Method, device and system for determining reactor core cell level nuclear heat steady coupling and storage medium

Abstract

The application discloses a reactor core cell level nuclear heat steady-state coupling determination method, device, system and storage medium. The method comprises the following steps: determining an initial neutron flux distribution of a cell level and an initial effective multiplication coefficient of a core; taking the initial neutron flux distribution and the initial effective multiplication coefficient as initial coupling parameters corresponding to a first prediction, sequentially performing a preset operation, obtaining a predicted coupling parameter of each cycle operation, and determining a parameter difference between the predicted coupling parameter of each cycle operation and the predicted coupling parameter of the last cycle operation, until detecting that the parameter difference is less than a corresponding predicted parameter difference, and determining a reactor under the predicted coupling parameter with the parameter difference less than the predicted parameter difference as a steady-state reactor; the preset operation is used for determining a neutron cross section of the current cycle operation according to a neutron flux distribution and an effective multiplication coefficient of the current cycle operation.

Description

Technical Field

[0001] This application relates to the field of reactor processing technology, and in particular to a method, apparatus, system and storage medium for determining nuclear thermal steady-state coupling at the reactor core grid level. Background Technology

[0002] A pressurized water reactor (PWR) core is a complex system composed of fuel assemblies, structural materials, coolant, control rods, and soluble poisons. The energy released by nuclide fission is transferred to the coolant through fuel pellets and cladding, driving a turbine to generate electricity. Throughout the process, there is a strong feedback effect between neutron physics and thermal hydraulics, which is a core consideration in nuclear design, thermal hydraulic analysis, and safety assessment.

[0003] Commercial pressurized water reactor (PWR) design systems have been developed for many years and have formed a complete methodology. However, in the two-step nuclear design process of related technologies, the core often uses the segmented method to solve the neutron diffusion equation, with the physics-thermal feedback scale at the segment level. As core operating parameters increase, localized undercooling boiling becomes increasingly significant, increasing the vapor content in local channels. This can either control reactivity through negative feedback or reduce heat transfer capacity, leading to fuel DNB (deviation from nucleation boiling) or meltdown risks. Accurate simulation of localized undercooling boiling requires a cell-level scale. The segmented-level feedback nuclear-thermal coupling system in related technologies struggles to accurately capture localized high vapor content phenomena and cannot accurately assess their impact on nuclear-thermal coupling calculations. This results in insufficient accuracy in calculating core steady-state parameters, hindering further optimization of reactor safety and economy.

[0004] Therefore, there is an urgent need for a nuclear thermal steady-state coupling determination method based on the grid-level scale to achieve fine and accurate calculation of the nuclear physics and thermal-hydraulic parameters of the reactor core under local boiling conditions, so as to meet the high-precision requirements of reactor design and safety evaluation. Summary of the Invention

[0005] This invention provides a method, apparatus, system, and storage medium for determining nuclear thermal steady-state coupling at the reactor core grid level, to at least address the problems of insufficient nuclear thermal coupling feedback scale and low accuracy in simulating local boiling conditions in related technologies. The technical solution of this invention is as follows: According to a first aspect of the present invention, a method for determining nuclear thermal steady-state coupling at the grid level of a reactor core is provided, the method comprising: determining the initial neutron flux distribution at the grid level and the initial effective multiplication factor of the core; Using the initial neutron flux distribution and initial effective multiplication factor as the initial coupling parameters for the first prediction, preset operations are executed sequentially to obtain the predicted coupling parameters for each cycle. The parameter difference between the predicted coupling parameters of each cycle and the predicted coupling parameters of the previous cycle is determined until a parameter difference less than the corresponding predicted parameter difference is detected. The reactor with the predicted coupling parameters corresponding to the parameter difference less than the predicted parameter difference is then identified as a steady-state reactor. The preset operations include: determining the neutron flux distribution and effective multiplication factor for the current cycle based on the neutron cross-section of the previous cycle; determining the thermal-hydraulic parameters for the current cycle based on the neutron flux distribution obtained in the current cycle; determining the coolant density and fuel Doppler temperature in the neutron flux distribution, effective multiplication factor, and thermal-hydraulic parameters of the current cycle as the predicted coupling parameters for the current cycle; and determining the neutron cross-section for the current cycle based on the predicted coupling parameters for the current cycle.

