Method for simulating pressurized water reactor oxide corrosion product cross-scale nuclear-thermal-material coupling

Abstract

A multi-scale nuclear-thermal-material coupled simulation method for pressurized water reactor (PWR) oxidation corrosion products is proposed. In the first stage, neutronics and thermal-hydraulic models are used for iterative simulation to determine the supercooled boiling location. In the second stage, a multiphysics coupled simulation is performed using an oxidation corrosion product (CRUD) model, a neutronics model, and a thermal-hydraulic model to obtain a high-resolution simulation under PWR nuclear-thermal-material coupled conditions. This invention considers scenarios where the thickness of oxidation corrosion products ranges from 20 micrometers to 200 micrometers, and the calculation and analysis of multiphysics fields such as neutron physics, flow heat transfer, and oxidation corrosion product deposition in PWRs can more accurately capture complex physical processes.

Description

Technical Field

[0001] This invention relates to a technology in the field of reactor materials, specifically a cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products. Background Technology

[0002] During long-term operation of pressurized water reactors, supercooled boiling occurs in some reactor fuel rods, leading to the deposition of oxidative corrosion products (CRUD) on the outer surface of the fuel rods. Their porous structure exacerbates internal boiling, causing boron in the coolant to accumulate within the corrosion products. Because boron has a high neutron absorption cross-section, this results in localized neutron flux and power suppression, subsequently causing axial fission power shifts in the reactor, posing a threat to reactor operational safety. Existing multiphysics coupling techniques for reactor cores neglect cross-scale modeling physics calculations and the supercooled boiling situation in the physical fields when performing high-resolution modeling of corrosion products, thus failing to reflect the true physical conditions. Summary of the Invention

[0003] This invention addresses the shortcomings of existing technologies, which are limited to fixed heat flux densities or corrosion product deposition feedback of individual fuel rods. These technologies fail to analyze in detail the differences in power distribution within fuel assemblies and their impact on corrosion product deposition and axial power shift, and also fail to consider the influence of corrosion products on changes in thermal conductivity and the overall physical field. This invention proposes a cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products. Considering scenarios where the thickness of oxidation corrosion products ranges from 20 micrometers to 200 micrometers, the calculation and analysis of multiple physical fields such as neutron physics, flow heat transfer, and oxidation corrosion product deposition in pressurized water reactors can more accurately capture complex physical processes.

[0004] This invention is achieved through the following technical solution:

[0005] This invention relates to a cross-scale nuclear-thermal-material coupling simulation method for oxidative corrosion products of pressurized water reactors. In the first stage, the supercooled boiling position is obtained by iterative simulation of neutronics model and thermal-hydraulic model. In the second stage, multiphysics coupling simulation is performed by oxidative corrosion products (CRUD) model, neutronics model and thermal-hydraulic model to obtain high-resolution simulation under nuclear-thermal-material coupling conditions of pressurized water reactor.

[0006] The multiphysics coupling simulation refers to: keeping the supercooled boiling condition unchanged, calculating the temperature, density and thermal conductivity of the CRUD region through the oxidation corrosion products (CRUD) model, and continuing the iterative process, that is: the thermal-hydraulic model calculates based on the temperature, density and thermal conductivity output by the CRUD model, and the neutronics model updates its database based on the temperature and density results of the thermal-hydraulic model and the CRUD model for calculation.

[0007] Technical effect

[0008] This invention comprehensively considers the impact of oxidative corrosion product deposition on the multiphysics field of pressurized water reactors and the possible changes in the initiation of supercooled boiling during the iteration process. Based on a high-resolution deterministic method and an adaptive iteration strategy, it ensures the stability of the solution to complex problems. Compared with existing technologies, it significantly improves computational efficiency while maintaining high resolution and high reliability. In particular, when modeling oxidative corrosion products (CRUD), this invention can more accurately represent the micron-scale characteristics of CRUD, avoiding the instability of numerical simulation results caused by the uncertainty of probability theory in Monte Carlo methods, while improving computational efficiency. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of a CRUD virtual mesh.

[0010] Figure 2 This is a schematic diagram of the system of the present invention;

[0011] Figure 3 This is a flowchart of the iterative loop of the method of the present invention;

[0012] Figure 4 (a) shows the arrangement of the fuel assembly; (b) shows the grid of the guide tube; (c) shows the schematic diagram of the grid of the fuel rod.

