Fuel cladding wear evaluation method and system

Abstract

The invention relates to a fuel cladding wear evaluation method and system, and the method comprises the steps: obtaining foreign matter attribute data, reactor core geometric data and fluid attribute data, and obtaining the motion track data, normal force and displacement amplitude of a foreign matter in a fluid environment corresponding to the fluid attribute data through simulation calculation; obtaining a fretting wear test carried out in a preset fretting mode based on the motion trail data to obtain wear characteristic data of the fuel cladding; and obtaining a fuel cladding wear result by using the wear characteristic data, the normal force and the displacement amplitude based on a preset model. According to the method, simulation calculation, fretting wear test and data analysis technologies are comprehensively applied, so that the wear condition of the fuel cladding is efficiently and accurately evaluated.

Description

Technical Field

[0001] The invention relates to the field of nuclear energy technology, and in particular to a fuel cladding wear evaluation method and system. Background Art

[0002] Fretting wear is usually caused by tiny foreign objects in the reactor, such as tiny wires and metal debris generated during construction, metal wires during maintenance, etc. Foreign objects entering the core may get stuck in the gap between the grid and the cladding, causing more serious fretting wear, aggravating the damage of the fuel assembly cladding, leading to increased nuclear radiation levels and the spread of radioactive contamination. Therefore, foreign objects entering the core pose a great threat to the safe and stable operation of nuclear power plants.

[0003] The high-speed flow of coolant in a nuclear reactor may carry tiny foreign objects, such as metal fragments or tool fragments left over during maintenance. When these foreign objects impact core components, such as fuel rods or control rods, at high speed, they may cause scratches, dents, or other forms of physical damage. Larger or harder foreign objects may cause more serious damage. These damages may pose a threat to the structural integrity of core components, especially in high-temperature and high-pressure environments, where these damages may accelerate and affect the safe operation of nuclear reactors. Long-term or repeated collisions will not only cause immediate physical damage, but also cause micro-motion wear on the surface and contact interfaces of core components. This wear is caused by tiny movements between foreign objects and the surface of components, especially when foreign objects are constantly washed by coolant. Long-term micro-motion may cause material fatigue, and damage will gradually accumulate, eventually affecting the structural integrity of the components. This wear may be microscopic and difficult to detect by conventional detection methods at an early stage. At the same time, it may also cause changes in the dimensions of key components, affecting their sealing and mechanical strength, and thus affecting the performance and safety of nuclear reactors. Summary of the invention

[0004] The technical problem to be solved by the present invention is that fuel cladding wear is difficult to be discovered by conventional detection methods at an early stage, and a fuel cladding wear evaluation method and system are provided.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a method for evaluating the wear of a fuel cladding, which is used for a core, wherein the core comprises a fuel rod having the fuel cladding and a grid for mounting the fuel rod, and the method comprises the following steps:

[0006] S1: Acquire foreign body property data, core geometry data and fluid property data, and obtain motion trajectory data, normal force and displacement amplitude of the foreign body in the fluid environment corresponding to the fluid property data through simulation calculation;

[0007] S2: obtaining a fretting wear test based on the motion trajectory data in a preset fretting mode to obtain wear characteristic data of the fuel cladding;

[0008] S3: Obtaining the fuel cladding wear result based on the preset model by using the wear characteristic data, the normal force and the displacement amplitude.

[0009] In one embodiment, the step S1 includes:

[0010] Establishing a core geometry model according to the core geometry data;

[0011] Performing flow field simulation according to the fluid property data and the core geometry model to obtain flow characteristic data of the fluid in the core area;

[0012] According to the fluid characteristic data and the foreign matter property data, combined with the core geometry model, through simulation calculation, the foreign matter motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data are obtained.

[0013] In one embodiment, performing flow field simulation according to the fluid property data and the core geometry model to obtain flow characteristic data of the fluid in the core region includes:

[0014] evaluating the complexity of the core geometry model and analyzing the flow characteristics of the fluid;

[0015] Selecting corresponding grid settings according to the complexity and the flow characteristics;

[0016] A preset solution algorithm and a preset turbulence model are used to perform flow field simulation to obtain flow characteristic data of the fluid in the core region.