[0006] In one implementation, the thermal-hydraulic parameters for the current cycle are determined based on the neutron flux distribution obtained in this cycle, including: determining a first power distribution of the reactor core based on the neutron flux distribution; mapping the first power distribution to a second power distribution based on a first mapping relationship from the neutron physical grid to the thermal-hydraulic grid; determining a first cooling parameter of the coolant and a first Doppler temperature of the fuel based on the second power distribution; the first cooling parameter includes a first coolant temperature, a first coolant density, and a first coolant cavitation fraction; mapping the first cooling parameter and the first Doppler temperature to a second cooling parameter and a second Doppler temperature respectively based on a second mapping relationship from the thermal-hydraulic grid to the neutron physical grid; and determining the second cooling parameter and the second Doppler temperature as the thermal-hydraulic parameters for this cycle.

[0007] In another implementation, the neutron cross section of the current cycle is determined based on the predicted coupling parameters of the current cycle operation. This includes determining the neutron cross section of the current cycle operation corresponding to the second coolant temperature, second coolant density, second coolant cavitation fraction, and second Doppler temperature in the second cooling parameters based on the correlation mapping relationship between coolant temperature, coolant density, coolant cavitation fraction, Doppler temperature and neutron cross section change.

[0008] In another implementation, the first cooling parameters of the coolant are determined based on the second power distribution, including: constructing a coolant energy conservation model based on the second power distribution; the coolant energy conservation model characterizes the relationship between coolant density, linear power density, channel flow area, coolant mass flow rate, and coolant specific enthalpy at the axial position; discretizing the coolant energy conservation model using a central difference method; determining the equilibrium vapor content and the first coolant density at the axial position based on the discretized coolant energy conservation model; and determining the bubble detachment from the wall starting point. The correlation mapping between the coolant liquid phase isobaric specific heat capacity, liquid phase thermal conductivity, heat flux density, thermodynamic equivalent diameter, mass flow rate, and coolant temperature is used to determine the first coolant temperature at the starting point of bubble detachment from the wall. Based on the Ahmad or Levy method, the true vapor content is determined according to the equilibrium vapor content at the starting point of bubble detachment from the wall. Based on the correlation mapping between the true vapor content, coolant vapor phase saturation density, coolant liquid phase saturation density, correction factor, coolant mass flow rate, and coolant cavitation fraction, the first coolant cavitation fraction corresponding to the true vapor content is determined.

[0009] In another implementation, the initial neutron flux distribution at the grid level and the initial effective multiplication coefficient of the reactor core are determined, including: determining a neutron transport model based on the correlation mapping relationship between the total order of the reactor, the neutron flux of adjacent orders, the concentration of delayed neutron precursor nuclei, the decay constant, the delayed neutron fraction, the fission cross section, and the effective multiplication coefficient; determining an odd-order term quantum model composed of odd-order terms from the neutron transport model; replacing even-order terms in the neutron transport model with even-order terms based on the odd-order term quantum model to obtain an even-order term flux model; discretizing the even-order term flux model using the finite difference method; and determining the initial neutron flux distribution and the initial effective multiplication coefficient based on the even-order multigroup neutron flux in the discretized even-order term flux model.

[0010] In another implementation, determining the parameter difference between the predicted coupling parameters of each cycle and the predicted coupling parameters of the previous cycle includes: determining the neutron distribution difference between the neutron flux distribution of the current cycle and the neutron flux distribution of the previous cycle; determining the difference in the effective multiplication coefficient between the current cycle and the effective multiplication coefficient of the previous cycle; determining the density difference between the coolant density of the current cycle and the coolant density of the previous cycle; and determining the Doppler temperature difference between the Doppler temperature of the fuel in the current cycle and the Doppler temperature of the fuel in the previous cycle.

[0011] In another implementation, determining the first Doppler temperature of the fuel includes: constructing a fuel temperature thermal conductivity model based on the fuel radial temperature and the specific heat capacity, density, thermal conductivity, volumetric heat flux density, and area factor of the material; determining the radial temperature distribution of the fuel based on the fuel temperature thermal conductivity model; and determining the first Doppler temperature based on the temperature mapping relationship between the fuel pellet center temperature and the fuel pellet surface temperature and the radial temperature distribution.