[0013] Figure 5 A schematic diagram comparing the relative axial power of components before and after CRUD is provided for this embodiment;

[0014] Figure 6 This is a schematic diagram of the relative power distribution of the fuel assembly in an embodiment.

[0015] Figure 7 This is a schematic diagram of the boron nucleus density distribution of the fuel assembly in an embodiment.

[0016] Figure 8 This is a schematic diagram illustrating the effect of the example;

[0017] Figure 9 This is a schematic diagram of a CRUD model. Detailed Implementation

[0018] like Figure 2As shown in this embodiment, a multi-scale nuclear-thermal-material coupling system for pressurized water reactor oxidation corrosion products is included. This system comprises a neutron calculation module, a thermal calculation module, a corrosion product calculation module, and a data exchange module. Specifically, the neutron calculation module uses a variational segmented block method to solve the neutron transport equation, obtaining the neutron flux distribution and power distribution. The thermal calculation module uses a coupling of the parallel channel equation and the fuel heat conduction equation to solve the temperature field, obtaining the temperature of the material in each region. The corrosion product calculation module solves the growth equation and the chemical composition equation, obtaining the thickness of the corrosion products and their internal chemical composition. The data exchange module exchanges and processes data based on the results from each module to achieve multi-physics coupling.

[0019] This embodiment is based on the simulation method of the above system, including:

[0020] Step 1: Initialize the coupled system by constructing the neutronics model and the thermo-hydraulic model, specifically including:

[0021] 1.1 Model the fuel grid and guide tube grid of the pressurized water reactor, and initialize the physical field with the mesh generation, material arrangement and flow conditions inside the pressurized water reactor as parameters.

[0022] 1.2 The neutron calculation module in the system obtains the multi-group cross-section σ of each nuclide from the ENDF / B-VII.0 cross-section database based on the obtained material and geometric information. x Based on the definition of constants, the effective self-shielding cross section of the nuclide g group is obtained. Where: φ F (E) represents the neutron flux density energy spectrum distribution of the grating element, n(E) represents the material nucleon density distribution of the grating element, and σ x This represents the microscopic cross-sectional distribution of the gate element.

[0023] 1.3 The neutron calculation module obtains the neutron flux φ at each location and in each energy group by solving the three-dimensional neutron transport equation. g (r) and the eigenvalues ​​k of the core problem eff After obtaining the volumetric heat release rate distribution, the coupled system calls the data transmission module to input the data into the thermal-hydraulic module.

[0024] The three-dimensional neutron transport equation is as follows: in: This is a leak in neutron space. Σ t (r,E)φ represents the neutrons that are removed from space due to scattering or absorption reactions, and the first term on the right-hand side of the equation represents the neutrons produced by scattering phenomena in space, Σ s For the macroscopic scattering cross section, Q f(r,E,Ω) represents neutrons produced by a fission reaction, and S(r,E,Ω) represents neutrons produced by an independent neutron source.

[0025] The volumetric heat release rate distribution Where: g=1,…,G, κ is the heat released in a single fission reaction, Σ f,g This represents the macroscopic fission cross section of a neutron.

[0026] The volumetric heat release rate distribution q″(r) obtained from the thermal-hydraulic module in system 1.4 is used to solve the fuel heat conduction equation to obtain the internal temperature of the fuel, specifically: Wherein: κ f The thermal conductivity of the fuel.

[0027] 1.5 Based on the obtained heat release from the fuel, the thermal-hydraulic module obtains the temperature and density distribution of the fluid by solving the fluid mass conservation equation, specifically: energy conservation equation. Momentum conservation equation as well as Where: ρ is the fluid density, u is the fluid velocity, and P fric Where P is the frictional pressure drop and P is the flow channel pressure.

[0028] 1.6 The thermal-hydraulic module in the system uses the Jens-Lottes empirical formula based on the obtained fuel temperature and coolant temperature. t w It is the fuel surface temperature, t s Here, q is the coolant saturation temperature, q is the heat flux density, and p is the pressure, where: ΔT is the superheated temperature of the fuel surface under subcooled boiling conditions. sat The system records the location of the fuel surface where supercooled boiling occurred.

[0029] Step 2, the system follows Figure 3 As shown in the coupled iterative strategy, the Picard iterative method is used to iterate between the neutronics model and the thermal-hydraulic model. Specifically, the thermal-hydraulic model calculates based on the power distribution provided by the neutronics model, and the neutronics model updates its database based on the temperature and density results calculated by the thermal-hydraulic model. This includes:

[0030] 2.1 The system is based on the obtained coolant density D m Coolant temperature T m Fuel temperature T f As a key parameter, the multi-group cross section σ is re-extracted from the cross section library. x ≡σ x (D m ,T m ,T f ).

