Multi-body modeling and simulation grid splicing method and device based on physical conservation

Abstract

The invention relates to a multi-body modeling and simulation grid splicing method and device based on physical conservation. The method comprises the following steps: carrying out simulation modeling on a physical space region of a reactor thermal hydraulic system to obtain two different sub-regions; the two different sub-domains form two interfaces; calculating fluxes on the two interfaces; deriving based on a non-matching interface flux conservation law, performing coefficient distribution on fluxes on the two interfaces, and calculating an interface field quantity value of an overlapping region of the two interfaces; performing weighted combination on the interface field quantity values on the two interface overlapping regions, updating the weighted interface field quantity values, and recombining the updated interface field quantity values based on the flux conservation law to obtain an interpolation result; and realizing simulation grid splicing according to an interpolation result. By adopting the method, the thermal hydraulic analysis efficiency of the reactor can be improved.

Description

Technical Field

[0001] This application relates to the technical field of reactor thermal-hydraulic system simulation, and particularly to a multi-body modeling and simulation grid splicing method and device based on physical conservation. Background Art

[0002] In the field of reactor thermal-hydraulic analysis, the application of CFD (Computational Fluid Dynamics) technology is extremely crucial. The internal structure of a reactor is intricate, especially the multi-body geometric structure part, which includes numerous independent regions such as fuel assemblies, control rod assemblies, coolant channels, etc. There are complex contacts and interfaces between these regions, such as between fuel rods and the wall of the coolant channel, between control rods and surrounding components, etc. When conducting CFD simulations, geometric modeling and mesh generation are fundamental steps. However, due to the complexity of the multi-body geometric structure inside the reactor, it is difficult to fully match the meshes of different component regions. For example, in the fuel assembly region, in order to accurately capture the flow and heat transfer characteristics of the coolant on the surface of the fuel rods, fine meshes need to be generated; while in some relatively simple spatial regions, the meshes can be appropriately sparse. In this case, the problem of mesh mismatch will occur.

[0003] In traditional simulation methods, non-conservative interpolation algorithms are often used to handle these mismatched mesh interfaces. However, in the high-demand application scenario of reactor thermal-hydraulic analysis, the defects of non-conservative interpolation algorithms are fully exposed. On the one hand, the flow conditions of the coolant inside the reactor are complex. In some high-flow-rate regions (similar to high Reynolds number flows), non-conservative interpolation is difficult to ensure the strict conservation of physical quantities such as mass, momentum, and energy, resulting in large errors in key parts such as near the fuel rods and in key flow channels in the simulation results, seriously affecting the accurate evaluation of the reactor's thermal-hydraulic performance. On the other hand, during the operation of the reactor, the flow and heat transfer of the coolant change rapidly, with a small time scale and a large spatial gradient. The numerical stability of the non-conservative interpolation algorithm is poor, and the calculation results are prone to oscillation or divergence phenomena, making the simulation results unreliable. Moreover, non-conservative interpolation also requires additional post-processing steps to correct errors, which greatly reduces the efficiency for the work that needs to quickly obtain simulation results to guide the safe operation and optimized design of the reactor.

[0004] In recent years, although various grid splicing methods based on conservation principles have been proposed, they still face challenges when applied to reactor thermal-hydraulic analysis. For example, the method of modifying the grid topology structure will greatly increase the workload for such a complex multi-body geometric structure of the reactor when re-meshing or merging meshes, and may reduce the local grid quality, affecting the simulation accuracy; while the method of constructing a super grid has excessive computational and storage overheads due to the large scale of reactor simulations, and it is difficult to be effectively implemented in actual reactor engineering analysis.

[0005] Therefore, in the field of reactor thermal-hydraulic analysis, how to simplify the algorithm complexity while maintaining flux conservation to achieve more efficient and accurate CFD simulation has become a key issue that needs to be urgently solved in the field of reactor safe operation and optimized design. Summary of the invention

[0006] Based on this, it is necessary to provide a multi-body modeling and simulation grid splicing method and device based on physical conservation that can improve the efficiency of reactor thermal-hydraulic analysis in response to the above-mentioned technical problems.

