic collisions, inelastic collisions and neutron capture between the neutron and the target nucleus.

[0049] For example, to speed up computation, the physical reactions of the irradiation process can be customized, such as by customizing the physics list in Geant4. The "coupled thermo-mechanical effects" can also be extended to achieve a more comprehensive damage assessment. In practical applications, the possible reactions during charged particle irradiation can be identified as electron ionization and bremsstrahlung. The possible reactions that can occur with particle irradiation include the photoelectric effect, Compton scattering, and electron-pair generation; while neutron irradiation will result in strong interactions, such as elastic and inelastic collisions with the target atomic nuclei, as well as neutron capture.

[0050] Based on the above reaction behavior and the Geant4 user manual, a custom physics list can be created for the simulation experiment, i.e., selecting appropriate physical reaction models in Geant4. For example, physical reaction models can be selected as G4EmStandardPhysics_option4, G4DecayPhysics, G4DecayPhysics, G4HadronElasticPhysicsXS, G4StoppingPhysics, G4IonPhysicsXS, G4IonElasticPhysics, G4NeutronTrackingCut, etc.

[0051] For each incident particle, it is necessary to consider the various reactions it may undergo (including side reactions). Therefore, to obtain the spatial distribution of the damage state, information about the interactions at each step during the particle's transport through the material can be identified and collected, including the pre-step and post-step regions, energy deposition, absorbed dose, and physical event identification. At the end of the simulation, this interaction information is integrated and summarized. For example, after Geant4's "run," the energy deposition under different physical reactions in each segmented region can be obtained.

[0052] This application provides a customized physical process model for PEEK materials. By using a specific list of physical processes, all key interactions are accurately simulated, ensuring coverage of all key physical processes related to PEEK (such as ionization, elastic scattering, nuclear reactions, etc.), thereby enabling the differentiation of the effects of different types of irradiated particles.

[0053] The following example illustrates the process of setting up irradiation conditions and models in this application.

[0054] Figure 3 This is a flowchart illustrating the irradiation conditions and model settings in one embodiment of this application. (Reference) Figure 3As shown, the geometric model, particle source, and physical model settings are performed respectively. For the geometric model settings (corresponding to step S110 mentioned earlier): The physical entity of the material sample, its position relative to the reference frame, and the relative positions of each component are set; the environment and reference frame (air, vacuum, etc.) of the material sample are set; a geometric model is established based on the three-dimensional shape and size of the material sample. For the particle source settings (corresponding to the preset irradiation simulation environment in step S120 mentioned earlier): Based on the experiment, the corresponding incident particles are selected in Geant4, such as charged particles, gamma photons, neutrons, etc.; the particle flux and energy are set according to standards; single-particle or mixed-particle incident is set, and the position, emission direction, and particle momentum of the particle gun are set. For the physical model settings (corresponding to the preset irradiation physical model in step S120 mentioned earlier): Based on the type of incident particles, the possible physical reactions are determined; the incident particle information and all process information of the physical reactions are registered; all physical reactions are arranged and combined to obtain a custom physical list.

[0055] In some embodiments, step S120 of conducting a simulated irradiation test includes: The irradiation response of each irradiated particle is constructed as an irradiation event.

[0056] In the pre- and post-reaction-step regions, the Monte Carlo method is used to simulate the geometric model of the trajectory, energy deposition, and absorbed dose distribution of each irradiated particle under irradiation, based on the irradiation event.

[0057] We obtain irradiation event information corresponding to each step of the reaction of each irradiated particle, including energy deposition information.

[0058] For example, the Monte Carlo simulation of irradiation in this application uses Geant4 software, and the simulation of polymer chemical bond breaking is achieved through a self-written program. In addition to Geant4, other particle transport software such as the fluctuation cascade simulation program (FLUktuierende KAskade, FLUKA), the Monte Carlo N-Particle program (MCNP), and the Particle and Heavy Ion Transport code System (PHITS) are also applicable, and machine learning algorithms can be combined to accelerate the simulation process.

[0059] This application uses Geant4 version v11.2.2 for simulation. particle, particle, PEEK was irradiated by particles, protons, neutrons, etc. Simulation experiments were conducted on the SCNET platform, Linux operating system, with a server configuration of x86 64C 2.5GHz 256GB. Parallel computing was performed using the Message Passing Interface (MPI) (single node, 64 cores), or different parallel computing modes such as Graphics Processing Unit (GPU) acceleration and cloud computing platforms.