[0017] In one embodiment, the foreign matter motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data are obtained through simulation calculation based on the fluid property data and the foreign matter property data in combination with the core geometric model, including:

[0018] The initial position and velocity parameters of the foreign body are obtained, and the Lagrangian method or discrete phase model is used to obtain the foreign body motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data through simulation calculation based on the fluid characteristic data and the foreign body property data in combination with the core geometry model.

[0019] In one embodiment, step S3 includes:

[0020] Establishing a multivariate regression model based on the normal force and the displacement amplitude;

[0021] The fuel cladding wear result is obtained through the wear characteristic data, the preset model and the multivariate regression model.

[0022] In one embodiment, the flow characteristic data includes fluid drag distribution;

[0023] The obtaining of the fuel cladding wear result by using the wear characteristic data, the preset model and the multivariate regression model comprises:

[0024] Determining the regional distribution and movement characteristics of the foreign matter moving in the gap between the fuel cladding and the grid based on the fluid drag distribution;

[0025] Determine a corresponding preset model based on the regional distribution and motion characteristics of the motion;

[0026] The fuel cladding wear result is obtained based on the corresponding preset model, the wear characteristic data and the multivariate regression model.

[0027] In one embodiment, the preset model corresponding to the regional distribution and motion characteristics of the motion is determined to include:

[0028] Based on the regional distribution and movement characteristics of the foreign matter moving in the gap, determining that the foreign matter exhibits sliding fretting wear or impact sliding fretting wear;

[0029] If it is the sliding fretting wear, the Archard model is used for prediction; if it is the impact sliding fretting wear, the Frick model is used for prediction.

[0030] In one embodiment, the foreign object attribute data includes foreign object type, foreign object shape, foreign object size and foreign object material.

[0031] In one embodiment, the fluid property data includes fluid temperature and fluid flow rate.

[0032] The present application also provides a fuel cladding wear evaluation system, comprising a processor and a memory storing a computer program, wherein the processor implements the steps of any of the above-mentioned fuel cladding wear evaluation methods when executing the computer program.

[0033] The implementation of the present invention has the following beneficial effects: The present invention relates to a method and system for evaluating the wear of a fuel cladding, wherein the steps of the method include obtaining foreign matter attribute data, core geometry data and fluid attribute data, obtaining the motion trajectory data, normal force and displacement amplitude of the foreign matter in the fluid environment corresponding to the fluid attribute data through simulation calculation; obtaining the wear characteristic data of the fuel cladding by performing a micromotion wear test in a preset micromotion mode based on the motion trajectory data; obtaining the wear characteristic data, the normal force and the displacement amplitude based on a preset model to obtain the wear result of the fuel cladding. The present invention realizes efficient and accurate evaluation of the wear of the fuel cladding by comprehensively using simulation calculation, micromotion wear test and data analysis technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0035] Figure 1 It is a schematic flow chart of the fuel cladding wear evaluation method of the present invention;

[0036] Figure 2 The geometric model of the reactor rod bundle area of ​​the present invention;

[0037] Figure 3 This is a schematic diagram of the boundary conditions of a 5×5 rod bundle channel of the present invention;

[0038] Figure 4 Schematic diagram of the position of foreign matter at the entrance of the rod bundle area of ​​the present invention;

[0039] Figure 5a The present invention is a rod bundle channel streamline distribution diagram;

[0040] Figure 5b It is a velocity distribution cloud diagram of the rod bundle channel of the present invention;

[0041] Figure 6 This is a schematic diagram of the absolute translation speed when the foreign body is 2mm*10mm in size;

[0042] Figure 7 This is a schematic diagram of the absolute translation speed when the foreign body is 2mm*5mm in size;

[0043] Figure 8 This is a schematic diagram of the absolute translation speed when the foreign body is 1mm*30mm in size;

[0044] Fig. 9This is a schematic diagram of the absolute translation speed when the foreign body is 1mm*10mm in size;

[0045] Fig.10 This is a schematic diagram of the absolute translation speed when the foreign body is 1mm*5mm in size;

[0046] Fig.11 The present invention is a schematic diagram of the absolute translation speed when the foreign body is 1mm*2mm;

[0047] Fig.12 It is a schematic diagram of foreign body movement data of the present invention;

[0048] Fig.13 This is a schematic diagram of the angular velocity of the foreign body rotation of the present invention;

[0049] Fig.14 It is a schematic diagram of the micro-motion of the foreign body wire and the cladding tube of the present invention;