[0031] 2.2 The system calls the module again to solve the three-dimensional neutron transport equations. If the eigenvalues ​​k of the problem... eff If the error compared to the previous calculation is less than 50 PCM, the eigenvalues ​​are considered to have converged; otherwise, the thermal-hydraulic model is calculated and the parameters are updated.

[0032] Step 3: When the eigenvalues ​​calculated by the quantum mechanics model converge, record the supercooled boiling situation under the current physical field and execute Step 4; otherwise, repeat Step 2.

[0033] Step 4: Keeping the system under supercooled boiling conditions, change the coupled iteration strategy and calculate the temperature, density, and thermal conductivity of the CRUD region using the CRUD product model. Continue the iteration process. The coupled iteration strategy is as follows: Figure 3 The lower part shows that the thermal-hydraulic model calculates based on the temperature, density, and thermal conductivity output from the CRUD model, while the neutronics model updates its database based on the temperature and density results from both the thermal-hydraulic model and the CRUD model. Specifically, this includes:

[0034] 4.1 Based on the coolant boron concentration and the heat flux density, fuel surface temperature, and coolant temperature calculated by the thermal model under the current operating conditions, solve the particle aggregation deposition equation m. p =h mt,p ∑ i c p,i Solute crystallization deposition equation and sedimentary erosion equation To obtain the final sedimentation results Where: h mt It is the mass transfer coefficient, c p,i It is the particle concentration, h cr It is the crystallinity coefficient, c cladding,i It is the surface concentration, c sat,i It is the saturation concentration, k er τ is the erosion constant, τ is the shear force, and W is the shear constant. a It is the work done by eroding the surface, E tot It is adhesion energy.

[0035] 4.2 Using the results obtained from the deposition model, the chemical composition inside the CRUD is calculated using a one-dimensional virtual mesh, and the chemical equilibrium equation is solved. Where: D i It is the fractal coefficient, used to obtain the boron concentration c at various locations. boron (r).

[0036] 4.3 Based on the results of the CRUD chemical composition model, the system establishes a cross-scale model, using a one-dimensional virtual grid to represent the radial distribution of boron concentration in the CRUD layer, such as... Figure 1 As shown, settings N(r) is the boron concentration N obtained from the regional nucleus density in the CRUD background layer. b It is passed to the neutron model for calculation.

[0037] 4.4 Based on the deposition layer thickness calculated using the CRUD deposition model, solve for the thermal conductivity of CRUD. Where: q”' sink ∝r c N c h c ∈(ε)(TT sat ), where: r c N is the characteristic radius of the chimney. c It is the chimney density, h c is the boiling heat transfer coefficient, ∈(ε) is the permeability, which is a function of porosity ε. Solving for CRUD yields the thermal conductivity κ. CRUD Calculations used to update the thermal model.

[0038] Step 5: When the eigenvalues ​​calculated by the neutron model converge, the coupled system completes the simulation and obtains the three-dimensional nuclear thermal material coupled temperature field, neutron flux field and power distribution of the problem; otherwise, repeat step 4.

[0039] like Figure 9 The diagram shows the CRUD model involved in this embodiment, including: a CRUD deposition model, a CRUD chemical composition model, and a CRUD thermal conductivity model. Specifically: the CRUD deposition model uses the coolant boron concentration under current operating conditions, the heat flux density calculated by the thermal model, temperature, and other parameters to obtain the deposition layer thickness and fluid surface heat transfer coefficient of the CRUD over a certain operating time; the CRUD chemical composition model uses the coolant boron concentration under current operating conditions, the heat flux density calculated by the thermal model, fuel surface temperature, coolant temperature, and the deposition layer thickness calculated by the CRUD deposition model, and solves the chemical equilibrium equation through a one-dimensional virtual mesh to obtain the boron concentration at each location of the corrosion products; the CRUD thermal conductivity model obtains the thermal conductivity of the CRUD deposition based on the deposition layer thickness calculated by the CRUD deposition model.

