Dispersion type fuel element dynamic damage evolution method, device and equipment

Abstract

The invention provides a dispersion type fuel element dynamic damage evolution method, device and equipment, and relates to the technical field of nuclear reactor physical thermal calculation, and the method comprises the following steps: constructing an element geometric simulation model of a dispersion type fuel element, and constructing a particle geometric simulation model of a plurality of fuel particles; the fuel particles have corresponding simulation points in the element geometric simulation model; the control flow engineering software calls the element geometric simulation model and the particle geometric simulation model so as to determine target fuel particles of which the particle geometric simulation model fails from the multiple fuel particles based on a first simulation result of the particle geometric simulation model; and the control flow engineering software adds microcracks to simulation points corresponding to the target fuel particles in the element geometric simulation model so as to complete the damage evolution process of the fuel element. The failure particles can be accurately locked, the dynamic process of damage evolution is restored, a reliable basis is provided for evaluating the full life cycle of the fuel element, and the precision and credibility of simulation analysis are improved.

Description

Technical Field

[0001] This disclosure relates to the field of nuclear reactor physics and thermal calculation technology, and in particular to a method, apparatus and equipment for dynamic damage evolution of dispersed fuel elements. Background Technology

[0002] Particulate dispersion composites are composite materials in which inclusions are dispersed within a matrix material. They form the core technological foundation for constructing dispersed fuel elements. These inclusions can be materials in the form of fibers, particles, etc., and can act as reinforcing and functional materials, thus endowing the composite material with unique properties and functions. In particulate dispersion composites, the particles are uniformly dispersed within the matrix material and work synergistically with it to achieve their intended effect.

[0003] Particulate dispersion composites possess many unique characteristics and advantages. First, particles can effectively enhance the mechanical properties of the matrix material. Second, different types of particles can endow composites with diverse functions, meeting the performance and functional requirements of various fields. Furthermore, the interfacial effect between particles and the matrix material is also a crucial factor influencing the performance of composites; improving the interface can enhance the overall performance of the composite material.

[0004] However, due to the complex structure of particulate dispersion composites, factors such as particle size distribution, geometry, and spatial distribution can affect the performance of the composites. The interface between the particles and the matrix has a significant impact on the composite properties, including interfacial adhesion strength and stress transfer. Especially in dispersed fuel elements used in nuclear energy, how to simulate the damage evolution of the complex internal structure of dispersed fuel elements at multiple scales is a key technical challenge for optimizing fuel element design and ensuring the safe operation of reactors. Summary of the Invention

[0005] This disclosure aims to at least partially address one of the technical problems in the related art.

[0006] Therefore, the first objective of this disclosure is to propose a method, apparatus, and equipment for dynamic damage evolution of dispersed fuel elements, analyze the influence of the temperature distribution of fuel balls on the temperature distribution of fuel particles coated with different power, and accurately, efficiently, and in real time calculate the temperature distribution of coated fuel particles.

[0007] The second objective of this disclosure is to propose a diffuse fuel element dynamic damage evolution device.

[0008] The third objective of this disclosure is to propose an electronic device.

[0009] The fourth objective of this disclosure is to provide a non-transitory computer-readable storage medium storing computer instructions.

[0010] To achieve the above objectives, a first aspect of this disclosure provides a method for dynamic damage evolution of dispersed fuel elements, the method comprising:

[0011] A component geometric simulation model of a dispersed fuel element is constructed, and a particle geometric simulation model of multiple fuel particles is constructed; wherein, in the component geometric simulation model, there exists a simulation point corresponding to the fuel particle, and the model state of the fuel particle is a non-failure state;

[0012] The control flow engineering software calls the component geometry simulation model and the particle geometry simulation model to determine the target fuel particle from the plurality of fuel particles whose particle geometry simulation model has failed, based on the first simulation result of the particle geometry simulation model.

[0013] The flow engineering software is controlled to add microcracks to the simulation points corresponding to the target fuel particles in the geometric simulation model of the component, so as to complete the damage evolution process of the fuel element.

[0014] To achieve the above objectives, a second aspect of this disclosure provides a dispersion-type fuel element dynamic damage evolution device, the device comprising:

[0015] A construction module is used to construct a component geometric simulation model of a dispersed fuel element and a particle geometric simulation model of multiple fuel particles; wherein, in the component geometric simulation model, there are simulation points corresponding to the fuel particles, and the model state of the fuel particles is a non-failure state;

[0016] The calling module is used to control the flow engineering software to call the component geometry simulation model and the particle geometry simulation model, so as to determine the target fuel particle whose particle geometry simulation model fails from the plurality of fuel particles based on the first simulation result of the particle geometry simulation model;

[0017] The processing module is used to control the flow engineering software to add microcracks to the simulation points corresponding to the target fuel particles in the component geometric simulation model, so as to complete the damage evolution process of the fuel element.

[0018] To achieve the above objectives, a third aspect of this disclosure provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0019] To achieve the above objectives, a fourth aspect of this disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method described in the first aspect.