[0050] Fig.15 This is the micro-motion characteristic curve of the present invention under the experimental condition that the normal load is 50N and the tangential displacement amplitude is 50μm;

[0051] Fig.16 It is a schematic diagram of the friction coefficient of sliding wear under a normal load of 50N of the present invention;

[0052] Fig.17 It is a cross-sectional diagram of the wear scar of sliding wear under a normal load of 50N of the present invention;

[0053] Fig.18 It is a cross-sectional view of the sliding wear scar under a normal load of 100N according to the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Aiming at the technical problem existing in the background technology: fuel cladding wear is difficult to be accurately detected by conventional detection methods at an early stage. The present invention provides a fuel cladding wear evaluation method and system, which solves the problem of fuel cladding wear being difficult to accurately evaluate and provide early warning by comprehensively using simulation calculation, micro-motion wear test and data analysis technology.

[0056] like Figure 1As shown, the technical solution of the present application provides a method for evaluating the wear of a fuel cladding, which is used for a core, and the core includes a fuel rod having a fuel cladding and a grid for mounting the fuel rod. The steps of the method include:

[0057] S1: Obtain foreign body property data, core geometry data and fluid property data, and obtain the motion trajectory data, normal force and displacement amplitude of the foreign body in the fluid environment corresponding to the fluid property data through simulation calculation;

[0058] S2: obtaining a fretting wear test based on the motion trajectory data in a preset fretting mode to obtain wear characteristic data of the fuel cladding;

[0059] S3: The wear characteristic data, normal force and displacement amplitude are used to obtain the fuel cladding wear results based on the preset model.

[0060] Specifically: First, by collecting foreign body property data, core geometry data and fluid property data, using simulation computing technology, based on discrete phase model (DPM), the motion trajectory, normal force and displacement amplitude of foreign bodies in fluid environment are accurately simulated. This step deeply analyzes the specific influence of various factors such as flow field characteristics and foreign body size on the motion trajectory and landing point distribution of foreign bodies; secondly, according to the motion trajectory data obtained by simulation, micro-motion wear test is carried out in the preset micro-motion mode to obtain the wear characteristic data of fuel cladding; finally, combined with the wear characteristic data, normal force and displacement amplitude, the wear results of fuel cladding are obtained by comprehensive evaluation using the preset model. During the implementation process, tests under different flow conditions were also implemented, and high-speed camera technology was used to capture the moment of interaction between foreign bodies and cladding, including key parameters such as impact angle and velocity change, and the motion trajectory and landing point distribution of foreign bodies were tracked, and a detailed database was established. The database records the size of foreign bodies stuck in the gap between the grid and the outer wall of the fuel cladding under different fluid flow conditions and their interaction behavior with the cladding, providing data support for the evaluation of fuel cladding wear.

[0061] Further, the foreign body property data includes the foreign body type, foreign body shape, foreign body size and foreign body material. The fluid property data includes the fluid temperature and fluid flow rate.

[0062] Furthermore, foreign body property data, core geometry data and fluid property data are obtained, and motion trajectory data, normal force and displacement amplitude of the foreign body in the fluid environment corresponding to the fluid property data are obtained through simulation calculation, including: establishing a core geometry model according to the core geometry data; performing flow field simulation according to the fluid property data and the core geometry model to obtain flow characteristic data of the fluid in the core area; obtaining motion trajectory data, normal force and displacement amplitude of the foreign body in the fluid environment corresponding to the fluid property data through simulation calculation according to the fluid characteristic data and the foreign body property data in combination with the core geometry model.

