Cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion product

Abstract

A pressurized water reactor oxidation corrosion product cross-scale nuclear-thermal-material coupling simulation method comprises the following steps: in the first stage, obtaining a supercooled boiling position through mutual loop iteration simulation of a neutronics model and a thermal hydraulic model; and in the second stage, multi-physics field coupling simulation is carried out through an oxidation corrosion product (CRUD) model, a neutronics model and a thermal hydraulic model, and high-resolution simulation under the pressurized water reactor nuclear-thermal-material coupling condition is obtained. According to the method, a scene in which the thickness range of the oxidation corrosion product is 20-200 microns is considered, multi-physical fields such as pressurized water reactor neutron physics, flow heat transfer and oxidation corrosion product deposition are calculated and analyzed, and the complex physical process can be captured more accurately.

Description

Technical Field

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

[0002] During long-term operation of pressurized water reactors (PWRs), subcooled boiling (SB) occurs in some reactor fuel rods, resulting in the deposition of oxidized corrosion products (CRUD) on their outer surfaces. The porous structure of the fuel rods exacerbates this internal boiling, leading to the enrichment of boron from the coolant within the corrosion products. Due to boron's high neutron absorption cross-section, this can lead to localized neutron flux and power suppression, which in turn can cause axial fission power shifts in the reactor, posing a threat to reactor safety. Existing reactor core multiphysics coupling technologies, when performing high-resolution modeling of corrosion products, ignore cross-scale modeling physics calculations and the subcooled boiling of the physical field, failing to reflect the actual physical conditions. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, which is limited to fixed heat flux density or corrosion product deposition feedback of a single fuel rod, and fails to carefully analyze the power distribution differences inside the fuel assembly and its influence on corrosion product deposition and axial power offset, and fails to consider the influence of corrosion products on thermal conductivity changes and the overall physical field, the present invention proposes a cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products. Taking into account the scenario where the thickness of oxidation corrosion products ranges from 20 microns to 200 microns, the computational analysis of multiple physical fields such as pressurized water reactor neutron physics, flow heat transfer and oxidation corrosion product deposition can more accurately capture complex physical processes.

[0004] The present invention is achieved through the following technical solutions:

[0005] The present invention relates to a cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products. In the first stage, a neutronics model and a thermal-hydraulic model are used for mutual iterative simulation to obtain the subcooled boiling position. In the second stage, a multi-physics field coupling 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 nuclear-thermal-material coupling conditions of the pressurized water reactor.

[0006] The multi-physics coupling simulation described herein is as follows: maintaining the subcooled boiling condition unchanged, calculating the temperature, density, and thermal conductivity of the CRUD region using the corrosion oxidation product (CRUD) model, and continuing the iterative process. Specifically, the thermal-hydraulic model performs calculations based on the temperature, density, and thermal conductivity output by the CRUD model, and the neutronics model performs calculations based on the temperature and density results of the thermal-hydraulic model and the CRUD model. Technical Effects

[0007] This method comprehensively considers the impact of corrosion product deposition on the multi-physics fields of pressurized water reactors (PWRs) and the possible variations in the onset of subcooled boiling during the iterative process. Based on a high-resolution deterministic approach and an adaptive iterative strategy, it ensures the stability of complex problem solving. Compared with existing technologies, this method significantly improves computational efficiency while maintaining high resolution and reliability. Specifically, when modeling corrosion product deposition (CRUD), this method more accurately characterizes the micron-scale dimensional characteristics of CRUD, avoiding the instability of numerical simulation results caused by the probabilistic uncertainty of the Monte Carlo method while also improving computational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 This is a schematic diagram of the CRUD virtual grid;

[0009] Figure 2 Schematic diagram of the system of the present invention;

[0010] Figure 3 It is an iterative cycle flow chart of the method of the present invention;

[0011] Figure 4 (a) Schematic diagram of the fuel assembly arrangement, (b) the guide tube grid, and (c) the fuel rod grid.