[0020] The method, apparatus, and electronic equipment for dynamic damage evolution of dispersed fuel elements provided in this disclosure construct a geometric simulation model of the dispersed fuel element and multiple particle geometric simulation models of fuel particles. Each element geometric simulation model contains simulation points corresponding to fuel particles, and the model state of the fuel particles is unfailed. Control flow engineering software calls the element geometric simulation model and the particle geometric simulation model, and based on the first simulation result of the particle geometric simulation model, determines the target fuel particle whose particle geometric simulation model has failed from among the multiple fuel particles. The control flow engineering software adds microcracks to the simulation points corresponding to the target fuel particles in the element geometric simulation model to complete the damage evolution process of the fuel element. Therefore, by leveraging the synergistic effect of the element geometric simulation model and the particle geometric simulation model of the fuel particles, the failed particles are accurately located, and the dynamic damage evolution process is reconstructed using a microcrack dynamic addition mechanism. This not only provides a reliable basis for evaluating the full life-cycle performance of fuel elements and improves the accuracy and reliability of simulation analysis, but also effectively guides the structural optimization design of fuel elements, providing key technical support for improving the safety and reliability of nuclear energy systems.

[0021] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0022] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:

[0023] Figure 1 This is a schematic flowchart illustrating a dynamic damage evolution method for a dispersed fuel element provided in an embodiment of this disclosure.

[0024] Figure 2 A schematic diagram of the structure of the dispersion-type fuel element provided in this disclosure;

[0025] Figure 3 A schematic diagram of the structure of the fuel pellets provided in this disclosure;

[0026] Figure 4 This is a schematic flowchart of another method for dynamic damage evolution of a dispersed fuel element provided in an embodiment of this disclosure.

[0027] Figure 5 A schematic diagram of the simulated points for adding microcracks provided in this disclosure;

[0028] Figure 6 This is a schematic diagram of the structure of a dispersion-type fuel element dynamic damage evolution device provided in an embodiment of this disclosure. Detailed Implementation

[0029] Embodiments of this disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0030] It should be noted that the acquisition, storage, use, and processing of data in this disclosed technical solution comply with the relevant provisions of laws and regulations.

[0031] The following description, with reference to the accompanying drawings, outlines a method, apparatus, and device for dynamic damage evolution of dispersed fuel elements according to embodiments of this disclosure.

[0032] Figure 1 This is a schematic flowchart illustrating a dynamic damage evolution method for a dispersed fuel element provided in an embodiment of this disclosure.

[0033] This embodiment illustrates the use of the dispersed fuel element dynamic damage evolution method configured in a dispersed fuel element dynamic damage evolution device. The charging device can be applied to any electronic device so that the electronic device can perform the dispersed fuel element dynamic damage evolution function.

[0034] Among them, electronic devices can be any device with computing capabilities, such as personal computers, mobile terminals, servers (or cloud computing), etc. Mobile terminals can be hardware devices with various operating systems, touch screens and / or displays, such as in-vehicle devices, mobile phones, tablets, personal digital assistants, wearable devices, etc.

[0035] like Figure 1 As shown, the method for dynamic damage evolution of dispersed fuel elements may include the following steps:

[0036] Step 101: Construct a geometric simulation model of the dispersed fuel element and a particle geometric simulation model of multiple fuel particles.

[0037] Specifically, for any fuel particle among multiple fuel particles, there exists a corresponding simulation point in the component's geometric simulation model. In other words, each fuel particle has a corresponding simulation point in the component's geometric simulation model.

[0038] The model state of the fuel particle can be a non-failure state, which can be used to indicate that the particle geometry simulation model of the corresponding fuel particle has not failed.

[0039] In this embodiment of the disclosure, a geometric simulation model of a dispersed fuel element can be constructed, and a particle geometric simulation model of any fuel particle among multiple fuel particles can be constructed. In one example, firstly, the geometric features and boundary conditions of the dispersed fuel element can be determined, and the geometric features of the fuel particles can be determined. The geometric features of the dispersed fuel element include its geometric shape, geometric dimensions, and dispersion space range. The boundary conditions of the dispersed fuel element may include, but are not limited to, the temperature boundary (also known as the thermal boundary or thermal condition), mechanical conditions, and concentration conditions of the fuel element. The geometric features of the fuel particles include parameter distribution information such as geometric shape, geometric dimensions, and geometric dimensions. For example, ... Figure 2 The schematic diagram of the dispersed fuel element shown indicates that its numerical model is a sphere with a three-dimensional geometry (which can be simplified to two dimensions due to axisymmetry). The spatial range of particle dispersion is the internal dispersion region. Boundary conditions include defining the fuel element's temperature boundary (e.g., 1200K), mechanical conditions (e.g., unconstrained free conditions), and concentration conditions (e.g., 0). Figure 3 The schematic diagram of the fuel particle structure shown indicates that the numerical model is a sphere with a three-dimensional geometry (which can be simplified to two dimensions due to axisymmetry). The geometrical parameter distribution of the fuel particles is, for example, a uniform distribution satisfying (x, y, z), meaning the particle center coordinates (x, y, z) are uniformly distributed in three-dimensional space. Next, the number of fuel particles and their spatial positions within the dispersed fuel element can be determined, for example, by performing X-ray scanning on the fuel element to obtain the three-dimensional spatial information and number of internal fuel particles. Secondly, the control flow engineering software calls the finite element software to construct a geometric simulation model of the dispersed fuel element based on its geometric features. This model includes multiple simulation points, each corresponding to a fuel particle based on its spatial location. The simulation point's state and physical field variables (referred to as the first physical field variable in this disclosure, such as temperature, stress intensity, target concentration, and target gas pressure) can be initialized based on the boundary conditions of the dispersed fuel element. For example, the initialization state of the simulation point is set to an unfailed state, the fission product concentration to 0, and the fission gas pressure to 0. Finally, based on the geometric features of the fuel particles, multiple particle geometric simulation models of the fuel particles are constructed, and the model state of the corresponding fuel particles is initialized to an unfailed state based on the simulation point's state.