[0063] like Figure 2 , Figure 3 and Figure 4 As shown, Figure 2 is the geometric model of the reactor bundle area, Figure 3 Schematic diagram of the boundary conditions of a 5×5 rod bundle channel. Figure 4 The figure is a schematic diagram of the location of foreign matter at the entrance of the rod bundle area. Specifically, first of all, the collection of foreign matter attribute data covers the type of foreign matter (such as filamentary cylinders), the shape and size of foreign matter (including cylinders with diameters of 2mm and 1mm, and lengths of 10mm, 5mm, 30mm, and 2mm respectively), and the material of foreign matter (such as stainless steel). At the same time, the fluid attribute data includes key information such as fluid temperature (such as 292.4℃) and fluid flow rate (such as 4m / s). In the implementation of the evaluation method, firstly, based on the core geometry data, the core geometry model is accurately constructed using professional modeling software. The model reflects the structural characteristics of the core in detail, covering the precise arrangement and size of fuel rods, grids (including positioning grids and stirring grids) and other related components. Subsequently, based on the fluid attribute data and the established core geometry model, the fluid dynamics simulation software is used to perform in-depth flow field simulation, aiming to obtain detailed flow characteristic data of the fluid in the core area, such as velocity distribution, pressure distribution and vortex characteristics, which are crucial for in-depth understanding of fluid behavior and prediction of foreign matter movement trajectory. Next, combining the fluid characteristic data, foreign body property data and core geometry model, the motion trajectory data, normal force and displacement amplitude of the foreign body in a specific fluid environment are accurately obtained through simulation calculation. In this embodiment, the fluid medium is defined as the working conditions of temperature 292.4°C, pressure 15.5MPa and flow rate 4m / s. These key parameters are not only the core basis for the subsequent micro-motion wear test design, but also the indispensable input data for building a wear prediction model.

[0064] The main parameters are shown in Table 1:

[0065]

[0066] Table 1

[0067] Furthermore, flow field simulation is performed based on the fluid property data and the core geometry model to obtain the flow characteristic data of the fluid in the core area, including: evaluating the complexity of the core geometry model and analyzing the flow characteristics of the fluid; selecting corresponding grid settings based on the complexity and flow characteristics; using a preset solution algorithm and a preset turbulence model to perform flow field simulation to obtain the flow characteristic data of the fluid in the core area.

[0068] Specifically, first, a comprehensive evaluation of the complexity of the reactor core geometry model and the flow characteristics of the fluid was conducted. This step is crucial for selecting appropriate grid settings and solution algorithms, aiming to balance the accuracy of the simulation with computational efficiency. Based on the above evaluation results, the grid type and division method were selected according to the complexity of the core geometry model and the specific requirements of the fluid flow characteristics. Specifically, in the middle area of ​​the core, especially the part with the spacer grid and the slurry grid, a tetrahedral unstructured grid was used to adapt to the complex geometry of these areas; while at both ends of the core, a structured grid was used to improve computational efficiency. The two types of grids are connected through an interface to ensure the smoothness of the entire flow domain. In order to capture the flow details and the movement of foreign particles, the grid density was increased in key areas (such as the spacer grid and the slurry grid). This measure significantly improved the resolution of the flow field simulation, enabling more accurate acquisition of the flow characteristics data of the fluid in the core area, including key information such as velocity distribution, pressure distribution, and vortex structure.

[0069] Furthermore, according to the fluid characteristic data and the foreign body property data, combined with the core geometry model, through simulation calculation, the foreign body motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data are obtained, including: obtaining the initial position and velocity parameters of the foreign body setting, using the Lagrangian method or discrete phase model, according to the fluid characteristic data and the foreign body property data, combined with the core geometry model, through simulation calculation, the foreign body motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data.

[0070] Specifically, the initial position and velocity parameters of the foreign matter were set before the simulation calculation. These parameters were set according to the type of foreign matter and the flow conditions to ensure that the simulation results can truly reflect the actual situation. During the simulation calculation, the Lagrangian method or discrete phase model (DPM) was used to simulate the movement of foreign matter in the fluid in combination with fluid characteristic data, foreign matter property data and core geometry model. Specifically, appropriate boundary conditions and initial conditions were set, such as the velocity inlet was 4m / s and the pressure outlet was 15.5MPa. The boundary conditions are shown in Table 2:

[0071]

[0072]