[0012] Figure 5 This is a schematic diagram comparing the relative axial power of components before and after the CRUD is introduced in the embodiment;

[0013] Figure 6 Schematic diagram of relative power distribution of fuel assembly in an embodiment;

[0014] Figure 7 Schematic diagram of boron nucleus density distribution of fuel assembly in the embodiment;

[0015] Figure 8 Schematic diagram of the embodiment effect;

[0016] Figure 9 This is the schematic diagram of the CRUD model. DETAILED DESCRIPTION

[0017] like Figure 2As shown, a cross-scale nuclear-thermal-material coupling system for oxidation corrosion products of a pressurized water reactor involved in this embodiment includes: a neutron calculation module, a thermal calculation module, a corrosion product calculation module and a data exchange module, wherein: the neutron calculation module uses a variational nodal method to solve the neutron transport equation to obtain 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 to obtain the temperature of the material in each region, the corrosion product calculation module solves the growth equation and the chemical composition equation to obtain the thickness of the corrosion product and the chemical composition inside it, and the data exchange module exchanges and processes data according to the results of each module to achieve multi-physics coupling.

[0018] This embodiment is based on the simulation method of the above system, including:

[0019] Step 1: Initialize the coupled system and construct the neutronics model and thermal hydraulic model respectively, including:

[0020] 1.1 Model the solved PWR fuel grid element and guide tube grid element, and use the mesh division, material layout inside the PWR, and flow conditions as parameters to initialize the physical field.

[0021] 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 information and geometric information x , according to the definition of constant, the effective self-screening cross section of nuclide g group is obtained Where: φ F (E) is the neutron flux density energy spectrum distribution of the gate element, n(E) is the material nucleon density distribution of the gate element, σ x is the microscopic cross-sectional distribution of the gate element.

[0022] 1.3 Neutron calculation module obtains the neutron flux φ at each position and energy group by solving the three-dimensional neutron transport equation g (r) and the eigenvalue k of the core problem eff After obtaining the volume heat release rate distribution, the coupling system calls the data transmission module to input the data into the thermal hydraulic module.

[0023] The three-dimensional neutron transport equation is: in: is the leakage of neutron space. t (r,E)φ is the neutron that is scattered or absorbed in the space and moved out. The first term on the right side of the equation is the neutron generated by the scattering phenomenon in the space, Σ s is the macroscopic scattering cross section, Q f(r, E, Ω) are neutrons produced by fission reactions, and S(r, E, Ω) are neutrons produced by an independent neutron source.

[0024] The volume heat release rate distribution Where: g = 1,…, G, κ is the heat released by a single fission reaction, Σ f,g is the macroscopic fission cross section of neutrons.

[0025] The volume heat release rate distribution q″(r) obtained by the thermal hydraulic module in the 1.4 system is used to obtain the temperature inside the fuel by solving the fuel heat conduction equation, specifically: Where: f is the thermal conductivity of the fuel.

[0026] 1.5 Based on the obtained fuel heat release, the thermal hydraulic module obtains the temperature and density distribution of the fluid by solving the mass conservation equation of the fluid, specifically: Momentum conservation equation as well as Where: ρ is the fluid density, u is the fluid velocity, P fric is the friction pressure drop, and P is the flow channel pressure.

[0027] The thermal hydraulic module in the 1.6 system uses the Jens-Lottes empirical relationship based on the obtained fuel temperature and coolant temperature. t w is the fuel surface temperature, t s is the coolant saturation temperature, q is the heat flux density, and p is the pressure, where: Calculate the fuel surface superheat temperature ΔT under subcooled boiling conditions sat , the system records the location on the fuel surface where subcooled boiling occurs.