[0040] The dispersion space range can be used to indicate the area in which fuel particles are distributed within the fuel element through diffusion.

[0041] Among them, the parameter distribution information of geometric dimensions can be used to indicate the parameter distribution of fuel particle geometry, such as size parameters (e.g., diameter, aspect ratio, etc.), statistical characteristic parameters (e.g., size mean, median, etc.), distribution morphology parameters (e.g., kurtosis, skewness, etc.), distribution model (e.g., normal distribution, etc.).

[0042] Step 102: The control flow engineering software calls the component geometry simulation model and the particle geometry simulation model to determine the target fuel particle from multiple fuel particles based on the first simulation result of the particle geometry simulation model.

[0043] The target fuel particle can be a fuel particle whose corresponding particle geometry simulation model has failed.

[0044] The first simulation result can be used to indicate the values ​​of multiple physical field variables (referred to as the second physical field variable in this disclosure) associated with the particle geometry model.

[0045] In this embodiment of the disclosure, the control flow engineering software calls the component geometry simulation model and the particle geometry simulation model to determine whether the particle geometry simulation model of any fuel particle is invalid based on the first simulation result of the particle geometry simulation model of any fuel particle. If it is determined that the particle geometry simulation model of the fuel particle is invalid, the fuel particle is identified as the target fuel particle.

[0046] In one example, the control flow engineering software can call the finite element software to perform coupled calculations on the component geometric simulation model based on the physical field variables initialized at each simulation point, obtain the simulation results of the component geometric simulation model, and set boundary conditions for the particle binding simulation model based on the simulation results of the component geometric simulation model, thereby obtaining the boundary conditions of the particle geometric simulation model; the control flow engineering software calls the finite element software to perform coupled calculations on the particle geometric simulation model, thereby obtaining the first simulation result of the particle geometric simulation model; based on the first simulation result of the particle geometric simulation model, the control flow engineering software determines the target fuel particle from multiple fuel particles from which the particle geometric simulation model fails.

[0047] Step 103: The control flow engineering software adds microcracks to the simulation points corresponding to the target fuel particles in the component geometric simulation model to complete the damage evolution process of the fuel element.

[0048] In one example, flow engineering software can add microcracks of random direction (or random angle) and random size to the simulation points corresponding to the target fuel particles in the component's geometric simulation model, thereby completing the damage evolution process of the fuel element.

[0049] The dynamic damage evolution method for dispersed fuel elements disclosed in this embodiment constructs a geometric simulation model of the dispersed fuel element and multiple particle geometric simulation models of fuel particles. Each fuel particle has a corresponding simulation point in the element geometric simulation model, and each fuel particle is marked with a status flag indicating that its corresponding particle geometric simulation model has not failed. Control flow engineering software calls the element geometric simulation model and the particle geometric simulation model, and based on the first simulation result of the particle geometric simulation model, identifies the target fuel particle whose particle geometric simulation model has failed from among the multiple fuel particles. The control flow engineering software adds microcracks to the simulation points in the element geometric simulation model corresponding to the target fuel particle to complete the damage evolution process of the fuel element. Therefore, by leveraging the synergistic effect of the element geometric simulation model and the particle geometric simulation model of the fuel particles, the failed particles are accurately located, and the dynamic damage evolution process is reconstructed using a microcrack dynamic addition mechanism. This not only provides a reliable basis for evaluating the full life-cycle performance of fuel elements and improves the accuracy and reliability of simulation analysis, but also effectively guides the structural optimization design of fuel elements, providing key technical support for improving the safety and reliability of nuclear energy systems.

[0050] This disclosure provides another method for dynamic damage evolution of dispersed fuel elements. Figure 4 This is a schematic flowchart of another method for dynamic damage evolution of a dispersed fuel element provided in an embodiment of this disclosure.

[0051] like Figure 4 As shown, the method for dynamic damage evolution of dispersed fuel elements may include the following steps:

[0052] Step 401: Construct a geometric simulation model of the dispersed fuel element and a particle geometric simulation model of multiple fuel particles.

[0053] It should be noted that the explanation of step 401 can be found in the relevant description in any embodiment of this disclosure, and will not be repeated here.

[0054] Step 402: The control flow engineering software performs a process of multiple processing steps, wherein, in any one processing step, the first fuel particle for this processing step is determined from multiple fuel particles.

[0055] Optionally, in some embodiments, during any processing, for any fuel particle among multiple fuel particles, if the model state of the fuel particle is in an unfailed state, then the fuel particle is determined as the first fuel particle for this processing.

[0056] It should be noted that this disclosure does not limit the number of the first fuel particles processed in this instance.

[0057] Step 403: Call the component geometry simulation model and the particle geometry simulation model of the first fuel particle being processed to obtain the first simulation result of the first fuel particle being processed.

[0058] Optionally, in some embodiments, a component geometry simulation model is invoked to perform a first coupling calculation of multiple first physical field variables at each simulation point, obtaining a first value of multiple first physical field variables at each simulation point after this processing; a particle geometry simulation model of the first fuel particle being processed is invoked to perform a second coupling calculation of multiple second physical field variables of the first fuel particle being processed, based on the first value of multiple first physical field variables obtained in this processing at the simulation point corresponding to the first fuel particle being processed, obtaining a second value of multiple second physical field variables of the first fuel particle being processed after this processing, and the second value of multiple second physical field variables of the first fuel particle being processed after this processing can be determined as the first simulation result of the first fuel particle being processed.