[0012] According to a second aspect of the present invention, a reactor core grid-level nuclear thermal steady-state coupling determination device is provided. The device comprises: a determination unit configured to determine the initial neutron flux distribution of the grid level and the initial effective multiplication coefficient of the core; and a coupling unit configured to sequentially and cyclically perform preset operations using the initial neutron flux distribution and the initial effective multiplication coefficient as the initial coupling parameters corresponding to the first prediction, to obtain the predicted coupling parameters for each cycle operation, and to determine the parameter difference between the predicted coupling parameters of each cycle operation and the predicted coupling parameters of the previous cycle operation, until the parameter difference is detected to be less than the corresponding predicted parameter. When the parameter difference is less than the predicted parameter difference, the reactor with the predicted coupling parameters corresponding to the predicted parameter difference is identified as a steady-state reactor. The preset operation includes: determining the neutron flux distribution and effective multiplication factor of the current cycle operation based on the neutron cross section of the previous cycle operation; determining the thermal-hydraulic parameters of the current cycle operation based on the neutron flux distribution obtained in the current cycle operation; determining the coolant density and fuel Doppler temperature in the neutron flux distribution, effective multiplication factor, and thermal-hydraulic parameters of the current cycle operation as the predicted coupling parameters of the current cycle operation; and determining the neutron cross section of the current cycle operation based on the predicted coupling parameters of the current cycle operation.

[0013] According to a third aspect of the invention, a reactor core grid-level nuclear thermal steady-state coupling determination system is provided, the system being configured to perform a reactor core grid-level nuclear thermal steady-state coupling determination method as described in the first aspect and any possible implementation thereof.

[0014] According to a fourth aspect of the present invention, an electronic device is provided, comprising: a processor and a memory for storing processor-executable instructions; wherein the processor is configured to execute the executable instructions to implement a reactor core grid-level nuclear thermal steady-state coupling determination method as described in the first aspect and any possible implementation thereof.

[0015] According to a fifth aspect of the invention, a computer-readable storage medium is provided, on which instructions are stored, such that when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is able to perform a reactor core grid-level nuclear thermal steady-state coupling determination method as described in the first aspect and any possible implementation thereof.

[0016] According to a sixth aspect of the present invention, a computer program product is provided, the computer program product including computer instructions, which, when executed on an electronic device, cause the electronic device to perform the reactor core grid-level nuclear thermal steady-state coupling determination method described in the first aspect and any possible implementation thereof.

[0017] The technical solution provided by this invention brings at least the following beneficial effects: The embodiments of this application, from initial parameters to each iteration calculation, are all performed at the "gate level," with a spatial resolution far exceeding that of the node-level methods in related technologies. Furthermore, it can precisely characterize the bubbles generated at local locations within the coolant channel, changes in vapor content, and the distribution of cavitation fraction, thus fundamentally solving the problem in related technologies where "nuclear-thermal coupling systems are difficult to accurately simulate local high vapor content phenomena." Moreover, through a loop of "preset operations," key parameters (coolant density, fuel Doppler temperature) obtained from thermal-hydraulic calculations are fed back to neutron physics calculations and used to update the neutron cross-section. The coolant density is directly affected by the cavitation fraction generated by local boiling, and the Doppler temperature is calculated from the detailed radial temperature distribution of the fuel. This closed-loop iterative mechanism, which directly influences the neutron cross-section with local thermal states (especially boiling-related parameters), ensures the authenticity and completeness of the physical feedback, solving the problem in related technologies where it is impossible to "evaluate the impact of high vapor content on nuclear-thermal coupling calculations." Furthermore, by continuously comparing the differences in predicted coupling parameters (including neutron flux, effective multiplication factor, coolant density, and Doppler temperature) between adjacent cycles and setting strict convergence criteria, it is ensured that a set of self-consistent and stable cell-level physical-thermal state parameters is ultimately obtained. This provides a reliable and convergent numerical solution basis for evaluating the steady-state safety (e.g., whether it deviates from DNB, whether the fuel temperature is safe) and economy (e.g., power distribution optimization) of the reactor core under local boiling conditions. Therefore, this application, by implementing cell-level, iteratively convergent nuclear-thermal coupling calculations that include feedback of key thermal parameters of local boiling, successfully overcomes the shortcomings of related technologies, such as coarse simulation scale and incomplete physical feedback. It provides an effective tool for accurately analyzing the impact of local boiling conditions on the steady-state characteristics of the reactor core, thereby producing significant positive effects in improving reactor simulation accuracy and supporting advanced design and safety assessment.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application, and do not constitute an undue limitation of this application.