[0028] Step 2: The system follows Figure 3 As shown in the coupled iterative strategy, the Picard iteration method is used to iterate between the neutronics model and the thermal-hydraulic model. That is, the thermal-hydraulic model calculates according to the power distribution provided by the neutronics model, and the neutronics model updates its database for calculation based on the temperature and density results calculated by the thermal-hydraulic model. Specifically, the following steps are performed:

[0029] 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, extract the multi-group cross-section σ from the cross-section library again x ≡σ x (D m ,T m ,T f ).

[0030] 2.2 The system calls the module again to solve the three-dimensional neutron transport equation. If the eigenvalue k of the problem eff If the error compared with the last calculation is less than 50 PCM, the eigenvalue is considered to have converged. Otherwise, the thermal-hydraulic model is calculated and the parameters are updated.

[0031] Step 3: When the eigenvalues calculated by the neutronics model converge, record the subcooled boiling situation under the current physical field and execute step 4; otherwise, repeat step 2.

[0032] Step 4: The system keeps the subcooled boiling condition unchanged, changes the coupled iteration strategy, calculates the temperature, density and thermal conductivity of the CRUD area through the CRUD model, and continues the iterative process. The coupled iteration strategy is as follows: Figure 3 As shown in the lower part, the thermal-hydraulic model calculates the temperature, density, and thermal conductivity output by the CRUD model. The neutronics model updates its database based on the temperature and density results of the thermal-hydraulic model and the CRUD model. Specifically, the following are performed:

[0033] 4.1 Based on the coolant boron concentration under the current working conditions and the heat flux density, fuel surface temperature, and coolant temperature calculated by the thermal model, solve the particle aggregation deposition equation m p =h mt,p ∑ i c p,i , solute crystallization deposition equation and sedimentation-erosion equations Get the final deposition result Where: h mt is the mass transfer coefficient, c p,i is the particle concentration, h cr is the crystallization coefficient, c cladding,i is the surface concentration, c sat,i is the saturation concentration, k er is the erosion constant, τ is the shear force, W a is the work done on the eroded surface, E tot is the adhesion energy.

[0034] 4.2 Using the results obtained from the deposition model, the one-dimensional virtual grid calculates the chemical composition inside the CRUD and solves the chemical equilibrium equation Where: D i is the fractal coefficient, and the boron concentration c at each location is obtained. boron (r).

[0035] 4.3 System Based on the results of the CRUD chemical composition model, a cross-scale model is established, using a one-dimensional virtual grid for the radial distribution of boron concentration in the CRUD layer, such as Figure 1 As shown, set N(r) is the regional nucleon density and the boron concentration N in the CRUD background layer is obtained. b , passed to the neutron model for calculation.

[0036] 4.4 According to the thickness of the deposited layer calculated by the CRUD deposition model, the thermal conductivity of CRUD is solved. Where: q"' sink ∝r c N c h c ∈(ε)(TT sat ), where: r c is the characteristic radius of the chimney, N c is the chimney density, h c is the boiling heat transfer coefficient, ∈(ε) is the permeability, which is a function of the porosity ε. Solving for the CRUD thermal conductivity κ CRUD Calculations used to update thermal models.

[0037] 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.

[0038] like Figure 9 As shown, the CRUD model involved in this embodiment includes: a CRUD deposition model, a CRUD chemical composition model, and a CRUD thermal conductivity model. The CRUD deposition model uses the coolant boron concentration under current operating conditions, the heat flux density calculated by the thermal model, and other parameters such as temperature to obtain the deposition layer thickness and fluid surface heat transfer coefficient of the CRUD under 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, the fuel surface temperature, the coolant temperature, and the deposition layer thickness calculated by the CRUD deposition model to solve the chemical equilibrium equation using a one-dimensional virtual grid to obtain the boron concentration at each location of the corrosion product. 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.