[0059] The first physical field variable may include, but is not limited to, temperature, stress intensity, concentration, etc., at the corresponding simulation point, and this disclosure does not impose any limitations on this. It should also be noted that this disclosure does not limit the number of first physical field variables.

[0060] The second physical field variable may include, but is not limited to, the temperature, stress intensity, concentration, etc. of the corresponding fuel particles, and this disclosure does not impose any restrictions on this. It should also be noted that this disclosure does not impose any restrictions on the number of the first physical field variables.

[0061] In one example, the control flow engineering software can call the finite element software to call the component geometry simulation model based on the physical field variables initialized at each simulation point, and perform a first coupling calculation on multiple first physical variables at each simulation point to obtain the simulation result of the component geometry simulation model after this processing, that is, the first value of multiple first physical variables at each simulation point after this processing. Based on the first value of multiple first physical variables at any simulation point after this processing, boundary conditions are set for the particle combination simulation model of the fuel particle corresponding to that simulation point to obtain the boundary conditions of the particle geometry simulation model of the fuel particle corresponding to the simulation point. Then, the control flow engineering software calls the finite element software to call the particle geometry simulation model of the first fuel particle processed this time, and performs a second coupling calculation on multiple second physical field variables of the first fuel particle processed this time based on the boundary conditions of the particle geometry simulation model of the first fuel particle processed this time, to obtain the second value of multiple second physical field variables of the first fuel particle processed this time after this processing. The second value of multiple second physical field variables of the first fuel particle processed this time after this processing can be determined as the first simulation result of the first fuel particle processed this time.

[0062] Thus, through a multi-level coupled calculation process, a comprehensive and high-precision simulation of the damage evolution mechanism of fuel elements was achieved. Specifically, the distribution of the first physical field variables at each simulation point was obtained through the element geometric simulation model, providing accurate boundary conditions for subsequent particle-level analysis. Then, based on these boundary conditions, the second physical field variables of the first fuel particle were coupled and calculated, fully characterizing the response characteristics of the fuel particle under the action of complex physical fields. This not only improves computational efficiency but also accurately captures the interaction between the fuel particle and the matrix material, providing a reliable basis for assessing the remaining life and safety of fuel elements. At the same time, it lays a solid foundation for optimizing fuel element design and improving the operational reliability of nuclear energy systems.

[0063] Step 404: Based on the first simulation result of the first fuel particle processed in this step, determine whether the first fuel particle processed in this step is the target fuel particle corresponding to this step.

[0064] The target fuel particle can be a fuel particle whose corresponding particle geometry simulation model has failed.

[0065] Optionally, in some embodiments, when the second physical field variable includes the stress intensity of the target layer in the corresponding fuel particle, if the second value of the stress intensity of the first fuel particle in the target layer after the current processing is not less than the set intensity threshold, then the particle geometry simulation model of the first fuel particle in the current processing is determined to be invalid, and the first fuel particle in the current processing is determined to be the target fuel particle corresponding to the current processing.

[0066] The target layer can be a structural layer of the fuel particle, such as a core layer, inner cladding layer, intermediate layer, or outer cladding layer. In one example, the target layer is the SiC intermediate layer of the fuel particle. It should be noted that this example is merely exemplary, and in practical applications, other structural layers can also be used; this disclosure does not impose any limitations on this.

[0067] The intensity threshold can be preset, and this disclosure does not restrict its value.

[0068] In one example, if the stress intensity of the first fuel particle after the current treatment is not less than the set intensity threshold, then the particle geometry simulation model of the first fuel particle after the current treatment is determined to be invalid, and the first fuel particle after the current treatment is determined to be the target fuel particle corresponding to the current treatment.

[0069] This allows for the determination of the target fuel particles during any given processing step.

[0070] It should be noted that when the second value of the stress intensity of the first fuel particle in the target layer after this treatment is less than the set intensity threshold, it is determined that the particle geometry simulation model of the first fuel particle in this treatment has not failed.

[0071] Optionally, in some embodiments, the flow engineering software can update the model state of the target fuel particle corresponding to the current processing from a non-failure state to a failed state. This allows for updating the model state of the fuel particle.

[0072] Step 405: Add microcracks to the simulation points in the component geometric simulation model corresponding to the target fuel particles in this process to complete the damage evolution process of the fuel element during this process.

[0073] In one example, control flow engineering software can add microcracks of random direction (or random angle) and random size to the simulation points in the component's geometric simulation model corresponding to the target fuel particles being processed. This simulates the damage evolution process of the fuel element during the current processing. The simulation points with added microcracks are as follows: Figure 5 As shown.

[0074] Optionally, in some embodiments, if the set conditions are not met in any one processing step, the flow engineering software can be controlled to repeat the processing step until the set conditions are met.

[0075] The set conditions can be preset, and this disclosure does not restrict the setting of the set conditions. In one example, the set condition can be: the number of times the processing procedure is executed reaches the maximum number of executions.

[0076] The dynamic damage evolution method for dispersed fuel elements disclosed in this embodiment involves performing multiple processing steps using control flow engineering software. In each processing step, a first fuel particle is identified from multiple fuel particles. The element's geometric simulation model and the particle geometric simulation model of the first fuel particle are then called to obtain a first simulation result for the first fuel particle. Based on this first simulation result, it is determined whether the first fuel particle is the target fuel particle for this processing. Microcracks are added to the simulation points in the element's geometric simulation model corresponding to the target fuel particle to complete the damage evolution process of the fuel element during this processing. Therefore, through multiple iterative processing steps, the failure sequence and damage evolution characteristics of different fuel particles can be comprehensively captured, dynamically reflecting the entire process of the fuel element from local damage to overall failure. This achieves efficient and accurate simulation of fuel element damage evolution, improving the accuracy and reliability of simulation analysis, providing quantitative basis for the structural optimization design of fuel elements, effectively reducing the operational risks of nuclear energy systems, shortening the R&D cycle, saving computational costs, and providing strong technical support for nuclear fuel safety assessment and performance improvement.