[0020] Figure 1This is a flowchart illustrating a method for determining nuclear thermal steady-state coupling at the grid level in a reactor core, according to an exemplary embodiment. Figure 2 This is a block diagram illustrating a reactor core grid-level nuclear thermal steady-state coupling determination device according to an exemplary embodiment; Figure 3 This is a schematic diagram of an electronic device according to an exemplary embodiment. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0022] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0023] Before providing a detailed description of the reactor core grid-level nuclear thermal steady-state coupling determination method provided in this application embodiment, a brief introduction to the application scenarios and implementation environment involved in this application embodiment is given.

[0024] First, a brief introduction to the application scenarios involved in this application will be given.

[0025] A pressurized water reactor (PWR) core is a complex system composed of fuel assemblies, structural materials, coolant, control rods, and soluble poisons. Uranium-235 and other nuclides fission release energy, which is released from the fuel pellets through the cladding into the coolant, raising its temperature and directly or indirectly generating steam to drive a secondary turbine for power generation. The entire process involves multiple disciplines, including neutron physics, thermal hydraulics, fuel performance, structural mechanics, and water chemistry. A strong feedback effect exists between neutron physics and thermal hydraulics in PWRs, and this feedback effect must be considered in nuclear design, thermal hydraulic analysis, and safety assessment.

[0026] During commercial pressurized water reactor (PWR) operation, the coolant is generally in a subcooled state. Early safety restrictions generally prevented localized boiling. However, with a deeper understanding of this phenomenon in recent years, localized subcooled boiling is now permitted in PWRs during operation. Increasing core operating parameters can reduce core outlet subcooling to some extent, leading to a significant increase in steam content in local channels. On the one hand, steam content in PWRs often has negative feedback, helping to control reactivity; on the other hand, increased steam content may reduce heat transfer capacity, potentially causing DNB (density-dependent boiling) or melting of the fuel, threatening core safety. Therefore, maintaining PWR core parameters within a reasonable range while ensuring core safety and appropriately improving core economics is worthy of further exploration. In current two-step nuclear design programs, the core often uses the segmented method to solve the neutron diffusion equation, and then reconstructs the calculation to obtain the flux and power distribution of each fuel rod. The physical-thermal feedback scale is at the segment level, while the local supercooled boiling phenomenon can only be better simulated at the grid level. Therefore, nuclear thermal coupling systems have difficulty accurately simulating local high vapor content phenomena and evaluating the impact of high vapor content on nuclear thermal coupling calculations.

[0027] To address the aforementioned issues, this application proposes a method for determining nuclear-thermal steady-state coupling at the core grid level. This method employs the finite difference method to discretize the SPn neutron transport equations, a single-channel two-phase model to simulate the coolant flow and heat transfer equations, and an integral method to discretize the cylindrical / plate thermal conductivity equations. Mesh mapping is used to convert parameters between the neutron physics and thermal-hydraulic mesh fields. Semi-convergence combined with relaxation techniques improves convergence efficiency. Picard iteration is used to obtain the three-dimensional neutron physics and thermal-hydraulic parameters at the entire core grid level, improving the accuracy of nuclear-thermal coupling calculations simulating local high steam content phenomena in pressurized water reactor cores. Thus, by implementing iteratively convergent nuclear-thermal coupling calculations at the grid level, incorporating feedback of key thermal parameters related to local boiling, the shortcomings of existing technologies—such as coarse simulation scale and incomplete physical feedback—are successfully overcome.

[0028] Specifically, firstly, the computational scale is refined from the traditional node-level to the cell-level, fundamentally enabling high-precision characterization of subtle phenomena such as high vapor content and void fraction caused by local boiling. Secondly, through a closed-loop iterative process, the precisely calculated coolant density (directly affected by void fraction) and key thermal state parameters such as fuel Doppler temperature are fed back in real time to neutron cross-section updates and physical calculations, establishing a refined physics-thermal coupling feedback mechanism. Simultaneously, a multi-parameter convergence criterion ensures that the entire coupled system ultimately converges to a set of self-consistent and stable cell-level steady-state solutions, guaranteeing the reliability of the calculation results. Finally, this method provides a high-precision numerical analysis tool for evaluating core safety margins and optimizing operating parameters under local boiling conditions, significantly improving the depth and reliability of reactor design and safety analysis.