[0073] Table 2

[0074] The wall is a no-slip wall, and the foreign body enters the rod bundle area at a random angle. By solving the fluid dynamics equations, the velocity and pressure distribution in the flow field are obtained, and on this basis, the motion simulation of the foreign body is introduced. In the simulation process, the force conditions of the foreign body are fully considered, including gravity, fluid drag, collision force, etc., and the motion trajectory, velocity change, normal force and displacement amplitude of the foreign body are calculated. In order to display the simulation results more intuitively, data visualization tools or software are used to visualize the flow field and foreign body trajectory, such as Figure 5a and Figure 5b As shown, Figure 5a is the streamline diagram of the rod bundle fluid domain, Figure 5b The velocity distribution cloud map of the rod bundle channel includes the streamline distribution map, the velocity distribution cloud map of the rod bundle channel, the velocity distribution cloud map of the rod bundle cross section, and the motion trajectory map of the foreign matter. By analyzing these key parameters, the following conclusions were drawn: the motion speed of the foreign matter will vary at different positions; the motion trajectory of the foreign matter will be blocked and affected by the grid; the deposition position and distribution range of the foreign matter will also vary depending on the size and shape. For example, when the foreign matter diameter is 2mm, Figure 6 , Figure 7 As shown, Figure 6 This is a schematic diagram of the absolute translation speed when the foreign body is 2mm*10mm. Figure 7 The diagram is a schematic diagram of the absolute translation speed when the foreign body is 2mm*5mm. When the diameter of the foreign body is 2mm, it will be blocked by the grid regardless of its length. When the diameter of the foreign body is reduced to 1mm, Figure 8 , Fig. 9 , Fig.10 , Fig.11 As shown, Figure 8 This is a schematic diagram of the absolute translation speed when the foreign body is 1mm*30mm. Fig. 9 This is a schematic diagram of the absolute translation speed when the foreign body is 1mm*10mm. Fig.10 This is a schematic diagram of the absolute translation speed when the foreign body is 1mm*5mm. Fig.11 This is a schematic diagram of the absolute translation speed when the foreign object is 1mm*2mm.

[0075] When the foreign body is 1mm in diameter, whether it will be blocked by the grid is significantly affected by the length of the foreign body. In addition, it was found that when the foreign body size is 2mm*10mm, it will be blocked at the first spacer grid, while the foreign body size of 2mm*5mm can pass through the first spacer grid and the mixing grid smoothly, but will be blocked at the second spacer grid. Figure 6 , Figure 7 and Figure 8It can be found that when the diameter of the foreign bodies is 2 mm, no matter what their length is, these foreign bodies will be blocked by the grid and cannot continue to move upward. However, when the diameter of the foreign bodies is reduced to 1 mm, whether the foreign bodies will be blocked by the grid is significantly affected by the length of the foreign bodies. Specifically, when the length of the foreign bodies is less than 5 mm, they can pass through the grid area and continue to move upward. It is worth noting that when the size of the foreign body is 2 mm*10 mm, it will be blocked at the first spacer grid. This blocking is due to the large length of the foreign body. After colliding with the grid, it will be directly stuck on the steel protrusion or spring sheet. However, for foreign bodies with a size of 2 mm*5 mm, the situation is different. Such foreign bodies can smoothly pass through the first spacer grid and the mixing grid, but will be blocked at the second spacer grid. This is because after passing through the first spacer grid, the foreign body is affected by the collision and the lateral flow, and begins to rotate, thereby being stuck at the second spacer grid.

[0076] The color of the trajectory in the figure represents the speed of the foreign body. Fig.12 and Fig.13 As shown, Fig.12 is the foreign body movement data, Fig.13 In summary, by adopting the Lagrangian method or discrete phase model, combined with fluid property data, foreign body property data and core geometry model, the motion trajectory data, normal force and displacement amplitude of foreign bodies in the fluid environment corresponding to the fluid property data are successfully obtained. These data provide important basis for the subsequent fretting wear test design and wear prediction model input.

[0077] For step S2: In the S2 stage, based on the foreign body motion trajectory data obtained by simulation calculation, a micro-motion wear test is designed to obtain the wear characteristic data of the fuel cladding.

[0078] As shown in 14, Fig.14The figure is a schematic diagram of the micro-motion of the foreign body wire and the cladding tube, in which the direction of water movement between the substrate and the cladding tube is the impact direction, and the vertical direction between the substrate and the cladding tube is the sliding direction. Specifically, in order to carry out these experiments, a foreign body micro-motion wear device is specially designed. The device includes four parts: a test bench, a control cabinet, a preheating device, and a water chemical circulation device. Among them, the test bench includes a matrix 10 to simulate a grid, a foreign body wire 20 to simulate a foreign body, and a cladding tube 30 to simulate a fuel cladding. The foreign body micro-motion wear device can simulate three micro-motion modes of wear experiments under high temperature, high pressure, and boric acid water environment. During the experiment, all parameters are precisely controlled and recorded by the computer of the control cabinet to ensure the accuracy and reliability of the experimental data. The experimental conditions for the micro-motion wear test are that the solution contains 1500ppm (mass) boric acid and 2.3ppm (mass) lithium hydroxide, the experimental temperature is set to 311°C, and the pressure is maintained at 15.5MPa. The experiment mainly focuses on the influence of tangential displacement amplitude (50μm, 75μm, 100μm), normal load (25N, 50N, 75N, 100N), foreign body type (316L stainless steel) and foreign body wire size (diameter 1mm, 2mm, 5mm) on the wear law of zirconium alloy fuel cladding tube under three micro-motion modes: sliding wear, impact wear and impact sliding wear.