[0077] To clearly illustrate the dynamic damage evolution method for dispersed fuel elements disclosed herein, a detailed explanation is provided below with examples.

[0078] In one example, the dynamic damage evolution method for dispersed fuel elements may include the following steps:

[0079] Step 1: Determine the geometric features and boundary conditions of the dispersed fuel element. The geometric features include the geometric shape, geometric dimensions, and spatial range of particle dispersion (referred to as fuel particles in this disclosure) of the numerical model of the fuel element (referred to as dispersion space range in this disclosure). The boundary conditions include the thermal conditions, mechanical conditions, and concentration conditions of the fuel element.

[0080] For example, determining the geometric characteristics and boundary conditions of dispersed fuel elements, such as Figure 2 The schematic diagram of the fuel element shown includes the following geometric features: the numerical model of the dispersion fuel element is a sphere, the geometric dimension is three-dimensional (which can be simplified to two-dimensional due to axisymmetry), the spatial range of particle dispersion is the internal dispersion region, and the defined boundary conditions include: the temperature boundary of the fuel element is 1200K, the mechanical condition is an unconstrained free condition, and the concentration condition is 0.

[0081] Step 2: Determine the geometric characteristics of the dispersed particles, whereby the geometric characteristics may include the geometric shape, geometric dimensions, and parameter distribution information of the numerical model of the dispersed particles.

[0082] For example, determining the geometric characteristics of dispersed particles, such as Figure 3The schematic diagram of the dispersed particles shown indicates that the defined geometric features include a sphere as the numerical model of the dispersed particles, a three-dimensional geometric dimension (which can be simplified to two-dimensional due to axisymmetry), the geometric parameters of each layer of the dispersed particles, and the distribution of the geometric parameters of each layer of the particles to satisfy a uniform distribution centered at (x,y,z).

[0083] Step 3: Determine the number of dispersed particles (referred to as the particle number in this disclosure) M and the spatial location (xi, yi, zi) of the dispersed particles within the fuel element (i = 1 to M), and write them into text file 1;

[0084] For example, determine the number of dispersed particles M (e.g., M is 10000) and the spatial location (xi, yi, zi) of the dispersed particles in the dispersed fuel element (i = 1 to 10000), and write them into text file 1;

[0085] Step 4: The control flow software (referred to as the flow engineering software in this disclosure) reads the text file 1 from Step 3 and creates an array P. Each dispersed particle is numbered with Ai (A1, A2, ..., Ai, ..., AM, i = 1 to M). The control flow software synchronously stores the spatial position (xi, yi, zi) of the dispersed particle Ai (i = 1 to M).

[0086] For example, the control flow software reads the text file 1 from step 3 and creates an array P. Each dispersed particle is numbered with Ai (A1, A2, ..., Ai, ..., AM, i = 1 to 10000). The control flow software synchronously stores the spatial position (xi, yi, zi) of the dispersed particle Ai (i = 1 to 10000).

[0087] Step 5: Based on Step 2 and Step 3, the control flow software sequentially generates corresponding parameters for the geometric features of each layer of the dispersed particles based on their geometric characteristics, so that all dispersed particles satisfy the parameter distribution indicated by the parameter distribution information of the dispersed particle geometric size in Step 2.

[0088] For example, based on steps 2 and 3, the control flow software randomly generates corresponding geometric parameters for each layer of material for each numbered dispersed particle based on the geometric characteristics of the dispersed particles. These parameters satisfy the geometric parameter distribution of each layer of material in step 2 (i.e., a uniform distribution centered on (x,y,z)).

[0089] Step 6: The control flow software calls the finite element software to construct an equivalent homogenization model of the dispersed fuel element based on the geometric features of the fuel element in Step 1 (referred to as the element geometric simulation model in this disclosure);

[0090] For example, the equivalent homogenization model of a dispersed fuel element can be a coupled irradiation-thermal-mechanical-diffusion model of a dispersed fuel element.

[0091] Step 7: The control flow software creates array Q, and calls the finite element software to determine the equivalent homogenization model dispersed particle points (referred to as simulation points in this disclosure) on the equivalent homogenization model of the dispersed fuel element, based on the spatial positions of the dispersed particles stored in array P. The finite element software then synchronizes the geometric features of the dispersed particles stored in array P to the corresponding equivalent homogenization model dispersed particle points, and sequentially numbers the equivalent homogenization model dispersed particle points according to ai (a1, a2, ..., ai, ..., aM, i = 1 to M). All equivalent homogenization model dispersed particle points are initialized by setting the label information of all equivalent homogenization model dispersed particle points to "not failed", the target concentration (e.g., including fission product concentration) to 0, and the target gas pressure (e.g., including fission gas pressure) to 0.

[0092] Step 8: The control flow software establishes a mapping relationship between the spatial position of dispersed particles Ai (i = 1 to M) and the dispersed particle points ai (i = 1 to M) in the equivalent homogenization model based on array P and array Q, and stores this mapping relationship in array S;

[0093] Step 9: The control flow software calls the finite element software to construct a particle coupling model of M particles (referred to as the particle geometry simulation model in this disclosure) based on the parameters of the geometric features of each layer of each dispersed particle generated in Step 5.