[0040] Through practical experiments, the coupled system, running on 2×7285H32C cloud servers, utilized 9 nodes with 576 cores to perform 3D modeling calculations on a typical 1 / 4 scale model of a pressurized water reactor fuel assembly. The fuel assembly consists of 17×17 cells, including 264 fuel rod cells and 25 guide tube cells. Axially, the active fuel height is 380 cm, with 20 cm of water at both ends acting as a reflector layer. Outside the reflector layer, a vacuum boundary condition is applied. Radially, the cells are arranged as follows... Figure 4As shown, the cell pitch is 1.26cm, forming a fuel assembly that is 21.5cm wide. The assembly boundary is set as a reflective boundary condition.

[0041] For the thermal-hydraulic calculation model, the coolant inlet temperature of the component model is 565K, the inlet mass flow rate is set to 24.056kg / s, and the working pressure is 15.5MPa. For each cell, 10 radial grids are divided to calculate the detailed heat transfer. In addition, the heat conduction of the fuel cell in the air gap is also considered in the model.

[0042] In the calculation of the CRUD model, the operating conditions of the pressurized water reactor fuel assembly after 180 days of steady-state continuous operation were simulated, with a boron concentration of 1300 ppm in the coolant under the operating conditions.

[0043] For the above model, in the iterative process of nuclear thermal CRUD coupling calculation, the nuclear thermal coupling calculation to determine the supercooled boiling position converges after 3 iterations, and the overall k of the fuel assembly is... eff The value decreased from 1.17685 to 1.16184, reflecting the influence of reactor assembly temperature. A CRUD model was subsequently introduced for coupled iteration, converging after two iterations. The overall k of the fuel assembly... eff The value decreased from 1.16184 to 1.15891, a drop of 293 pcm. This indicates that the presence of CRUD increases neutron absorption within the reactor assembly. Accurate analysis of the impact of CRUD on the overall assembly is crucial for reactor design, operation, and evaluation.

[0044] The effects of CRUD phenomenon on the axial power distribution of fuel assemblies were calculated as follows: Figure 5 As shown, after considering the effects of CRUD, the axial power distribution shifts downwards by approximately 50 cm towards the bottom of the core. Specifically, Figure 5 The results showed a significant power decrease at a core height of 250–300 cm, with the peak power of the assembly shifting from 170 cm to 130 cm, due to boron enrichment. This change in power distribution resulted in an approximately 22% increase in peak power and a rise in the peak power factor from 1.409 to 1.719. This increase poses a significant risk to the safe operation of the reactor.

[0045] like Figure 6 The diagram shows the three-dimensional power distribution characteristics and local radial power distribution features of the module. As can be observed from the color bars, at certain local locations of the module, the power peak exceeds 1.63 times the axial average power peak. Figure 4 As shown in (a), the presence of the guide tube causes a discontinuity in the radial power distribution, significantly affecting the overall radial power distribution. Combined with... Figure 4(b) Analysis reveals that the power distribution of the fuel assembly exhibits a trend of higher power in the central region and decreasing towards the periphery, with peak power concentrated in the area near the guide tube. For example, the relative peak power at the center of the assembly reaches 1.64, while the relative peak power in the peripheral region drops to 1.43, a difference of 14%.

[0046] like Figure 7 The figure shows the distribution of boron isotope density within the component, reflecting the accumulation of boron due to CRUD. Figure 7 As shown in (a), the formation of CRUDs is mainly concentrated between 210 cm and 380 cm in component height. With increasing height, the thickness of the CRUD and the corresponding boron concentration gradually decrease. Figure 7 (b) shows the radial boron isotope density variations at component heights of 150 cm, 210 cm, 270 cm, and 360 cm. Figure 7 (c) shows the distribution of these locations. Figure 7 As shown in (c4), in the lower region of the component, the boron isotope density is uniformly distributed at 9.525 × 10⁻⁶. -6 The atom / barn-cm concentration is the same as the inlet coolant boron concentration, therefore there is no potential risk of CRUD formation. (Comparison) Figure 7 (c3) and Figure 7 (c2) It can be observed that within the module, subcooled boiling does not occur uniformly in the radial direction. Axially, subcooled boiling first appears at a height of 210 cm. Radially, CRUD development initially begins in the area near the module center, close to the guide tube and with relatively high power, then gradually expands to cover most of the module area. For example... Figure 7 (c1) and Figure 7 As shown in (c2), the accumulation of CRUD and the overall thickness of the initial supercooled boiling region decrease with increasing height. At a height of 360 cm, the measured average boron isotope density is 2.185 × 10⁻⁶. -5 atom / barn-cm, which is equivalent to the boron nucleon density at 270 cm (5.094 × 10⁻⁶). -5 40% of (atom / barn-cm).