[0007] A multi-body modeling and simulation grid splicing method based on physical conservation, the method comprising: The physical space area of ​​the reactor thermal hydraulic system is simulated and modeled to obtain two different subdomains; the two different subdomains form two interfaces; the fluxes on the two interfaces are calculated; Based on the non-matching interface flux conservation law, the flux on the two interfaces is deduced by coefficient allocation, and the interface field magnitude in the overlapping area of ​​the two interfaces is calculated; the interface field magnitude in the overlapping area of ​​the two interfaces is weightedly combined to obtain the weighted interface field magnitude; The weighted interface field values ​​are updated to obtain updated interface field values; the updated interface field values ​​are reorganized based on the flux conservation law to obtain interpolation results; and simulation grid splicing is achieved according to the interpolation results.

[0008] A multi-body modeling and simulation grid splicing device based on physical conservation, the device comprising: The flux calculation module is used to simulate and model the physical space area of ​​the reactor thermal hydraulic system to obtain two different subdomains; the two different subdomains form two interfaces; and the flux on the two interfaces is calculated; The interface field magnitude calculation module is used to derive based on the law of conservation of non-matching interface flux, distribute coefficients of fluxes on two interfaces, calculate the interface field magnitude of the overlapping area of ​​the two interfaces; perform weighted combination of the interface field magnitudes on the overlapping area of ​​the two interfaces to obtain the weighted interface field magnitude; The field value reorganization module is used to update the weighted interface field value to obtain the updated interface field value; reorganize the updated interface field value based on the flux conservation law to obtain the interpolation result; and realize the simulation grid splicing according to the interpolation result.

[0009] The above multi-body modeling and simulation grid stitching method based on physical conservation can, first of all, reasonably define and abstract complex physical phenomena and regions in the reactor thermal-hydraulic analysis by establishing sub-domains, providing a clear spatial scope for subsequent numerical calculations, enabling the analysis to focus on specific regions, avoiding unnecessary calculations and interferences, and helping to improve the calculation efficiency. Among them, the sub-domains can form interfaces, which is conducive to the regional treatment of complex reactor systems. Different sub-domains may have different physical characteristics or flow states. Such a division can adopt more appropriate calculation methods or parameter settings according to the characteristics of different sub-domains. At the same time, the existence of interfaces also facilitates the handling of the interactions between sub-domains, making the calculation more organized and improving the accuracy and efficiency of the analysis. By accurately calculating the flux, the transmission laws of mass, momentum, energy, etc. in the reactor thermal-hydraulic process can be better understood, providing basic data for subsequent analysis based on the conservation laws, helping to improve the accuracy and reliability of the analysis, and thus improving the overall analysis efficiency. Then, based on the flux conservation law, coefficients are derived and distributed to calculate the interface field quantity values. On the one hand, the conservation of physical quantities is ensured, which is crucial for reactor thermal-hydraulic analysis because conservation is the basic requirement for accurately describing physical processes and can avoid incorrect results caused by non-conservation of physical quantities, improving the accuracy of the analysis. On the other hand, reasonable coefficient distribution can more accurately calculate the interface flux according to the characteristics of different interfaces and the requirements of physical processes, providing accurate data for subsequent calculations and helping to improve the efficiency of the entire analysis process. By weighted combination of the interface field quantity values, the information of two interfaces can be comprehensively considered to generate comprehensive and consistent results. The weighting method can be reasonably set according to factors such as the importance of the interface and the distribution of physical quantities, so as to more accurately reflect the actual physical situation in the reactor, avoid the one-sidedness of single-interface information, improve the reliability and accuracy of the analysis results, and thus improve the analysis efficiency. Updating the weighted interface field quantity values can continuously adjust and optimize the field quantity values according to the real-time information and physical laws during the calculation process to make them closer to the real situation. Mapping based on the flux conservation law to obtain the interpolation result ensures the conservation of physical quantities throughout the calculation process again, ensuring that the analysis results conform to physical reality. At the same time, the interpolation result can provide more accurate boundary conditions or initial conditions for subsequent calculations, enabling the calculation to converge more stably and quickly, improving the calculation efficiency, and providing a reliable numerical solution for reactor thermal-hydraulic analysis, helping to more deeply understand and analyze the thermal-hydraulic phenomena in the reactor, and thus improving the overall analysis efficiency. Description of the Drawings