[0094] For example, the dispersed particle coupling model can be a dispersed particle fission product-irradiation-thermal-mechanical-diffusion coupling model.

[0095] For example, the control flow software calls the finite element software based on the parameters of the geometric features of each layer of each dispersed particle generated in step 5, and constructs a dispersed particle fission product-irradiation-thermal-mechanical-diffusion coupling model of 10,000 dispersed particles randomly determined in step 5 and satisfying uniform distribution.

[0096] Step 10: The control flow software calls the finite element software to call the equivalent homogenization model of the dispersed fuel element to perform coupled calculations of multiple first physical field variables at the current time step, obtain the distribution results of multiple first physical field variables at the current time step, and save the distribution results of multiple first physical field variables at the current time step to text file 2;

[0097] For example, the control flow software calls the finite element software to call the equivalent homogenized irradiation-thermal-mechanical-diffusion coupling model of the diffuse fuel element to perform coupling calculations of multiple first physical field variables at the current time step, obtain the distribution results of multiple first physical field variables at the current time step, and save the distribution results of multiple first physical field variables at the current time step to text file 2;

[0098] Step 11: The control flow software reads the distribution results of multiple first physical field variables in the text file 2 at the current time step, and extracts the values ​​of multiple first physical field variables at the corresponding spatial positions from the distribution results of multiple first physical field variables at the current time step based on the spatial position of any equivalent homogenization model dispersed particle point. The extracted values ​​of multiple first physical field variables are used as the first values ​​of multiple first physical field variables of the corresponding equivalent homogenization model dispersed particle point at the current time step, and are saved to array Q.

[0099] Step 12: The control flow software reads the first values ​​of multiple first physical field variables of each equivalent homogenized model dispersed particle point in array Q at the current time step, and calls the finite element software to set and save the boundary conditions of the dispersed particle coupling model of the corresponding dispersed particle based on the first values ​​of multiple first physical field variables of any equivalent homogenized model dispersed particle point at the current time step.

[0100] For example, the control flow software reads the first values ​​of multiple first physical field variables of each equivalent homogenized model dispersed particle point in array Q at the current time step, and calls the finite element software to set and save the boundary conditions of the dispersed particle fission product-irradiation-thermal-mechanical coupling model of the corresponding dispersed particle based on the first values ​​of multiple first physical field variables of any equivalent homogenized model dispersed particle point at the current time step.

[0101] Step 13: The control flow software calls the finite element software to call M dispersed particle coupling models to perform coupling calculations of multiple second physical variables at the current time step, obtain the distribution results of multiple second physical field variables at the current time step, and write the distribution results of multiple second physical field variables at the previous time step into text file 3;

[0102] For example, the control flow software calls the finite element software to call the coupling model of 10,000 dispersed particle fission products-irradiation-thermal-mechanical coupling to perform coupling calculations of multiple second physical variables at the current time step, obtain the distribution results of multiple second physical field variables at the current time step, and write the distribution results of multiple second physical field variables at the previous time step into text file 3.

[0103] Step 14: The control flow software reads the distribution results of multiple second physical field variables at the current time step from the text file 3, and extracts the values ​​of multiple second physical field variables at the corresponding spatial positions from the distribution results of multiple second physical field variables at the current time step based on the spatial position of any equivalent homogenization model dispersed particle point (or the spatial position of dispersed particles). The extracted values ​​of multiple second physical field variables are used as the second values ​​of multiple second physical field variables of the corresponding equivalent homogenization model dispersed particle point at the current time step, and are saved to array Q.

[0104] Step 15: Based on the calculation results of any dispersed particle simulation in array Q, i.e., the second values ​​of multiple second physical field variables of the dispersed particle point in the equivalent homogenization model corresponding to the dispersed particle at the current time step, the control flow software determines whether the dispersed particle coupling model of the dispersed particle has failed at the current time step. If the dispersed particle coupling model of the dispersed particle has failed, the control flow software updates the label information of the dispersed particle point in the equivalent homogenization model corresponding to the dispersed particle in array Q from "not failed" to "failed", and writes the concentration and pressure of the dispersed particle point in the equivalent homogenization model corresponding to the dispersed particle at the current time step into array Q. If the dispersed particle coupling model of the dispersed particle has not failed, the dispersed particle point in the equivalent homogenization model corresponding to the dispersed particle is still in the initial state, i.e., the label information of the dispersed particle point in the equivalent homogenization model corresponding to the dispersed particle is still "not failed" at the time of initialization, and the concentration and pressure are still 0.

[0105] For example, when the second physical field variable includes the stress intensity of the SiC layer, if the second value of the stress intensity of the SiC layer of the dispersed particle at the current time step is not less than the set intensity threshold, then the dispersed particle fission product-irradiation-thermal-mechanical coupling model of the dispersed particle is determined to be invalid; otherwise, the dispersed particle fission product-irradiation-thermal-mechanical coupling model of the dispersed particle is determined to be not invalid.

[0106] Step 16: The control flow software adds microcracks with random direction (or angle) and random size to the dispersed particles that have failed in the dispersed particle coupling model at the current time step according to the mapping relationship stored in array S, and writes the direction (angle) and size (size) parameters of the microcracks of the dispersed particles that have failed in the dispersed particle coupling model at the current time step into array S.