[0060] This application uses Geant4 to simulate polymer energy deposition under different irradiation conditions and fluxes for different irradiated particles. In the Geant4 simulation, all particle fluxes are emitted through a single run. Each incident particle has a corresponding event, including all physical reactions that occur within that particle, and each reaction process has multiple steps. To statistically analyze all energy deposition during the irradiation process, the energy deposition in each step of each event needs to be summed, and then the results are aggregated in the run to calculate the bond breakage probability.

[0061] This application implements a two-stage evaluation process through the collaborative use of Monte Carlo simulation and bond-breaking models. The first stage calculates energy deposition using Monte Carlo simulators such as Geant4; the second stage outputs bond-breaking probabilities by analyzing the energy deposition data and combining it with a bond energy database. This application decouples particle physics simulation from chemical bond damage modeling, ensuring both simulation accuracy and computational flexibility. Specifically, by simulating the trajectory of irradiated particles and the energy deposition process event-by-event using the Monte Carlo method, it can accurately track the dynamic interactions of each particle in the material and obtain accurate energy deposition information.

[0062] The following example illustrates the process of using Geant4 to simulate the irradiation process in this application.

[0063] Figure 4 This is a flowchart illustrating an irradiation process simulation using Geant4 in one embodiment of this application. (Reference) Figure 4 As shown, during the irradiation process simulation using Geant4, the simulation process and information collection and analysis were performed separately. For example, Figure 4 The “simulation process” shown corresponds to the steps of conducting the simulated irradiation experiment mentioned earlier: constructing the irradiation response of each irradiated particle as an irradiation event; and simulating the trajectory, energy deposition, and absorbed dose distribution of each irradiated particle under irradiation using the Monte Carlo method in the pre- and post-reaction step regions based on the irradiation event. Specifically, for Figure 4The simulation process in Geant4 is as follows: Each simulation is considered a run, including all reactions of each particle (primary reactions and all secondary reactions), and a general information collection function is defined within the run. All reactions of each incident particle (including primary reactions, secondary reactions, and all reactions of the secondary particles they produce) are considered an event. Each particle is the smallest unit in the reaction, and at each step, it has the necessary simulation information, including the pre-step and post-step regions, energy deposition, absorbed dose, physical event identification, etc.

[0064] For example, Figure 4 The "information collection and analysis" shown corresponds to the steps of conducting simulated irradiation experiments mentioned earlier: obtaining irradiation event information corresponding to each step of the reaction of each irradiated particle, including energy deposition information. Specifically, for Figure 4 Information collection and analysis: Information about the irradiation process is collected using a "step-event-run" model, with statistics compiled for each reaction step. The statistical information for each step of the reaction for each particle is then summarized to obtain information for each event. Finally, the information from each event is aggregated to obtain the summary information for the irradiation process.

[0065] In step S130, the probability of chemical bond breaking (i.e. the probability of polymer chemical bond breaking) is calculated based on the energy deposition information during the simulated irradiation test.

[0066] In some embodiments, energy deposition information includes energy deposition density and energy deposition; the bond breakage probability is calculated using the following formulas (1) and (2): (1) (2) Where p represents the probability of bond breakage; Indicates energy deposition density; The critical energy density representing the breaking of chemical bonds. Determined based on a pre-defined bond energy database; m represents the number of effective energy depositions required to damage the chemical bond, and m is an integer greater than 1; Represents the coordinates of the geometric model; This indicates the energy deposition during the irradiation process; This represents the micro-element volume corresponding to energy deposition.

[0067] For example, m can represent the number of hits required to cause damage to the target (i.e., break a key). The smaller m is, the slower the probability function changes (p is the independent variable). (where m is the dependent variable), this application sets m to 2. For The determination of the bond energy can be referenced using the online bond energy database iBonD (internet Bond-energy Databank). Considering that PEEK mainly produces phenyl, phenoxy, carbonyl, and hydroxyl products under irradiation by charged particles and photons, the range of bond breaking can be determined by combining the chemical formula of PEEK. For example, the bond breaking range includes hydroxyl dehydrogenation (3.73 eV), CO bond breaking (4.81 eV), C / C bond breaking of ketones (4.21 eV), phenyl ether bond breaking (1.17 eV), and C=O double bond breaking (7.81 eV), where eV represents electron volts. Therefore, for all the divided regions, the corresponding bond breaking probability can be automatically obtained, which is a quantifiable index of the microstructure.