[0039] After specific practical experiments, the coupling system was used under a 2×7285H32C cloud server, calling 9 nodes with 576 cores to perform three-dimensional modeling calculations using a 1 / 4 model of a typical pressurized water reactor fuel assembly. The fuel assembly consists of 17×17 grid elements, including 264 fuel rod grid elements and 25 guide tube grid elements. In terms of axial arrangement, the active height of the fuel is 380cm, and there is 20cm of water at both ends as a reflection layer. Outside the reflection layer, a vacuum boundary condition is set. In the radial direction, the grid elements are arranged as follows Figure 4As shown, the grid cell pitch is 1.26 cm, forming a 21.5 cm wide fuel assembly, and a reflecting boundary condition is set at the assembly boundary.

[0040] 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 operating pressure is 15.5MPa. For each grid cell, 10 radial grids are divided to calculate the detailed heat transfer situation. In addition, the model also considers the heat conduction of the fuel grid cell in the air gap part.

[0041] 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, and the boron concentration in the coolant under the operating conditions was 1300 ppm.

[0042] For the above model, in the iterative process of nuclear thermal CRUD coupling calculation, the nuclear thermal coupling of the subcooled boiling position is determined to converge after 3 iterations, and the k of the entire fuel assembly is eff It dropped from 1.17685 to 1.16184, reflecting the influence of the reactor component temperature effect. The CRUD model was then introduced for coupled iteration. After two iterations, the model converged. The k of the fuel assembly as a whole was eff It dropped from 1.16184 to 1.15891, a decrease of 293 pcm. This indicates that the presence of CRUD increases neutron absorption within reactor components. Accurately analyzing the impact of CRUD on the overall component is crucial for reactor design, operation, and evaluation.

[0043] The influence of CRUD phenomenon on the axial power distribution of fuel assembly is calculated as follows: Figure 5 As shown in Figure 2, after considering the impact of CRUD, the axial power distribution shifts downward by about 50 cm toward the bottom of the core. Specifically, Figure 5 The power distribution at the core height of 250–300 cm shows a significant decrease in power, with the peak power of the component shifting from 170 cm to 130 cm due to the boron enrichment effect. This change in power distribution results in an approximately 22% increase in peak power, with the power crest factor rising from 1.409 to 1.719. This increase poses a significant risk to the safe operation of the reactor.

[0044] like Figure 6 As shown in the figure, the three-dimensional power distribution characteristics and local radial power distribution characteristics of the component are shown. It can be observed from the color bar that at some local positions of the component, the power peak exceeds 1.63 times the axial average power peak. Figure 4 As shown in (a), the existence of the guide tube causes discontinuity in the radial power distribution, which has a significant impact on the overall radial power distribution. Figure 4(b) Analysis reveals that the fuel assembly's power distribution exhibits a trend of being higher in the center and decreasing toward the periphery, with peak power concentrated near the guide tubes. For example, the relative power peak at the center of the assembly reaches 1.64, while the peak power in the periphery drops to 1.43, a difference of 14%.

[0045] like Figure 7 As shown in Figure 2, the distribution of boron isotope density within the component reflects the accumulation of boron due to CRUD. Figure 7 As shown in (a), the formation of CRUD is mainly concentrated between 210 cm and 380 cm in the component height. As the height increases, the thickness of CRUD and the corresponding boron concentration gradually decrease. Figure 7 (b) shows the radial boron isotope density variation at the assembly height of 150 cm, 210 cm, 270 cm and 360 cm, as shown in Figure 7 (c) shows the distribution of these locations. Figure 7 As shown in (c4), in the lower area of the component, the boron isotope density is uniformly distributed at 9.525×10 -6 atoms / barn-cm, the same as the inlet coolant boron concentration, so there is no potential risk of CRUD formation. Figure 7 (c3) and Figure 7 (c2), it can be observed that subcooled boiling does not occur uniformly in the radial direction inside the component. From the axial point of view, subcooled boiling first appears at a height of 210 cm. In the radial direction, the development of CRUD initially starts in the area near the center of the component close to the guide tube and with relatively high power, and then gradually expands to cover most areas of the component. Figure 7 (c1) and Figure 7 As shown in (c2), the accumulation of CRUD and the overall thickness of the initial region of supercooled boiling decrease with increasing altitude. At an altitude of 360 cm, the average boron isotope density was measured to be 2.185×10 -5 atom / barn-cm, which is equivalent to the boron nucleon density at 270 cm (5.094×10 -5 atom / barn-cm).