[0107] Step 17: The control flow software calls the finite element software to add the geometric features of the microcracks to the corresponding dispersed particle points in the equivalent homogenization model of the dispersed fuel element based on the direction (angle) and size (size) parameters of the microcracks of the dispersed particles that failed in the dispersed particle coupling model at the current time step, and saves them.

[0108] Step 18: In the next time step, the control flow software determines whether the set time step has been reached. If the set time step has not been reached, steps 10-17 are repeated. If the set time step has been reached, the control flow software calculation ends.

[0109] In summary, the dynamic damage evolution method for dispersed fuel elements disclosed herein effectively avoids the high computational cost problem caused by conducting three-dimensional refined direct simulation of dispersed fuel elements; it employs an equivalent homogenization strategy and establishes a precise mapping relationship between the spatial distribution of dispersed particles and the "simulation points" in the equivalent homogenization model of dispersed fuel elements, thereby achieving continuous coupled simulation of the dynamic damage evolution process; it helps to reduce the research time and accurately obtain the diffusion distribution of radionuclides after damage to dispersed fuel.

[0110] To achieve the above embodiments, this disclosure also proposes a dispersion-type fuel element dynamic damage evolution device.

[0111] Figure 6 This is a schematic diagram of the structure of a dispersion-type fuel element dynamic damage evolution device provided in an embodiment of this disclosure.

[0112] like Figure 6 As shown, the diffuse fuel element dynamic damage evolution device 60 includes: a construction module 61, a calling module 62, and a processing module 63.

[0113] The construction module 61 is used to construct the element geometry simulation model of the dispersed fuel element and the particle geometry simulation model of multiple fuel particles. In the element geometry simulation model, there are simulation points corresponding to the fuel particles, and the model state of the fuel particles is the non-failure state.

[0114] Module 62 is used to control the flow engineering software to call the component geometry simulation model and the particle geometry simulation model, and to determine the target fuel particle from multiple fuel particles whose particle geometry simulation model has failed based on the first simulation result of the particle geometry simulation model.

[0115] The processing module 63 is used by the control flow engineering software to add microcracks to the simulation points corresponding to the target fuel particles in the component geometric simulation model in order to complete the damage evolution process of the fuel element.

[0116] Furthermore, in one possible implementation of this embodiment, module 62 is invoked to: control the flow engineering software to perform multiple processing steps, wherein, in any one processing step, a first fuel particle for the current processing is determined from multiple fuel particles; a component geometry simulation model and a particle geometry simulation model of the first fuel particle for the current processing are invoked to obtain a first simulation result of the first fuel particle for the current processing; and based on the first simulation result of the first fuel particle for the current processing, it is determined whether the first fuel particle for the current processing is the target fuel particle corresponding to the current processing.

[0117] In one possible implementation of this embodiment, module 62 is used to: call the element geometry simulation model to perform a first coupling calculation of multiple first physical field variables at each simulation point, and obtain a first value of multiple first physical field variables at each simulation point after this processing; call the particle geometry simulation model of the first fuel particle being processed, and perform a second coupling calculation of multiple second physical field variables of the first fuel particle being processed based on the first value of multiple first physical field variables obtained in this processing at the simulation point corresponding to the first fuel particle being processed, and obtain a second value of multiple second physical field variables of the first fuel particle being processed after this processing; and determine the second value of multiple second physical field variables of the first fuel particle being processed after this processing as the first simulation result of the first fuel particle being processed.

[0118] In one possible implementation of this disclosure, the second physical field variable includes the stress intensity of the target layer in the corresponding fuel particle; the module 62 is used to: determine that the particle geometry simulation model of the first fuel particle in this processing is failed if the second value of the stress intensity of the target layer of the first fuel particle in this processing is not less than a set intensity threshold; and determine the first fuel particle in this processing as the target fuel particle corresponding to this processing.

[0119] In one possible implementation of this disclosure, module 62 is invoked to: for any fuel particle among a plurality of fuel particles, if the model state of the fuel particle is in an unfailed state, determine the fuel particle as the first fuel particle to be processed.

[0120] In one possible implementation of this disclosure, the processing module 63 is configured to: for any given processing step, the control flow engineering software adds microcracks to the simulation points in the element geometric simulation model corresponding to the target fuel particles in this processing step, so as to complete the damage evolution process of the fuel element in this processing step.

[0121] In one possible implementation of this disclosure, the dispersed fuel element dynamic damage evolution device 60 may further include:

[0122] The control module is used to control the flow engineering software to repeatedly execute the processing procedure until the set conditions are met if the set conditions are not met in any single processing step.

[0123] In one possible implementation of this disclosure, the dispersed fuel element dynamic damage evolution device 60 may further include:

[0124] The update module is used by the control flow engineering software to update the model state of the target fuel particle from a never-failed state to a failed state.

[0125] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and will not be repeated here.

[0126] The dynamic damage evolution device for dispersed fuel elements disclosed in this embodiment constructs a geometric simulation model of the dispersed fuel element and multiple particle geometric simulation models of fuel particles. Within the element geometric simulation model, there are simulation points corresponding to the fuel particles, and the model state of the fuel particles is an unfailed state. Control flow engineering software calls the element geometric simulation model and the particle geometric simulation model, and based on the first simulation result of the particle geometric simulation model, determines the target fuel particle whose particle geometric simulation model has failed from among the multiple fuel particles. The control flow engineering software adds microcracks to the simulation points corresponding to the target fuel particles in the element geometric simulation model to complete the damage evolution process of the fuel element. Therefore, by leveraging the synergistic effect of the element geometric simulation model and the particle geometric simulation model of the fuel particles, the failed particles are accurately located, and the dynamic damage evolution process is reconstructed using a microcrack dynamic addition mechanism. This not only provides a reliable basis for evaluating the full life-cycle performance of fuel elements and improves the accuracy and reliability of simulation analysis, but also effectively guides the structural optimization design of fuel elements, providing key technical support for improving the safety and reliability of nuclear energy systems.