[0068] The above formulas (1)-(2) are equivalent to a microscopic bond breakage probability calculation model based on a bond energy database. This model can be used to calculate the bond breakage probability by combining specific chemical bond energy parameters of PEEK materials (such as CO bonds, phenyl ether bonds, C=O bonds, etc.). Compared to traditional macroscopic dose assessment methods, this application establishes a direct mapping relationship between particle energy deposition and chemical bond breakage, thus providing a basis for accurate assessment. Specifically, this application establishes a quantitative relationship between energy deposition density and bond breakage probability, and utilizes critical energy density parameters in a pre-set bond energy database to achieve accurate quantitative calculation of the chemical bond breakage probability. This reflects the microscopic distribution characteristics of irradiation energy within the material, thereby more accurately predicting the structural evolution and performance degradation trends of the material under irradiation conditions.

[0069] In some embodiments, the bond breakage probability is estimated based on the radiation chemical yield G-value formula; or the bond breakage probability is calculated based on a dynamic bond recombination model and the bond repair effect under irradiation. For example, by introducing the radiation chemical yield G-value formula or the dynamic bond recombination model, this application can accurately reflect the dynamic equilibrium process of chemical bond breakage and repair during irradiation.

[0070] The following example illustrates the damage calculation process for PEEK materials in this application.

[0071] Figure 5 This is a flowchart illustrating damage calculation for PEEK material in one embodiment of this application. (Reference) Figure 5As shown, the damage model is constructed and the bond breakage probability is calculated. For constructing the damage model: the model is constructed using the formulas (1)-(2) mentioned above. The parameters in the formulas include energy deposition and the critical energy density for bond breakage. The product of PEEK under irradiation is determined, and the range of bond breakage is determined by combining the chemical formula of PEEK. The critical energy density for bond breakage is obtained from the online bond energy database iBonD. For calculating the bond breakage probability: after obtaining the required information in run, information processing (calculating the bond breakage probability) is performed directly. Based on the information processing results and custom output statements, the damage information is exported, and post-processing (such as generating damage cloud maps, particle range, etc.) is performed using MATLAB scripts.

[0072] In step S140, the damage index of the non-metallic material is obtained based on the bond breakage probability. For example, the statistics of energy deposition are spatially distributed, and the statistics of other information are also spatially distributed. Therefore, after calculating the spatial distribution of the bond breakage probability, the damage index of the non-metallic polymer can be reflected. At the same time, the range of the radiating particles and the total energy deposition can also reflect the damage index of the non-metallic polymer.

[0073] In some embodiments, after obtaining the damage index of the non-metallic material based on the bond breakage probability, the method further includes: generating a bond breakage probability distribution map and / or a material damage cloud map based on the damage index; and / or analyzing the damage status of the non-metallic material based on the damage index, wherein the damage status includes at least one of irradiation damage, damage evolution relationship, performance degradation trend, and lifetime damage.

[0074] For example, this application transforms the damage index into a visualized bond breakage probability distribution map or material damage cloud map, which can intuitively present the spatial distribution characteristics of irradiation damage, improving the intuitiveness of irradiation damage diagnosis and the efficiency of subsequent decision-making. In practical applications, during the evaluation of irradiation damage effects on non-metallic materials, a parallel computing and automated data analysis architecture can be used. Simulations can be accelerated through MPI and GPU parallel computing, and automated scripts can be used to directly extract Geant4 Hit and Step data to generate bond breakage probability distribution maps. This improves the efficiency of high-flux irradiation simulations and achieves the high-efficiency processing capabilities required for engineering applications.

[0075] The following example illustrates the process of using Geant4 to simulate energy deposition and calculate molecular structural damage in this application.