[0010] Figure 1 It is a schematic flow chart of a multi-body modeling and simulation grid stitching method based on physical conservation in an embodiment; Figure 2Schematic diagram of multi-subdomain discretization for non-matching interface pairs in an embodiment; Figure 3 Schematic diagram of flux coefficient distribution and recombination in an embodiment; Figure 4 Block diagram of a multi-body modeling and simulation grid splicing device based on physical conservation in an embodiment. Detailed implementation manners

[0011] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0012] In one embodiment, as Figure 1 shown, a multi-body modeling and simulation grid splicing method based on physical conservation is provided, including the following steps: Step 102, perform simulation modeling on the physical space region of the reactor thermal-hydraulic system to obtain two different subdomains; the two different subdomains form two interfaces; calculate the fluxes on the two interfaces.

[0013] During the reactor thermal-hydraulic analysis process, a subdomain refers to a physical space region selected for numerical calculation and analysis in the reactor thermal-hydraulic system under study. It generally includes: the core region and the coolant system. Among them, the core region contains fuel assemblies, control rods, coolant channels, etc. Nuclear fission reactions occur in the fuel in the core, generating a large amount of heat. The coolant flows in the channels, taking the heat out of the core. The computational domain needs to accurately describe the fuel arrangement in the core, the coolant flow path, and related physical parameters to accurately analyze processes such as heat transfer, fluid flow, and neutron physics in the core. The coolant system includes reactor coolant pumps, steam generators, pressurizers, and connecting pipes, etc. The coolant circulates in these components, transferring the heat generated in the core to the steam generator to generate steam for power generation or other uses. The computational domain should cover the entire process of the coolant system to study changes in parameters such as the coolant flow rate, pressure, and temperature, as well as the stability and safety of the system.

[0014] By establishing sub-domains, complex physical phenomena and regions in reactor thermal-hydraulic analysis can be reasonably defined and abstracted, providing a clear spatial scope for subsequent numerical calculations. This enables the analysis to focus on specific regions, avoiding unnecessary calculations and interference, and contributing to improving the calculation efficiency. The formation of sub-domain interfaces is conducive to the zonal treatment of complex reactor systems. Different sub-domains may have different physical characteristics or flow states. Such a division allows for the adoption of more appropriate calculation methods or parameter settings according to the characteristics of different sub-domains. Meanwhile, the existence of interfaces also facilitates the handling of interactions between sub-domains, making the calculation more organized and enhancing the accuracy and efficiency of the analysis. By accurately calculating the flux, the transport laws of mass, momentum, energy, etc. in the reactor thermal-hydraulic process can be better understood, providing basic data for subsequent analysis based on conservation laws, contributing to improving the accuracy and reliability of the analysis, and thus enhancing the overall analysis efficiency.

[0015] Step 104: Based on the non-matching interface flux conservation law, derive and allocate coefficients to the fluxes on the two interfaces, and calculate the interface field quantity values in the overlapping region of the two interfaces; perform a weighted combination of the interface field quantity values in the overlapping region of the two interfaces to obtain the weighted interface field quantity values.

[0016] Derive and allocate coefficients according to the flux conservation law, calculate the interface field quantity values on the two interfaces, and combine them based on weighted averaging to generate a comprehensive and consistent result. Subsequently, the weighted result will be redistributed to the corresponding regions to ensure the precise conservation and balance of the flux or field quantity between the interfaces.