[0079] In the sliding wear experiment, a sinusoidal loading tangential displacement was used, the frequency was fixed at 20Hz, and the normal load was kept constant. The wear volume, macromorphology, and micromorphology of the cladding tube surface after the experiment were analyzed in detail using a Bruker white light interferometer and an emission scanning electron microscope. In particular, when analyzing the sliding wear of a 2mm diameter 316L stainless steel foreign body wire under different conditions, several representative cycles (such as the 2400th, 36000th, 90000th, and 198000th) were selected to draw the micro-motion characteristic curve, and the change process of the friction coefficient from the initial unstable state to the stable state was observed.

[0080] like Fig.15 , Fig.16 , Fig.17 and Fig.18 As shown, Fig.15 This is the micro-motion characteristic curve under the experimental conditions of 50μm-50N. Fig.16 Schematic diagram of friction coefficient of sliding wear with normal load 50N. Fig.17 This is the cross-sectional diagram of the sliding wear scar with a normal load of 50N. Fig.18This is a cross-sectional view of the wear scar caused by sliding wear with a normal load of 100N. In addition, the wear scar was analyzed in 3D using Vision64 post-processing software. It was found that with the increase in displacement amplitude, the wear depth showed an overall increasing trend, and the accumulation of wear debris became more and more obvious. Under specific experimental conditions (such as 50μm-50N and 75μm-50N), discontinuous discontinuities appeared in the wear scar cross section, which may indicate that a specific wear mechanism is at work.

[0081] In terms of experimental parts, the size and performance of the fuel cladding tube used in this foreign body micro-wear device meet the experimental requirements. At the same time, in order to facilitate the installation and removal of the foreign body wire, a special experimental part matrix is ​​designed, and the foreign body wire and the matrix are designed as one to ensure the smooth progress of the experiment.

[0082] Further, step S3 includes: establishing a multivariate regression model according to the normal force and the displacement amplitude;

[0083] The fuel cladding wear results are obtained through wear characteristic data, preset models and multivariate regression models.

[0084] Specifically, first, in order to establish a multivariate regression model, wear test data under different normal forces and displacement amplitudes were collected. Using professional statistical software, a multivariate linear regression analysis was performed on these data to determine the linear relationship between the wear coefficient K and the normal force F and the displacement amplitude D. The final result of this process is a multivariate linear regression model for the wear coefficient K. Next, this multivariate regression model and the wear characteristic data obtained from the experiment (such as wear volume, wear depth, etc.) and preset model parameters (such as the initial wear coefficient in the Archard model, etc.) are used to calculate the wear results of the fuel cladding. The specific approach is to substitute the experimental data, model parameters and multivariate regression model into the Archard wear formula, and calculate the wear coefficient K under the current normal force and displacement amplitude, and then obtain the wear results of the fuel cladding. The mathematical expression of the multivariate linear regression model is:

[0085] K=3.613-2.251E-17F-6.611E-18D;

[0086] Where: F is the normal load; D is the displacement amplitude; K is the wear coefficient. This model is constructed based on the test data of fretting wear between foreign matter and fuel cladding under different working conditions. The calculated values ​​of this model basically fall within the error band of ±25%, and the model prediction results are in good agreement with the test results.

[0087] In actual operation, a data collection and processing program, a multivariate linear regression analysis program, and a wear calculation program were written to automate this process. The data collection and processing program is responsible for cleaning and organizing the experimental data to provide accurate and reliable data support for regression analysis; the multivariate linear regression analysis program uses statistical software to perform regression analysis on the data to obtain a multivariate linear regression model of the wear coefficient K; finally, the wear calculation program substitutes the experimental data, model parameters, and multivariate regression model into the formula for calculation to obtain the wear results of the fuel cladding.