[0076] Figure 2 This is a flowchart illustrating the simulation of energy deposition and calculation of molecular structural damage using Geant4 on PEEK materials in one embodiment of this application. (Reference) Figure 2As shown, the overall process includes: acquiring PEEK material input, performing GEANT4 simulation energy deposition (including: defining the simulation environment, establishing a physical model, simulating energy deposition and absorbed dose), and calculating molecular structure damage (including constructing a molecular structure evolution model and performing molecular structure damage simulation).

[0077] For example, Figure 2 The "Input" and "Define Simulation Environment" shown correspond to step S110, which involves constructing a geometric model based on the material properties of the non-metallic material, and step S120, which involves setting up a preset irradiation simulation environment. Specifically, for Figure 2 To obtain input for PEEK materials, you need to obtain the average molecular chain length, arrangement, and crystal structure of PEEK. To define the simulation environment, you need to define the molecular structure of the PEEK material, the geometric model of the material sample, the irradiation source, boundary conditions, initial conditions, step size, etc. Figure 2 The "establishing a physical model" shown can correspond to the preset irradiation physical model in step S120 above. Specifically, for Figure 2 Physical models were established: particle physics models of ionization and strong-weak interactions were established; statistical physics models of polymer chain bond breaking and cross-linking were established.

[0078] Figure 2 The "simulated energy deposition and absorbed dose" shown corresponds to the simulated irradiation experiment on the geometric model in step S120 above. Specifically, for Figure 2 Simulated energy deposition and absorbed dose: statistical sampling to simulate primary and secondary particle trajectories, energy deposition, and absorbed dose distribution under irradiation. Figure 2 The "molecular structure evolution model" and "molecular structure damage simulation" shown correspond to step S130, which calculates the bond breaking probability of chemical bonds based on energy deposition information during the simulated irradiation test, and step S140, which obtains the damage index of non-metallic materials based on the bond breaking probability. Specifically, for Figure 2 Medium-sized molecular structure evolution model: Analyze energy deposition and allocate energy according to the number of chemical bonds; establish statistical models for molecular chain breakage and cross-linking processes under irradiation. For molecular structure damage simulation: calculate the bond breakage probability of different chemical bonds; calculate the polymer damage index and analyze the rules and trends of configuration changes.

[0079] For example, this application is equivalent to a rapid assessment method for the irradiation damage effect of PEEK materials based on the Monte Carlo method and bond breakage model, which can automatically calculate the bond breakage probability of the PEEK microstructure after irradiation. The assessment method for the irradiation damage effect of non-metallic materials in this application can be performed according to the following simplified steps: 1. Construct a PEEK geometric model and divide it into regions (to obtain the energy deposition in each region, i.e., the spatial distribution of damage evolution).

[0080] 2. Set up the particle source for irradiation and set the corresponding particle injection rate according to the test standards.

[0081] 3. Define a physics list based on the possible physical processes to more accurately simulate the interaction between charged particles, neutrons, and PEEK.

[0082] 4. Statistically analyze the energy deposition information during the irradiation process (step-event-run) and calculate the bond breakage probability.

[0083] 5. The above simulations are completed using batch processing. This application allows modification of relevant parameters (mesh density, incident particles, particle flux, particle energy, etc.) via script files without recompiling or recalculating, directly obtaining spatial information about the damage distribution.

[0084] The technical solution of this application can perform data processing and multi-scale damage modeling efficiently and accurately, improving engineering practicality and optimizing computational resources. The technical effects that this application can produce are as follows: In terms of technical processes, traditional methods using Geant4 to simulate polymer irradiation require complex data screening and analysis, which is time-consuming and error-prone. The automated data extraction and analysis process described in this application can be built as a program that directly outputs microscopic bond breakage probabilities by integrating Geant4 simulation results and the bond energy database iBonD, improving evaluation efficiency and reducing human error. Furthermore, existing methods typically only provide macroscopic dose data, failing to reflect the damage status of specific chemical bonds. This application, based on multi-physics process coupling modeling, uses customized physics lists (such as G4EmStandardPhysics_option4, G4HadronElasticPhysicsXS, etc.) to accurately simulate various interactions between particles and PEEK, quantifying the breakage probabilities of different chemical bonds (such as CO bonds, phenyl ether bonds, C=O bonds, etc.), making the simulation results more scientifically and engineeringally valuable.