[0029] For ease of understanding, the method for determining nuclear thermal steady-state coupling at the grid level of the reactor core provided in this application will be described in detail below with reference to the accompanying drawings.

[0030] Figure 1 This is a flowchart illustrating a method for determining nuclear thermal steady-state coupling at the grid level in a reactor core, according to an exemplary embodiment. Figure 1 As shown, the method for determining the nuclear thermal steady-state coupling of the reactor core grid element level is implemented.

[0031] S11 determines the initial neutron flux distribution at the gate level and the initial effective multiplication factor of the core.

[0032] The specific implementation steps are as follows.

[0033] Firstly, given that the total order N and n of the reactor are a certain order, the neutron flux of any order and its adjacent orders... Delayed neutron precursor nucleus concentration C, decay constant λ, delayed neutron fraction β, fission cross section Σf, and effective multiplication coefficient Based on the correlation and mapping relationship between them, a neutron transport model (SPn neutron transport equation) is constructed, and its expression is as follows.

[0034] (1) (2) Where S represents the source term, and The energy group number is represented by χ, which is the fission spectrum, and v is the number of neutrons released in each fission.

[0035] Secondly, from the neutron transport model, the odd-order terms composed of odd-order terms with odd order n are extracted and the formula (1) is rewritten to obtain formula (3). Formula (3) is substituted into the even-order terms flux expression to eliminate the odd-order terms (the process is as shown in formula (4) and formula (5)). The even-order terms flux model composed of 2N+1 equations is obtained, and its matrix form is as follows.

[0036] (3) (4) (5) The specific relationships among the coefficients in the matrix of formula (5) are as follows: , , , , , , , , , .

[0037] The finite difference method is used to discretize formula (5) in space, and formula (5) becomes the following formula (6).

[0038] (6) Where A is the coefficient matrix and Φ is the neutron flux vector of even-order terms.

[0039] (7) Where the absorption cross section Σa,dV is the network volume. Specifically, the even-order flux model is spatially discretized using the finite difference method to obtain a set of discretized linear equations. The BicgTAB or Gauss-Seidel iterative method is used to solve the set of equations, i.e., formula (6), to obtain the even-order multi-group neutron flux, which is then determined as the initial neutron flux distribution. 0; at the same time, the initial effective proliferation coefficient is calculated according to formula (7).

[0040] S12, using the initial neutron flux distribution and initial effective multiplication coefficient as the initial coupling parameters corresponding to the first prediction, sequentially execute the preset operation to obtain the predicted coupling parameters for each cycle operation, and determine the parameter difference between the predicted coupling parameters of each cycle operation and the predicted coupling parameters of the previous cycle operation, until the parameter difference is detected to be less than the corresponding predicted parameter difference, the reactor with the predicted coupling parameters corresponding to the parameter difference being less than the predicted parameter difference is determined as a steady-state reactor.

[0041] The preset operations include: determining the neutron flux distribution and effective multiplication coefficient of the current cycle based on the neutron cross section of the previous cycle; determining the thermal-hydraulic parameters of the current cycle based on the neutron flux distribution obtained in the current cycle; determining the coolant density and fuel Doppler temperature from the neutron flux distribution, effective multiplication coefficient, and thermal-hydraulic parameters of the current cycle as the predicted coupling parameters of the current cycle; and determining the neutron cross section of the current cycle based on the predicted coupling parameters of the current cycle.

[0042] In this step, starting from the initial coupling parameters, the preset operations are executed cyclically until the convergence condition is met.

[0043] The determination of the neutron flux distribution and effective multiplication coefficient for this cycle includes: based on the neutron cross section Σk obtained from the previous cycle. 1. (Using the initial neutron cross section Σ0 in the first iteration), update the coefficient matrix A of the even-order flux model, and repeat the discretization and solution process in step 1 to obtain the neutron flux distribution for this iteration. k and effective proliferation coefficient.

[0044] The initial neutron flux distribution obtained in step S11 0 and the initial effective proliferation coefficient are used as the initial coupling parameters for the first prediction. The following preset operations are executed in sequence until the parameter difference is detected to be less than the corresponding prediction parameter difference.