[0017] Step 106: Update the weighted interface field quantity values to obtain the updated interface field quantity values; map the updated interface field quantity values based on the flux conservation law to obtain the interpolation result; realize the simulation grid splicing according to the interpolation result.

[0018] Updating the weighted interface field quantity values can continuously adjust and optimize the field quantity values according to real-time information and physical laws during the calculation process, making them closer to the actual situation. Mapping based on the flux conservation law to obtain the interpolation result once again ensures the conservation of physical quantities throughout the calculation process, ensuring that the analysis results conform to physical reality. At the same time, the interpolation result can provide more accurate boundary conditions or initial conditions for subsequent calculations, enabling the calculation to converge more stably and quickly, improving the calculation efficiency, and providing a reliable numerical solution for reactor thermal-hydraulic analysis, contributing to a deeper understanding and analysis of thermal-hydraulic phenomena in the reactor, and thus enhancing the overall analysis efficiency. Through verification in actual engineering cases (such as reactor pressure vessel analysis), this application highlights its great value in improving simulation accuracy and solving non-matching interface problems in complex multi-body geometric situations, greatly improving the analysis efficiency.

[0019] The above-mentioned multi-body modeling and simulation grid stitching method based on physical conservation can, first of all, reasonably define and abstract complex physical phenomena and regions in the reactor thermal-hydraulic analysis by establishing sub-domains, providing a clear spatial range for subsequent numerical calculations, enabling the analysis to focus on specific regions, avoiding unnecessary calculations and interferences, and helping to improve the calculation efficiency. Among them, the sub-domains can form interfaces, which is conducive to the regional treatment of complex reactor systems. Different sub-domains may have different physical characteristics or flow states. Such a division can adopt more appropriate calculation methods or parameter settings according to the characteristics of different sub-domains. At the same time, the existence of interfaces also facilitates the handling of the interactions between sub-domains, making the calculation more organized and improving the accuracy and efficiency of the analysis. By accurately calculating the flux, the transmission laws of mass, momentum, energy, etc. in the reactor thermal-hydraulic process can be better understood, providing basic data for subsequent analysis based on conservation laws, helping to improve the accuracy and reliability of the analysis, and thus improving the overall analysis efficiency. Then, based on the flux conservation law, coefficients are derived and assigned to calculate the interface field quantity values. On the one hand, it ensures the conservation of physical quantities, which is crucial for reactor thermal-hydraulic analysis because conservation is the basic requirement for accurately describing physical processes and can avoid incorrect results caused by non-conservation of physical quantities, improving the accuracy of the analysis; on the other hand, reasonable coefficient assignment can calculate the interface flux more accurately according to the characteristics of different interfaces and the requirements of physical processes, providing accurate data for subsequent calculations and helping to improve the efficiency of the entire analysis process. By weighted combination of the interface field quantity values, the information of the two interfaces can be comprehensively considered to generate comprehensive and consistent results. The weighting method can be reasonably set according to factors such as the importance of the interface and the distribution of physical quantities, so as to more accurately reflect the actual physical situation in the reactor, avoid the one-sidedness of single-interface information, improve the reliability and accuracy of the analysis results, and thus improve the analysis efficiency. Updating the weighted interface field quantity values can continuously adjust and optimize the field quantity values according to real-time information and physical laws during the calculation process to make them closer to the real situation. Mapping based on the flux conservation law to obtain the interpolation result once again ensures the conservation of physical quantities throughout the calculation process, ensuring that the analysis results conform to physical reality. At the same time, the interpolation result can provide more accurate boundary conditions or initial conditions for subsequent calculations, enabling the calculation to converge more stably and quickly, improving the calculation efficiency, and providing a reliable numerical solution for reactor thermal-hydraulic analysis, helping to more deeply understand and analyze the thermal-hydraulic phenomena in the reactor, and thus improving the overall analysis efficiency.