[0085] In terms of engineering applicability, this application, through spatially resolved bond breakage probability calculation, can directly provide microscopic damage distribution data that can be used for lifetime prediction. Compared with existing methods that only output physical quantities (such as energy deposition), this application is more convenient for materials research and development and structural optimization. At the same time, through computational resource optimization design (such as MPI parallel computing, adaptive mesh generation, and selective physical process loading), this application can improve simulation efficiency, enabling long-term damage evolution prediction under high flux irradiation to be completed within a reasonable time, solving the problems of high cost and high risk in experimental research.

[0086] This application also includes experiments on non-metallic materials, specifically a Geant4 simulation of the electron beam curing process of polyester fibers. The experimental results of this application are presented below.

[0087] Figure 6 This is a schematic diagram of a non-metallic material calculation example during testing in one embodiment of this application. (Reference) Figure 6 As shown, the polyester fiber is defined as a cylinder (also modeled according to its molecular formula and density) with a diameter of 10 cm. The electron source is located directly above it, 10 cm away. Furthermore, the electron beam is incident perpendicularly with an energy of 10 MeV and a particle number of 1e7.

[0088] Figure 7 This is a schematic diagram illustrating the spatial distribution of energy deposition under coarse and fine grids during an experiment in one embodiment of this application. (Reference) Figure 7 As shown, it illustrates the spatial distribution of total energy deposition through grids of varying coarseness.

[0089] Figure 8 This is a schematic diagram illustrating the geometric modeling of a non-metallic material example as a thin film during an experiment in one embodiment of this application. (Reference) Figure 8 As shown, in this example, the PEEK geometry is modeled as a thin film (…). To save computation time, h is set according to the different rays. The particle source is selected as an electron beam, proton beam, or gamma particle beam, located 0.8h directly above the beam (z-axis) at a distance from its center. The momentum direction of the particles is any direction in the xy-plane, with energies of 120 keV, 170 keV, and 250 keV, respectively; the flux is selected as 1e⁴ / cm. 2 1e5 / cm 2 1e6 / cm 2 1e7 / cm 2 .

[0090] Figure 9 In one embodiment of this application, the electron flux was 1e4 / cm during the experiment. 2 A schematic diagram illustrating the relationship between energy deposition and incident distance. Figure 10 In one embodiment of this application, the electron flux was 1e4 / cm during the experiment. 2 A schematic diagram illustrating the function of absorbed dose versus incident distance. Figure 11 In one embodiment of this application, the electron flux was 1e4 / cm during the experiment. 2 A schematic diagram illustrating the probability of bond breaking as a function of incident distance. Figure 12 This is a schematic diagram showing the corresponding information of proton irradiation during an experiment in one embodiment of this application. Figure 13This is a schematic diagram of the corresponding information of photon irradiation during an experiment in one embodiment of this application.

[0091] according to Figures 9-13 The curves or lines shown indicate that heavily charged particles have a shorter range in PEEK; for example, the proton's range in PEEK is only 2... The range of electrons is approximately... In other words, compared to electrons, heavily charged particles have weaker penetrating power. However, when the incident energies are similar (120 keV, 170 keV), the energy deposition and absorbed dose of proton irradiation are two orders of magnitude higher than those of electrons. For example, at a particle fluence of 1e⁷ / cm². 2 Below this, the extreme value of the absorbed dose from electron irradiation is 1.5. The absorbed dose is approximately 1.4, while the extreme value of the absorbed dose from proton irradiation is approximately 1.4. This indicates that irradiation by heavily charged particles causes greater superficial damage to PEEK, while electron irradiation may cause deeper, less severe damage to PEEK.

[0092] Furthermore, photon irradiation lacks the concept of range, and unlike irradiation of charged particles, it does not exhibit a distinct extreme point of energy deposition. This means that even when PEEK is irradiated with gamma photons, significant energy deposition and absorbed dose may occur at deeper depths. Experimental results indicate that gamma photons possess the strongest penetrating power, but the energy deposition and absorbed dose in PEEK from photon irradiation are relatively small (two orders of magnitude smaller than electron irradiation). Therefore, photon irradiation does not cause large localized damage to PEEK overall, but rather widespread, minor damage. Simultaneously, for irradiation of all particles, the probability of bond breakage is extremely low when the absorbed dose is very small, consistent with the material properties of PEEK.