[0045] Through the above implementation method, from initial parameters to each iteration calculation, everything is clearly performed at the "gate level," which has a spatial resolution far exceeding that of the nodal-level methods in related technologies. Furthermore, it can precisely characterize the bubbles generated at local locations within the coolant channel, changes in vapor content, and the distribution of cavitation fraction, thus fundamentally solving the problem in related technologies where "nuclear-thermal coupling systems are difficult to accurately simulate local high vapor content phenomena." Moreover, through a loop of "preset operations," key parameters (coolant density, fuel Doppler temperature) obtained from thermal-hydraulic calculations are fed back to neutron physics calculations and used to update the neutron cross-section. The coolant density is directly affected by the cavitation fraction generated by local boiling, and the Doppler temperature is calculated from the detailed radial temperature distribution of the fuel. This closed-loop iterative mechanism, which directly influences the neutron cross-section with local thermal states (especially boiling-related parameters), ensures the authenticity and completeness of the physical feedback, solving the problem in related technologies where it is impossible to "assess the impact of high vapor content on nuclear-thermal coupling calculations." Furthermore, by continuously comparing the differences in predicted coupling parameters (including neutron flux, effective multiplication factor, coolant density, and Doppler temperature) between two adjacent cycles and setting strict convergence criteria, it is ensured that a set of self-consistent and stable cell-level physical-thermal state parameters is finally obtained. This provides a reliable and convergent numerical solution basis for evaluating the steady-state safety (such as whether it deviates from DNB and whether the fuel temperature is safe) and economy (such as power distribution optimization) of the reactor core under local boiling conditions.

[0046] Therefore, this application successfully overcomes the shortcomings of related technologies, such as coarse simulation scale and incomplete physical feedback, by implementing cell-level, iteratively convergent nuclear thermal coupling calculations that include feedback of key thermal parameters of local boiling. It provides an effective tool that can accurately analyze the impact of local boiling conditions on the steady-state characteristics of the reactor core, thereby producing significant positive effects in improving the accuracy of reactor simulation and supporting advanced design and safety assessment.

[0047] As a refinement and extension of the specific implementation of the above embodiments, in order to fully explain the specific implementation process of this embodiment, this application provides some other methods for determining the nuclear thermal steady-state coupling of reactor core grid elements.

[0048] The specific process of determining the thermal-hydraulic parameters of the current cycle operation based on the neutron flux distribution obtained in step S12 above includes the following steps.

[0049] First, the first power distribution of the reactor core is determined based on the neutron flux distribution.

[0050] The first power distribution Q of the reactor core is determined by the following formula.

[0051] (8) Where Q is the actual power of the grid (W). The cross section represents neutron energy fission. Neutron flux; For the mesh volume; The total energy group number is denoted as .

[0052] Secondly, based on the first mapping relationship from the neutron physics grid to the thermal-hydraulic grid, the first power distribution is mapped and transformed into the second power distribution.

[0053] Specifically, based on the first mapping relationship from the neutron physics grid to the thermal-hydraulic grid, the first power distribution Q1 is mapped to the second power distribution Q2. The first mapping relationship adopts the extensive quantity mapping method based on the volume weight method. The mapping weight coefficient wij is calculated as follows: the proportion of the intersection volume of the source field (neutron physics grid) grid j and the target field (thermal-hydraulic grid) grid i to the sum of the intersection volumes of the source field grid j and all target field grids, i.e., the following formula (9).

[0054] (9) in, Power calculated for neutron physics fields; The grid mapping weight coefficient describes the transformation relationship between the source field grid j and the target field grid i; This represents the power converted to a thermal-hydraulic field. The power mentioned above is an extensive quantity (i.e., volume-dependent). The calculation method is the proportion of the intersection volume of the source field grid j and the target field grid i to the sum of the intersection volumes of the source field grid i and all target field grids.

[0055] Third, based on the second power distribution, the first cooling parameters of the coolant and the first Doppler temperature of the fuel are determined.

[0056] The first cooling parameters include the first coolant temperature, the first coolant density, and the first coolant cavitation fraction.

[0057] In some embodiments, determining the first cooling parameter of the coolant based on the second power distribution specifically includes the following steps.

[0058] Step 1: Based on the second power distribution, construct a coolant energy conservation model.

[0059] The coolant energy conservation model characterizes the relationship between coolant density, linear power density, channel flow area, coolant mass flow rate and coolant specific enthalpy at the axial position.