[0127] To implement the above embodiments, this disclosure also proposes an electronic device, comprising:

[0128] At least one processor; and a memory communicatively connected to said at least one processor; wherein,

[0129] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the aforementioned method.

[0130] To implement the above embodiments, this disclosure also proposes a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the aforementioned methods.

[0131] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0132] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0133] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain.

[0134] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0135] It should be understood that various parts of this disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0136] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0137] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in the form of a hardware module or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0138] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A method for dynamic damage evolution of dispersed fuel elements, characterized in that, The method includes: A component geometric simulation model of a dispersed fuel element is constructed, and a particle geometric simulation model of multiple fuel particles is constructed; wherein, in the component geometric simulation model, there exists a simulation point corresponding to the fuel particle, and the model state of the fuel particle is a non-failure state; The control flow engineering software calls the component geometry simulation model and the particle geometry simulation model to determine the target fuel particle from the plurality of fuel particles whose particle geometry simulation model has failed, based on the first simulation result of the particle geometry simulation model. The flow engineering software is controlled to add microcracks to the simulation points corresponding to the target fuel particles in the geometric simulation model of the component, so as to complete the damage evolution process of the fuel element.

2. The method according to claim 1, characterized in that, The control flow engineering software calls the component geometry simulation model and the particle geometry simulation model to determine the target fuel particle from the plurality of fuel particles whose particle geometry simulation model has failed, based on the first simulation result of the particle geometry simulation model, including: The process of controlling the flow engineering software to perform multiple processes, wherein, in any one of the processes, the first fuel particle for this process is determined from the plurality of fuel particles; The component geometry simulation model and the particle geometry simulation model of the first fuel particle being processed are invoked to obtain the first simulation result of the first fuel particle being processed. Based on the first simulation result of the first fuel particle processed in this study, it is determined whether the first fuel particle processed in this study is the target fuel particle corresponding to this study.

3. The method according to claim 2, characterized in that, The process of calling the component geometry simulation model and the particle geometry simulation model of the first fuel particle being processed to obtain the first simulation result of the first fuel particle being processed includes: The component geometric simulation model is invoked to perform the first coupling calculation of multiple first physical field variables at each of the simulation points, so as to obtain the first value of multiple first physical field variables at each of the simulation points after this processing. The particle geometry simulation model of the first fuel particle being processed is invoked. Based on the first values ​​of multiple first physical field variables obtained in this processing at the simulation point corresponding to the first fuel particle being processed, a second coupling calculation of multiple second physical field variables of the first fuel particle being processed is performed to obtain the second values ​​of multiple second physical field variables of the first fuel particle being processed after this processing. The second values ​​of multiple second physical field variables of the first fuel particle after this processing are determined as the first simulation result of the first fuel particle after this processing.

4. The method according to claim 3, characterized in that, The second physical field variable includes the stress intensity of the target layer in the corresponding fuel particle; The step of determining whether the first fuel particle being processed is the target fuel particle for this processing based on the first simulation result of the first fuel particle being processed includes: If the second value of the stress intensity of the first fuel particle in the target layer after the current treatment is not less than the set intensity threshold, the particle geometry simulation model of the first fuel particle in the current treatment is determined to be invalid. The first fuel particle processed in this operation is identified as the target fuel particle for this operation.

5. The method according to claim 2, characterized in that, The step of determining the first fuel particle to be processed from the plurality of fuel particles includes: For any one of the plurality of fuel particles, if the model state of the fuel particle is not in a failed state, the fuel particle is determined as the first fuel particle in this process.

6. The method according to claim 2, characterized in that, The control flow engineering software adds microcracks to the simulation points corresponding to the target fuel particles in the component's geometric simulation model to complete the damage evolution process of the fuel element, including: During any given processing step, the flow engineering software is controlled to add microcracks to the simulation points in the component's geometric simulation model that correspond to the target fuel particles in this processing step, in order to complete the damage evolution process of the fuel element during this processing step.

7. The method according to claim 2, characterized in that, The method further includes: If any of the processing steps fails to meet the set conditions, the flow engineering software is controlled to repeat the processing steps until the set conditions are met.

8. The method according to any one of claims 1-7, characterized in that, The method further includes: The flow engineering software is controlled to update the model state of the target fuel particle from the non-failure state to the failure state.

9. A dynamic damage evolution device for a dispersed fuel element, characterized in that, The device includes: A construction module is used to construct a component geometric simulation model of a dispersed fuel element and a particle geometric simulation model of multiple fuel particles; wherein, in the component geometric simulation model, there are simulation points corresponding to the fuel particles, and the model state of the fuel particles is a non-failure state; The calling module is used to control the flow engineering software to call the component geometry simulation model and the particle geometry simulation model, so as to determine the target fuel particle whose particle geometry simulation model fails from the plurality of fuel particles based on the first simulation result of the particle geometry simulation model; The processing module is used to control the flow engineering software to add microcracks to the simulation points corresponding to the target fuel particles in the component geometric simulation model, so as to complete the damage evolution process of the fuel element.

10. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

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