[0020] In one of the embodiments, calculating the fluxes on two interfaces includes: Calculating the fluxes on two interfaces as: ; Wherein, The flux of the representation surface The value of the interface field quantity on the interface , The value of the interface field quantity of the interface , The value of the interface field quantity on the interface , The value of the interface field quantity of the interface , Each in the weight Each in the weight The flux of the representation surface Respectively represent the values of the relevant variables on the adjacent cells of the , interface and such as velocity, temperature The local numbers of the cell faces on the interface The local numbers of the cell faces on the interface

[0021] In a specific embodiment, as Figure 2 shown, when the computational domain is divided into two subdomains and , these two subdomains are independently discretized, and a pair of non-matching interfaces will be formed between them, denoted as and , respectively composed of the faces of subdomains and . These interfaces ensure correct communication between subdomains and are crucial for the accuracy of numerical simulation.

[0022] Assume that the , interfaces are respectively composed of the , faces. Based on the assumption or method of local connectivity: Each face on an interface is only coupled to some or all of the faces on the opposite interface that overlap with it. In other words, only when there is a geometric relationship (such as overlap) between the faces on two interfaces is numerical coupling allowed between them. The connectivity data between interfaces is defined using two lists: (1) Among them, the operator and return the area of the intersection surface.

[0023] In finite volume discretization, the flux is usually defined as the area expansion quantity related to the face F and can be calculated according to the values defined by the adjacent cells of the face. Specifically, the adjacent cells can be expressed as and , corresponding to the subdomains and respectively. The flux can be expressed as: (2) Among them, respectively represent the values of the relevant variables on the cells and , such as velocity, temperature, etc., represents the coefficient of finite volume discretization.

[0024] In equation (2), the terms on the right side can be respectively expressed as: (3) Therefore, equation (2) can be rewritten as: (4) Based on equation (4), for the faces and on the interfaces , , there is: (5) Combined with equation (3), we can obtain: (6) Due to the reason of grid splicing, based on the local connectivity assumption, there may be a situation where one grid cell corresponds to multiple grid cells on the opposite side at the splicing interface, then there will be: (7) Since the grid element mapping is not one-to-one, each has a certain weight in , and vice versa, each has a certain weight in , that is to say, equation (7) can be refined as: (8) The core idea of this application is to eliminate the geometric discontinuity between non-matching interfaces through interpolation techniques while maintaining computational efficiency and accuracy. It does not require modifying the mesh but uses weighted interpolation to transfer numerical values from the relative interface to the current interface. Specifically, the calculation of the flux on the interface is similar to that of the internal face flux. By introducing an interpolation formula, the matrix of the finite volume problem can be directly assembled on the original interface. This method transforms the connectivity problem of non-matching interfaces into a unified numerical framework through interpolation techniques, greatly reducing the computational complexity. This not only improves the computational efficiency but also simplifies the implementation process while maintaining consistency with traditional internal flux calculations. In summary, this application solves the geometric discontinuity problem of non-matching interfaces through interpolation techniques, avoids complex mesh adjustments, and achieves efficient and accurate numerical coupling.

[0025] In one of the embodiments, the derivation is based on the flux conservation law of non-matching interfaces, including: Based on the derivation of the flux conservation law of non-matching interfaces, the total fluxes on the two interfaces are equal, i.e.: ; Where, represents the flux of face , represents the flux of face ; Furthermore, by equating the coefficients, we get: ; Where, represents the value of the interface field quantity on interface , represents the value of the interface field quantity of interface , represents the value of the interface field quantity on interface , represents the value of the interface field quantity of interface , represents the weight of each in , represents the weight of each in .