[0047] like Figure 8 As shown, compared with existing technologies, this method uses the probabilistic Monte Carlo method as the reference solution, and the background grid method can achieve cross-scale calculations at the cell level while introducing only 31 PCM of error. In contrast, without this method, the calculation will introduce amplified numerical errors, resulting in an error of 969 PCM. For Picard iterations of the three physics fields, this invention avoids the oscillation problem caused by the inability to determine the supercooled boiling position, reducing the average number of iteration convergence steps from 8 to 3, an improvement of approximately 60%.

[0048] The above-described specific implementations can be partially adjusted by those skilled in the art in different ways without departing from the principles and purpose of the present invention. The scope of protection of the present invention is defined by the claims and is not limited to the above-described specific implementations. All implementation schemes within the scope of the claims are bound by the present invention.

Claims

1. A cross-scale nuclear-thermal-material coupling simulation method for oxidation corrosion products of pressurized water reactors, characterized in that, In the first stage, the supercooled boiling position was obtained by iterative simulation using the neutronics model and the thermal-hydraulic model. In the second stage, multiphysics coupling simulation was performed using the oxidation corrosion product model, the neutronics model, and the thermal-hydraulic model to obtain a high-resolution simulation under the coupled conditions of the pressurized water reactor core-thermal-material. The multiphysics coupling simulation refers to: keeping the supercooled boiling condition unchanged, calculating the temperature, density and thermal conductivity of the CRUD region through the oxidation corrosion product model, and continuing the iterative process, that is: the thermal-hydraulic model calculates based on the temperature, density and thermal conductivity output by the CRUD model, and the neutronics model updates its database based on the temperature and density results of the thermal-hydraulic model and the CRUD model for calculation. The CRUD models include: CRUD deposition model, CRUD chemical composition model, and CRUD thermal conductivity model; The aforementioned nuclear-thermal-material coupling simulation method specifically includes: Step 1: Initialize the coupled system and construct the neutronics model and the thermo-hydraulic model respectively; Step 2: Use the Picard iteration method to iterate between the neutronics model and the thermal-hydraulic model. That is, the thermal-hydraulic model calculates based on the power distribution provided by the neutronics model, and the neutronics model updates its database based on the temperature and density results calculated by the thermal-hydraulic model. Step 3: When the eigenvalues ​​calculated by the quantum mechanics model converge, record the supercooled boiling situation under the current physical field and execute Step 4; otherwise, repeat Step 2. Step 4: Keeping the supercooled boiling condition unchanged, calculate the temperature, density, and thermal conductivity of the CRUD region using the oxidation corrosion product model, and continue the iterative process. That is, the thermal-hydraulic model calculates based on the temperature, density, and thermal conductivity output by the CRUD model, and the neutronics model updates its database based on the temperature and density results of the thermal-hydraulic model and the CRUD model for calculation. Step 5: When the eigenvalues ​​calculated by the neutron model converge, the simulation is completed, and the three-dimensional nuclear thermal material coupled temperature field, neutron flux field and power distribution of the problem are obtained; otherwise, repeat step 4.

2. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 1, characterized in that, Step 1 specifically includes: 1.1 Model the fuel grid cells and guide tube grid cells of the pressurized water reactor, and initialize the physical field with the mesh generation, material arrangement and flow conditions inside the pressurized water reactor as parameters; 1.2 The neutron calculation module in the system obtains multiple group cross-sections of each nuclide from the ENDF / B-VII.0 cross-section database based on the obtained material and geometric information. The effective self-shielding cross section of the g-group nuclide is obtained. ,in: The neutron flux density energy spectrum distribution of the gate element. The nucleon density distribution of the cell material. This represents the microscopic cross-sectional distribution of the gate element; 1.3 The neutron calculation module obtains the neutron flux at various locations and in various energy groups by solving the three-dimensional neutron transport equations. The eigenvalue k of the core problem eff After obtaining the volumetric heat release rate distribution, the coupled system calls the data transmission module to input the data into the thermal-hydraulic module; 1.4 Distribution of volumetric heat release rate obtained from the thermal-hydraulic module in the system The internal temperature of the fuel is obtained by solving the fuel heat conduction equation, specifically: ,in: The thermal conductivity of the fuel; 1.5 Based on the obtained heat release from the fuel, the thermal-hydraulic module obtains the temperature and density distribution of the fluid by solving the fluid mass conservation equation, specifically: energy conservation equation. Momentum conservation equation as well as ,in: Let u be the fluid density and u be the fluid velocity. For frictional pressure drop, For flow channel pressure; 1.6 The thermal-hydraulic module in the system uses the Jens-Lottes empirical formula based on the obtained fuel temperature and coolant temperature. , It is the fuel surface temperature. It is the coolant saturation temperature. It is heat flux density. It is pressure, where: the superheated temperature of the fuel surface under supercooled boiling conditions is calculated. The system records the location of the fuel surface where supercooled boiling occurred.

3. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 1, characterized in that, Step 2 specifically includes: 2.1 Based on the obtained coolant density Coolant temperature fuel temperature As a key parameter, multiple cross sections were re-extracted from the cross section library. ; 2.2 Solving the three-dimensional neutron transport equations, if the eigenvalues ​​of the problem are k eff If the error compared to the previous calculation is less than 50 PCM, the eigenvalues ​​are considered to have converged; otherwise, the thermal-hydraulic model is calculated and the parameters are updated.

4. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 2, characterized in that, The three-dimensional neutron transport equation is as follows: ,in: This is a leak in neutron space; The neutrons removed from space due to scattering or absorption reactions are represented by the first term on the right-hand side of the equation, which represents neutrons produced by scattering within space. For macroscopic scattering cross section, Neutrons produced by fission reactions Neutrons produced by an independent neutron source; The volumetric heat release rate distribution ,in: , The heat released in a single fission reaction. This represents the macroscopic fission cross section of a neutron.

5. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 1, characterized in that, Step 4 specifically includes: 4.1 Based on the coolant boron concentration and the heat flux density, fuel surface temperature, and coolant temperature calculated by the thermal model under the current operating conditions, solve the particle aggregation deposition equation. Solute crystallization deposition equation and deposition wear equation The final deposition results were obtained. ,in: The mass transfer coefficient is . Particle concentration, The crystallinity coefficient, For surface concentration, The saturation concentration Let be the erosion constant. Shear force, To perform work on the eroded surface, It is the adhesion energy; 4.2 Using the results obtained from the deposition model, the chemical composition inside the CRUD is calculated using a one-dimensional virtual mesh, and the chemical equilibrium equation is solved. ,in: The fractal coefficient is used to obtain the boron concentration at each location. ; 4.3 Results of the CRUD chemical composition model, establishing a cross-scale model, setting... , To determine the nucleon density of the region, the boron concentration in the CRUD background layer was calculated. This information is passed to the neutron model for computation. 4.4 Based on the deposition layer thickness calculated using the CRUD deposition model, solve for the thermal conductivity of CRUD. ,in: The characteristic radius of the chimney. For chimney density, The boiling heat transfer coefficient is... Permeability is denoted by porosity. The function is used to solve for the CRUD thermal conductivity. Calculations used to update the thermal model.

6. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 1, characterized in that, The CRUD deposition model uses the coolant boron concentration under the current operating conditions, and the heat flux density and temperature calculated by the thermal model to obtain the CRUD deposition layer thickness and fluid surface heat transfer coefficient. The CRUD chemical composition model uses the coolant boron concentration under the current operating conditions, the heat flux density calculated by the thermal model, the fuel surface temperature, the coolant temperature, and the deposition layer thickness calculated by the CRUD deposition model to solve the chemical equilibrium equation through a one-dimensional virtual mesh to obtain the boron concentration at each location of the corrosion products. The CRUD thermal conductivity model is used to calculate the thickness of the deposited layer based on the CRUD deposition model to obtain the thermal conductivity of the CRUD deposition.

7. A cross-scale nuclear-thermal-material coupling system for pressurized water reactor oxidation corrosion products implementing the method of any one of claims 1-6, characterized in that, include: The system comprises a neutron calculation module, a thermal calculation module, a corrosion product calculation module, and a data exchange module. Specifically: the neutron calculation module uses the variational segmented block method to solve the neutron transport equation, obtaining the neutron flux distribution and power distribution; the thermal calculation module uses the coupling of the parallel channel equation and the fuel heat conduction equation to solve the temperature field, obtaining the temperature of the material in each region; the corrosion product calculation module solves the growth equation and the chemical composition equation, obtaining the thickness of the corrosion products and their internal chemical composition; and the data exchange module exchanges and processes data based on the results of each module to achieve multi-physics coupling.

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