[0088] Among them, Archard wear formula is:

[0089] V=(3.613-2.251E-17F-6.611E-18D)F×D×4n

[0090] Where V is the wear volume, n is the number of cycles, F is the normal load, D is the displacement amplitude, and K is the wear coefficient.

[0091] Furthermore, the flow characteristic data includes fluid drag distribution; the fuel cladding wear results obtained through the wear characteristic data, the preset model and the multivariate regression model include: determining the regional distribution and movement characteristics of the foreign matter moving in the gap between the fuel cladding and the frame based on the fluid drag distribution; determining the corresponding preset model based on the regional distribution and movement characteristics of the movement; and obtaining the fuel cladding wear results based on the corresponding preset model, the wear characteristic data and the multivariate regression model.

[0092] Specifically, firstly, the flow field in the reactor is studied in depth through three-dimensional numerical simulation analysis or experimental measurement to obtain detailed fluid drag distribution. This distribution information is crucial for determining the motion trajectory, speed and other characteristics of foreign matter in the gap between the fuel cladding and the grid. Based on the magnitude and direction of the fluid drag, the motion area distribution and motion characteristics of foreign matter in the gap can be accurately depicted.

[0093] Next, according to the motion characteristics and distribution area of ​​the foreign body, select the appropriate preset wear model for prediction. If the motion of the foreign body is manifested as sliding fretting wear, select the corresponding sliding fretting wear model; if it is manifested as impact sliding fretting wear, select the impact sliding fretting wear model. This step ensures the accuracy of wear prediction. The wear characteristic data obtained from the experiment, the preset model parameters, and the previously established multivariate regression model are substituted into the selected wear model for calculation. This process is automated by writing programs, including the fluid drag distribution calculation program and the motion characteristic judgment program.

[0094] Further, determining the corresponding preset model based on the regional distribution and motion characteristics of the motion includes: determining that the foreign matter exhibits sliding fretting wear or impact sliding fretting wear based on the regional distribution and motion characteristics of the foreign matter moving in the gap;

[0095] If it is sliding fretting wear, the Archard model is used for prediction; if it is impact sliding fretting wear, the Frick model is used for prediction.

[0096] The preset models corresponding to the regional distribution of motion and the motion characteristics include:

[0097] First, based on the regional distribution and movement characteristics of the foreign body in the gap, determine whether the foreign body exhibits sliding fretting wear or impact sliding fretting wear. This can be obtained by analyzing and judging the motion trajectory, speed, acceleration and other characteristics of the foreign body. If it is sliding fretting wear, the Archard model is used for prediction. The wear characteristic data obtained from the experiment, the preset Archard model parameters and the multivariate regression model are substituted into the Archard wear formula to calculate the wear results of the fuel cladding.

[0098] If it is impact sliding fretting wear, the Frick model is used for prediction. Similarly, the wear characteristic data obtained from the experiment, the preset Frick model parameters and the multivariate regression model are substituted into the Frick wear formula to calculate the wear results of the fuel cladding.

[0099] The actual application process of the fuel cladding wear evaluation method includes: at the beginning of the calculation, the initial state parameters are first input, including foreign body size, foreign body movement speed, flow field characteristics, etc., to determine the distribution and movement characteristics of foreign bodies in the fuel assembly area. Then, the corresponding calculation model is called according to the foreign body movement characteristics and distribution, such as the Archard model for sliding micro-wear. Finally, the calculated damage results (wear volume and wear depth) are output.

[0100] The present application also provides a fuel cladding wear evaluation system, comprising a processor and a memory storing a computer program, wherein the processor implements the steps of any of the above-mentioned fuel cladding wear evaluation methods when executing the computer program.

[0101] This application uses the simulation technology of the flow field in the core, the wear experimental data of foreign matter and the outer wall of the fuel cladding, and establishes an accurate prediction model for the wear of foreign matter and the outer wall of the fuel cladding. We can quickly and accurately evaluate the wear degree of the fuel cladding. This evaluation result provides a very valuable reference for the safety performance analysis and optimization design of the fuel assembly, which helps to ensure the safe and stable operation of the nuclear reactor.