[0026] In a specific embodiment, the flux conservation law of non-matching interfaces is: the total fluxes on interfaces and must be equal, i.e.: (9) Due to the directionality of the flux, Equation (9) can be discretized as follows: (10) Combining Equation (8), we have: (11) To make Equation (11) hold, we can set the corresponding terms on both sides of the equation and equal respectively. That is to say, (12) Furthermore, by equating the coefficients, we can obtain: (13) In one embodiment, as Figure 3 shown, the interface field quantity values on the overlapping regions of the two interfaces 、 are calculated respectively, and refined and distributed according to the area relationship of the overlapping region, we can get: and ; ; where, represents the interface field quantity value of surface , represents the interface field quantity value of surface , represents the weight of each in , represents the weight of each in . The weight is expressed as: ;

[0027] In one embodiment, the interface field quantity values on the two interfaces are weighted and combined to obtain the weighted interface field quantity value, including: For the refined part shared by the interfaces 、 , assuming here that 、 satisfy the local connectivity assumption, the field quantities of these two interfaces are weighted and averaged by a weighting coefficient , which reflects the contribution of each interface to the shared part. After determining their respective contributions, the calculation of the weighted combination is as follows: ; where, represents the weighting coefficient, represents surface The interface field quantity value, Represents the surface The interface field quantity value.

[0028] In one of the embodiments, the finally obtained weighted value Represents the balanced contribution of the two interfaces in the shared overlapping region. Subsequently, this value is redistributed back to their respective corresponding regions, namely And , so as to ensure that the numerical solution remains consistent and the required physical quantities are conserved between the interfaces. At this time, the interface field quantity values And Are updated as follows: ; Wherein, Represents the weighted interface field quantity value, Represents the set that satisfies the local connectivity assumption with the interface , Represents the set that satisfies the local connectivity assumption with the interface , Represents the surface The interface field quantity value, Represents the surface The interface field quantity value.

[0029] In one of the embodiments, the updated interface field quantity value is mapped based on the law of conservation of flux, including: In the finite volume discretization, Usually has a specific mapping relationship. Similarly, Also has the same mapping relationship. For example, for the diffusion term, the mapping relationship can be expressed as: ; Wherein, Represents the interface field quantity value of the interface , , Represents the interface field quantity value on the interface , , Represents the interface field quantity value of the interface , , Represents the interface field quantity value of the interface , , Represents each In The weight in, Represents each In The weight in.

[0030] In one embodiment, the updated interfacial field quantity values are mapped based on the law of flux conservation to obtain an interpolation result, including: The updated interfacial field quantity values are mapped based on the law of flux conservation, and the interpolation result is: 。

[0031] In a specific embodiment, the interpolation result shows that the recombined weighting values ensure strict conservation of the flux, which is crucial for maintaining numerical stability and can accurately reflect the interaction between the two regions in the final solution.

[0032] In one embodiment, as Figure 4 shown, a multi-body modeling and simulation grid stitching device based on physical conservation, the device includes: A flux calculation module 402, configured to perform simulation modeling on the physical space region of the reactor thermal-hydraulic system to obtain two different sub-domains; the two different sub-domains form two interfaces; calculate the fluxes on the two interfaces; An interfacial field quantity value calculation module 404, configured to perform derivation based on the non-matching interfacial flux conservation law, allocate coefficients to the fluxes on the two interfaces, calculate the interfacial field quantity values in the overlapping region of the two interfaces; perform weighted combination on the interfacial field quantity values in the overlapping region of the two interfaces to obtain weighted interfacial field quantity values; A field quantity value recombination module 406, configured to update the weighted interfacial field quantity values to obtain updated interfacial field quantity values; recombine the updated interfacial field quantity values based on the law of flux conservation to obtain an interpolation result; implement simulation grid stitching according to the interpolation result.

[0033] It should be understood that although Figure 1 the steps in the flowchart of Figure 1 are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover,

[0034] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0035] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A multi-body modeling and simulation grid splicing method based on physical conservation, characterized in that: The method comprises: Simulating and modeling the physical space region of the reactor thermal hydraulic system to obtain two different subdomains; the two different subdomains form two interfaces; and calculating the fluxes on the two interfaces; Derived based on the law of conservation of flux of non-matching interfaces, coefficients are allocated for the fluxes on the two interfaces, and the interface field magnitudes in the overlapping region of the two interfaces are calculated; weighted combination is performed on the interface field magnitudes in the overlapping region of the two interfaces to obtain weighted interface field magnitudes; The weighted interface field magnitude is updated to obtain an updated interface field magnitude; the updated interface field magnitude is reorganized based on the flux conservation law to obtain an interpolation result; and simulation grid splicing is realized according to the interpolation result.