[0046] like Figure 8 As shown, compared with existing technologies, this method uses the probabilistic Monte Carlo method as a reference solution. The background grid method can achieve cross-scale calculations at the grid cell level while introducing only a 31PCM error. Compared to the case without this method, the calculation will have an amplified numerical error, resulting in a 969PCM error in the calculated results. For the Picard iteration of the three physical fields, this method avoids the oscillation problem caused by the uncertainty of the subcooled boiling position and reduces the average number of iterative convergence steps from 8 to 3, an improvement of approximately 60%.

[0047] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principles and purpose of the present invention. The scope of protection of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. All implementation schemes within its scope shall be subject to the constraints of the present invention.

Claims

1. A cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products, characterized in that: In the first stage, the subcooled boiling position was obtained through iterative simulation of the neutronics model and the thermal-hydraulic model. In the second stage, multi-physics 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 nuclear-thermal-material coupling conditions of the pressurized water reactor. The multi-physics coupling simulation refers to: maintaining the subcooled boiling condition unchanged, calculating the temperature, density, and thermal conductivity of the CRUD region using 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 and performs calculations based on the temperature and density results of the thermal-hydraulic model and the CRUD model; The CRUD model includes: a CRUD deposition model, a CRUD chemical component model and a CRUD thermal conductivity model.

2. The cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products according to claim 1 is characterized in that: include: Step 1: Initialize the coupled system and construct the neutronics model and thermal 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 for calculation based on the temperature and density results calculated by the thermal-hydraulic model. Step 3: When the eigenvalues calculated by the neutronics model converge, record the subcooled boiling situation under the current physical field and execute step 4; otherwise, repeat step 2. Step 4: Maintaining the subcooled boiling condition, the temperature, density, and thermal conductivity of the CRUD region are calculated using the oxidation corrosion product model. The iterative process continues, i.e., the thermal-hydraulic model performs calculations based on the temperature, density, and thermal conductivity output by the CRUD model, and the neutronics model performs calculations based on the temperature and density results from the thermal-hydraulic model and the CRUD model. Step 5: When the eigenvalues calculated by the neutron model converge, the simulation is completed to obtain the three-dimensional nuclear-thermal material coupled temperature field, neutron flux field and power distribution of the problem. Otherwise, repeat step 4.

3. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 2 is characterized in that: The step 1 specifically includes: 1.1 Model the solved PWR fuel grid element and guide tube grid element, and use the meshing, material layout, and flow conditions inside the PWR as parameters to initialize the physical field; 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 information and geometric information x , calculate the effective self-screening cross section of nuclide group g Where: φ F (E) is the neutron flux density energy spectrum distribution of the gate element, n(E) is the material nucleon density distribution of the gate element, σ x is the microscopic cross-sectional distribution of the gate element; 1.3 Neutron calculation module obtains the neutron flux φ at each position and energy group by solving the three-dimensional neutron transport equation g (r) and the eigenvalue k of the core problem eff After obtaining the volume heat release rate distribution, the coupling system calls the data transmission module to input the data into the thermal hydraulic module; The volume heat release rate distribution q″(r) obtained by the thermal hydraulic module in the 1.4 system is used to obtain the temperature inside the fuel by solving the fuel heat conduction equation, specifically: Where: f is the thermal conductivity of the fuel; 1.5 Based on the obtained fuel heat release, the thermal hydraulic module obtains the temperature and density distribution of the fluid by solving the mass conservation equation of the fluid, specifically: Momentum conservation equation as well as Where: ρ is the fluid density, u is the fluid velocity, P fric is the friction pressure drop, P is the flow channel pressure; The thermal hydraulic module in the 1.6 system uses the Jens-Lottes empirical relationship based on the obtained fuel temperature and coolant temperature. t w is the fuel surface temperature, t s is the coolant saturation temperature, q is the heat flux density, and p is the pressure, where: Calculate the fuel surface superheat temperature ΔT under subcooled boiling conditions sat , the system records the location on the fuel surface where subcooled boiling occurs.