[0102] It can be understood that the above embodiments only express the preferred implementation modes of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the patent scope of the present invention. It should be pointed out that, for ordinary technicians in this field, the above technical features can be freely combined without departing from the concept of the present invention, and several deformations and improvements can be made, which all belong to the protection scope of the present invention. Therefore, all equivalent changes and modifications made to the scope of the claims of the present invention should belong to the coverage of the claims of the present invention.

Claims

1. A method for evaluating the wear of a fuel cladding, used in a core, wherein the core comprises a fuel rod having the fuel cladding and a grid for mounting the fuel rod, characterized in that: The method comprises the following steps: S1: Acquire foreign body property data, core geometry data and fluid property data, and obtain motion trajectory data, normal force and displacement amplitude of the foreign body in the fluid environment corresponding to the fluid property data through simulation calculation; S2: obtaining a fretting wear test based on the motion trajectory data in a preset fretting mode to obtain wear characteristic data of the fuel cladding; S3: Obtaining the fuel cladding wear result based on the preset model by using the wear characteristic data, the normal force and the displacement amplitude.

2. The fuel cladding wear evaluation method according to claim 1, characterized in that: The step S1 includes Establishing a core geometry model according to the core geometry data; Performing flow field simulation according to the fluid property data and the core geometry model to obtain flow characteristic data of the fluid in the core area; According to the fluid characteristic data and the foreign matter property data, combined with the core geometry model, through simulation calculation, the foreign matter motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data are obtained.

3. The fuel cladding wear evaluation method according to claim 2, characterized in that: The performing of flow field simulation according to the fluid property data and the core geometry model to obtain flow characteristic data of the fluid in the core region includes: evaluating the complexity of the core geometry model and analyzing the flow characteristics of the fluid; Selecting corresponding grid settings according to the complexity and the flow characteristics; A preset solution algorithm and a preset turbulence model are used to perform flow field simulation to obtain flow characteristic data of the fluid in the core region.

4. The fuel cladding wear evaluation method according to claim 2, characterized in that: The foreign body motion trajectory data, normal force and displacement amplitude under the fluid environment corresponding to the fluid property data are obtained by simulation calculation based on the fluid property data and the foreign body property data in combination with the core geometry model, including: The initial position and velocity parameters of the foreign body are obtained, and the Lagrangian method or discrete phase model is used to obtain the foreign body motion trajectory data, normal force and displacement amplitude in the fluid environment corresponding to the fluid property data through simulation calculation based on the fluid characteristic data and the foreign body property data in combination with the core geometry model.

5. The fuel cladding wear evaluation method according to claim 2, characterized in that: The step S3 comprises: Establishing a multivariate regression model based on the normal force and the displacement amplitude; The fuel cladding wear result is obtained through the wear characteristic data, the preset model and the multivariate regression model.

6. The fuel cladding wear evaluation method according to claim 5, characterized in that: The flow characteristic data includes fluid drag distribution; The obtaining of the fuel cladding wear result by using the wear characteristic data, the preset model and the multivariate regression model comprises: Determining the regional distribution and movement characteristics of the foreign matter moving in the gap between the fuel cladding and the grid based on the fluid drag distribution; Determine a corresponding preset model based on the regional distribution and motion characteristics of the motion; The fuel cladding wear result is obtained based on the corresponding preset model, the wear characteristic data and the multivariate regression model.

7. The fuel cladding wear evaluation method according to claim 6, characterized in that: The preset model corresponding to the regional distribution and motion characteristics of the motion includes: Based on the regional distribution and movement characteristics of the foreign matter moving in the gap, determining that the foreign matter exhibits sliding fretting wear or impact sliding fretting wear; If it is the sliding fretting wear, the Archard model is used for prediction; if it is the impact sliding fretting wear, the Frick model is used for prediction.

8. The fuel cladding wear evaluation method according to claim 2, characterized in that: The foreign object attribute data includes foreign object type, foreign object shape, foreign object size and foreign object material.

9. The fuel cladding wear evaluation method according to claim 1, characterized in that: The fluid property data includes fluid temperature and fluid flow rate.

10. A fuel cladding wear evaluation system, characterized in that: The method comprises a processor and a memory storing a computer program, wherein the processor implements the steps of the fuel cladding wear evaluation method according to any one of claims 1 to 9 when executing the computer program.

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