[0093] This application also includes a system for evaluating the irradiation damage effect of non-metallic materials, comprising a memory and a processor. The memory stores instructions executable by the processor; the processor executes these instructions to implement the aforementioned method for evaluating the irradiation damage effect of non-metallic materials.

[0094] Figure 14 This is a system block diagram of a system for evaluating the irradiation damage effect of non-metallic materials according to an embodiment of this application. (Reference) Figure 14As shown, the non-metallic material irradiation damage effect assessment system 1400 may include an internal communication bus 1401, a processor 1402, a read-only memory (ROM) 1403, a random access memory (RAM) 1404, and a communication port 1405. When applied to a personal computer, the non-metallic material irradiation damage effect assessment system 1400 may also include a hard disk 1406. The internal communication bus 1401 enables data communication between the components of the non-metallic material irradiation damage effect assessment system 1400. The processor 1402 can make judgments and issue prompts. In some embodiments, the processor 1402 may consist of one or more processors. The communication port 1405 enables the non-metallic material irradiation damage effect assessment system 1400 to communicate with external systems. In some embodiments, the non-metallic material irradiation damage effect assessment system 1400 can send and receive information and data from a network through the communication port 1405. The non-metallic material irradiation damage assessment system 1400 may also include different types of program storage units and data storage units, such as a hard disk 1406, a read-only memory (ROM) 1403, and a random access memory (RAM) 1404, capable of storing various data files used for computer processing and / or communication, as well as possible program instructions executed by the processor 1402. The processor executes these instructions to implement the main part of the method. The results of the processor processing are transmitted to the user equipment via a communication port and displayed on the user interface.

[0095] The above-mentioned method for evaluating the irradiation damage effect of non-metallic materials can be implemented as a computer program, stored in hard disk 1406, and loaded into processor 1402 for execution, so as to implement the method for evaluating the irradiation damage effect of non-metallic materials of this application.

[0096] This application also includes a computer-readable medium storing computer program code that, when executed by a processor, implements the aforementioned method for assessing the irradiation damage effects on non-metallic materials.

[0097] When the method for assessing the irradiation damage effects of non-metallic materials is implemented as a computer program, it can also be stored as an article of manufacture in a computer-readable storage medium. For example, computer-readable storage media can include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic stripes), optical discs (e.g., compact discs (CDs), digital multifunction discs (DVDs)), smart cards, and flash memory devices (e.g., electrically erasable programmable read-only memory (EPROM), cards, sticks, key drives). Furthermore, the various storage media described herein can represent one or more devices and / or other machine-readable media used for storing information. The term "machine-readable medium" can include, but is not limited to, wireless channels and various other media (and / or storage media) capable of storing, containing, and / or carrying code and / or instructions and / or data.

[0098] It should be understood that the embodiments described above are merely illustrative. The embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For hardware implementation, the processor may be implemented within one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, and / or other electronic units designed to perform the functions described herein, or combinations thereof.

[0099] Some aspects of this application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The aforementioned hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system." The processor may be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. Furthermore, aspects of this application may manifest as computer products residing in one or more computer-readable media, including computer-readable program code. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compressed CDs, digital multifunction DVDs, etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).

[0100] A computer-readable medium may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and so on, or suitable combinations thereof. A computer-readable medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer-readable medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signals, or similar media, or any combination of the above media.

[0101] The basic concepts have been described above. Obviously, for those skilled in the art, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0102] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0103] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used to describe embodiments are sometimes modified by the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in this application are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

Claims

1. A method for evaluating the irradiation damage effect on non-metallic materials, characterized in that, include: A geometric model is constructed based on the material properties of the non-metallic material, including chemical bonds; The geometric model was subjected to simulated irradiation experiments using a preset irradiation simulation environment and a preset irradiation physical model. The probability of breaking the chemical bonds is calculated based on the energy deposition information during the simulated irradiation test. as well as The damage index of the non-metallic material is obtained based on the bond breakage probability.