2. The method according to claim 1, characterized in that: The fluxes at the two interfaces are calculated, including: The fluxes on the two interfaces are calculated as: ； in, Display surface The flux, Display interface The interface field magnitude on , Display interface The interface field magnitude , Display interface The interface field magnitude on , Display interface The interface field magnitude , Indicates each exist The weight in Indicates each exist The weight in Display surface The flux, Respectively represent the interface , Adjacent units and The values ​​of related variables, such as speed, temperature, Display interface The local number of each element face on Display interface Local numbering of each unit face above.

3. The method according to claim 1, characterized in that Derivation based on the non-matching interface flux conservation law includes: Based on the law of conservation of flux on non-matching interfaces, the total flux on the two interfaces is equal, that is: ； in, Display surface The flux, Display surface The flux; Further by equating the coefficients, we get: ； in, Display interface The interface field magnitude on , Display interface The interface field magnitude , Display interface The interface field magnitude on , Display interface The interface field magnitude , Indicates each exist The weight in Indicates each exist The weight in .

4. The method according to claim 1, characterized in that Calculating the interface field magnitude on the overlapping region of the two interfaces, including: The interface field values ​​on the overlapping area of ​​the two interfaces are calculated as follows: ； in, Display surface The interface field magnitude, Display surface The interface field magnitude, Indicates each exist The weight in Indicates each exist The weight in It is expressed as: 。 5. The method according to claim 1, characterized in that The interface field magnitudes on the overlapping regions of the two interfaces are weightedly combined to obtain a weighted interface field magnitude, including: The interface field magnitudes on the overlapping region of the two interfaces are weighted and combined to obtain the weighted interface field magnitude: in, represents the weighting coefficient, Display surface The interface field magnitude, Display surface The interface field value.

6. The method according to claim 1, characterized in that The weighted interface field value is updated as follows: ； in, represents the weighted interface field magnitude, Presentation and interface The set that satisfies the local connectivity assumption, Presentation and interface The set that satisfies the local connectivity assumption, Display surface The interface field magnitude, Display surface The interface field value.

7. The method according to claim 1, characterized in that Mapping of updated interface field values ​​based on flux conservation law, including: The mapping relationship is: ； in, Display interface The interface field magnitude , Display interface The interface field magnitude on , Display interface The interface field magnitude , Display interface The interface field magnitude on , Indicates each exist The weight in Indicates each exist The weight in .

8. The method according to claim 7, characterized in that Based on the flux conservation law, the updated interface field values ​​are mapped to obtain interpolation results, including: Based on the law of flux conservation, the updated interface field value is mapped and the interpolation result is obtained as follows: 。 9. A multi-body modeling and simulation grid splicing device based on physical conservation, characterized in that: The device comprises: A flux calculation module is used to simulate and model the physical space area of ​​the reactor thermal hydraulic system to obtain two different subdomains; the two different subdomains form two interfaces; and the flux on the two interfaces is calculated; An interface field magnitude calculation module is used to derive based on the law of conservation of non-matching interface flux, distribute coefficients on the fluxes on the two interfaces, and calculate the interface field magnitude of the overlapping area of ​​the two interfaces; perform weighted combination on the interface field magnitudes on the overlapping area of ​​the two interfaces to obtain a weighted interface field magnitude; The field value reorganization module is used to update the weighted interface field value to obtain an updated interface field value; reorganize the updated interface field value based on the flux conservation law to obtain an interpolation result; and realize simulation grid splicing according to the interpolation result.

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