4. The cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products according to claim 2 is characterized in that: The step 2 specifically includes: 2.1 According to the obtained coolant density D m , coolant temperature T m , fuel temperature T f As a key parameter, extract the multi-group cross-section σ from the cross-section library again x ≡σ x (D m ,T m ,T f ); 2.2 Solve the three-dimensional neutron transport equation. If the eigenvalue k of the problem eff If the error compared with the last calculation is less than 50 PCM, the eigenvalue is considered to have converged. Otherwise, the thermal-hydraulic model is calculated and the parameters are updated.

5. The cross-scale nuclear-thermal-material coupled simulation method for pressurized water reactor oxidation corrosion products according to claim 3 is characterized in that: The three-dimensional neutron transport equation is: in: is the leakage of neutron space; Σ t (r,E)φ is the neutron that is scattered or absorbed in the space and moved out. The first term on the right side of the equation is the neutron generated by the scattering phenomenon in the space, Σ s is the macroscopic scattering cross section, Q f (r, E, Ω) are neutrons produced by fission reactions, and S(r, E, Ω) are neutrons produced by an independent neutron source; The volume heat release rate distribution Where: g = 1,…, G, κ is the heat released by a single fission reaction, Σ f,g is the macroscopic fission cross section of neutrons.

6. The cross-scale nuclear-thermal-material coupling simulation method for pressurized water reactor oxidation corrosion products according to claim 1 is characterized in that: The step 4 specifically includes: 4.1 Based on the coolant boron concentration under the current working conditions and the heat flux density, fuel surface temperature, and coolant temperature calculated by the thermal model, solve the particle aggregation deposition equation m p =h mt,p ∑ i c p,i , solute crystallization deposition equation and deposition wear equation Get the final deposition result Where: h mt is the mass transfer coefficient, c p,i is the particle concentration, h cr is the crystallization coefficient, c cladding,i is the surface concentration, c sat,i is the saturation concentration, k er is the erosion constant, τ is the shear force, W a The work done on the eroded surface, E tot is the adhesion energy; 4.2 Using the results obtained from the deposition model, the one-dimensional virtual grid calculates the chemical composition inside the CRUD and solves the chemical equilibrium equation Where: D i is the fractal coefficient, and the boron concentration c at each location is obtained. boron (r); 4.3 Results of the CRUD chemical composition model, establishing a cross-scale model, setting N(r) is the regional nucleon density, and the boron concentration N in the CRUD background layer is obtained. b , passed to the neutron model for calculation; 4.4 According to the thickness of the deposited layer calculated by the CRUD deposition model, the thermal conductivity of CRUD is solved. Where: q″′ sink ∝r c N c h c ∈(ε)(TT sat ), where: r c is the characteristic radius of the chimney, N c is the chimney density, h c is the boiling heat transfer coefficient, ∈(ε) is the permeability, which is a function of the porosity ε, and the CRUD thermal conductivity κ is obtained by solving CRUD Calculations used to update thermal models.

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

8. A cross-scale nuclear-thermal-material coupling system for PWR oxidation corrosion products that implements the method of any one of claims 1 to 7, characterized in that: include: Neutron calculation module, thermal calculation module, corrosion product calculation module and data exchange module, among which: the neutron calculation module uses the variational block method to solve the neutron transport equation to obtain 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 to obtain the temperature of the material in each area; the corrosion product calculation module solves the growth equation and the chemical composition equation to obtain the thickness of the corrosion product and the chemical composition inside it; the data exchange module exchanges and processes data according to the results of each module to realize multi-physics coupling.

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