2. The method for evaluating the irradiation damage effect of non-metallic materials as described in claim 1, characterized in that, After the step of constructing a geometric model based on the material properties of the non-metallic material, the method further includes: dividing the geometric model into meshes according to a preset mesh density to obtain multiple mesh regions; The calculation of the bond breaking probability of the chemical bond based on the energy deposition information during the simulated irradiation test further includes: calculating the bond breaking probability of the corresponding chemical bond in each grid region based on the energy deposition information in each grid region during the simulated irradiation test.

3. The method for evaluating the irradiation damage effect of non-metallic materials as described in claim 1, characterized in that, After the step of constructing a geometric model based on the material properties of the non-metallic material, the method further includes: dividing the geometric model into spatial regions to obtain multiple spatial regions and corresponding coordinate ranges; The calculation of the bond breaking probability of the chemical bond based on the energy deposition information during the simulated irradiation test further includes: calculating the bond breaking probability of the chemical bond within the corresponding coordinate range based on the energy deposition information in each spatial region during the simulated irradiation test.

4. The method for evaluating the irradiation damage effect of non-metallic materials as described in any one of claims 1-3, characterized in that, The energy deposition information includes energy deposition density and energy deposition; the bond breakage probability is calculated using the following formula: Where p represents the bond breakage probability; This represents the energy deposition density; This represents the critical energy density for breaking the chemical bond. Determined based on a preset bond energy database; m represents the number of effective energy depositions required to damage the chemical bond, where m is an integer greater than 1; The coordinates of the geometric model are represented; This indicates the energy deposition during the irradiation process; This represents the micro-element volume corresponding to the energy deposition.

5. The method for evaluating the irradiation damage effect on non-metallic materials as described in any one of claims 1-3, characterized in that, The bond breakage probability is estimated based on the formula for the radiation chemical yield G; or the bond breakage probability is calculated based on the dynamic bond recombination model and the bond repair effect under irradiation.

6. The method for evaluating the irradiation damage effect of non-metallic materials as described in claim 1, characterized in that, The preset irradiation simulation environment includes irradiated particles; the preset irradiation physics model includes a list of physical processes, which is used to simulate the interaction between the irradiated particles and the non-metallic material; the list of physical processes includes at least one of the following physical reactions: If the irradiated particles are charged particles, the corresponding physical reactions include electron ionization and bremsstrahlung. If the irradiated particles are Particles, and the corresponding physical reactions include the photoelectric effect, Compton scattering, and electron pair formation; If the irradiated particle is a neutron, the corresponding physical reactions include elastic collisions, inelastic collisions, and neutron capture between the neutron and the target atomic nucleus.

7. The method for evaluating the irradiation damage effect of non-metallic materials as described in claim 1, characterized in that, The preset irradiation simulation environment includes irradiated particles; The simulated irradiation test includes: The irradiation response of each irradiated particle is constructed as an irradiation event; In the pre- and post-reaction step regions, the Monte Carlo method is used to simulate the trajectory, energy deposition, and absorbed dose distribution of each irradiated particle under irradiation based on the irradiation event; The irradiation event information corresponding to each step of the reaction of each irradiated particle is obtained, and the irradiation event information includes the energy deposition information.

8. The method for evaluating the irradiation damage effect of non-metallic materials as described in claim 1, characterized in that, After the step of obtaining the damage index of the non-metallic material based on the bond breakage probability, the method further includes: Generate a bond breakage probability distribution map and / or a material damage cloud map based on the damage index; and / or The damage condition of the non-metallic material is analyzed based on the damage index, and the damage condition includes at least one of irradiation damage, damage evolution relationship, performance degradation trend and lifespan damage.

9. The method for evaluating the irradiation damage effect of non-metallic materials as described in claim 1, characterized in that, The non-metallic material includes polyetheretherketone; The material properties also include at least one of the following: three-dimensional shape, size, molecular formula, density, molecular structure, average molecular chain length, arrangement, crystal structure, and chemical bond energy; The preset irradiation simulation environment includes at least one of the following: environmental medium, irradiated particle source, irradiated particle flux, irradiated particle energy, irradiated particle incident direction, irradiated particle momentum direction, boundary conditions, initial conditions, and step size.

10. A system for evaluating the irradiation damage effect on non-metallic materials, characterized in that, include: Memory is used to store instructions executed by the processor; A processor for executing the instructions to implement the method for evaluating the irradiation damage effect of nonmetallic materials as described in any one of claims 1-9.

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