[0060] Step two: Discretize the coolant energy conservation model using the central difference method.

[0061] Step 3: Based on the discretized coolant energy conservation model, determine the equilibrium vapor content of the coolant at the axial position and the first coolant density.

[0062] Step 4: Determine the first coolant temperature at the starting point of bubble detachment from the wall based on the correlation mapping relationship between the specific heat capacity of the coolant liquid phase at constant pressure, the thermal conductivity of the liquid phase, the heat flux density, the thermal equivalent diameter, the mass flow rate, and the coolant temperature at the starting point of bubble detachment from the wall.

[0063] Step 5: Based on the Ahmad method or the Levy method, determine the true vapor content according to the equilibrium vapor content at the starting point of bubble detachment from the wall.

[0064] Step 6: Determine the first coolant cavitation fraction corresponding to the true vapor content based on the correlation mapping relationship between the true vapor content, the vapor saturation density of the coolant, the liquid saturation density of the coolant, the correction factor, the mass flow rate of the coolant, and the coolant cavitation fraction.

[0065] Specifically, as one implementation method, the coolant temperature, density, vapor content, void fraction, and enthalpy are calculated by establishing a discrete expression for the single-channel two-phase heat transfer equation.

[0066] First, the linear power density of the target field grid i is calculated based on the following formula. .

[0067] (10) Secondly, the energy conservation equation for the coolant is adopted by the center difference separation method.

[0068] The energy conservation equation for the coolant is shown in equation (11).

[0069] (11) The discretized form of formula (11) is shown in formula (12).

[0070] (12) in, The density of the coolant (its unit can be...) ); The passageway area (its unit can be...) ); Linear power density (its unit can be...) ); The coolant mass flow rate (its unit can be...) ); Specific enthalpy of coolant (its unit can be...) ).

[0071] Next, the equilibrium vapor content at the axial z position is calculated using formula (13).

[0072] (13) Next, the bubble detachment from the wall starting point (FDB) is calculated.

[0073] When the coolant is subcooled <Axial FDB undercooling This location is the starting point where the bubble detaches from the wall, and the coolant subcooling degree. and axial FDB position undercooling The calculation formulas are as follows: formulas (14) and (15). Record the equilibrium vapor content at FDB as... .

[0074] (14) (15) in, This is the coolant saturation temperature; This refers to the liquid phase temperature of the coolant. The thermal conductivity is the liquid phase coefficient. This refers to the specific heat capacity of the liquid phase at constant pressure. Where is heat flux density; D is thermal equivalent diameter; G is mass flow rate; For Peclet numbers.

[0075] Next, calculate the true steam content. The true steam content is calculated using either the Ahmad method or the Levy method. The Ahmad method is shown in formula (16) below, and the Levy method is shown in formula (17) below.

[0076] (16) (17) Next, the cavitation fraction is calculated using the Zuber-Findlay relation, as shown in formulas (18) and (19) below.

[0077] (18) (19) in, This is the saturated density of the gas phase; ρ is the saturated density of the liquid phase; g is the acceleration due to gravity; G is the mass flow rate; is the correction factor; p is the pressure; This is the critical pressure.

[0078] Next, the density of the gas-liquid mixture is calculated using either the cavitation fraction or the equilibrium vapor content. The equilibrium vapor content method is shown in formula (20); the cavitation fraction method is shown in formula (21).

[0079] (20) (twenty one) Next, calculate the heat transfer coefficient. The Dittus-Boelter relation is used in the single-phase flow region, and the Chen relation is used in the saturated boiling region.

[0080] Next, a discrete expression for the fuel temperature heat conduction equation is established to solve for the fuel radial temperature distribution, cladding temperature distribution, and fuel Doppler temperature.

[0081] Specifically, first, calculate the volumetric power density q.

[0082] (twenty two) Second, discrete fuel heat conduction equations.

[0083] The unified expression of the fuel temperature heat conduction equation is as follows.

[0084] (twenty three) For the specific heat capacity of the material, For material density, Material thermal conductivity, Internal heat source (volume heat flux density); Area factor.

[0085] If it is a cylinder, then If it is a flat plate, then If it is a ball, then The corresponding boundary conditions are shown in the following formula.

[0086] Core center temperature boundary: (twenty four).

[0087] The outer surface boundary of the core is defined by the following formula.

[0088] (25) The boundary of the inner surface of the shell is defined by the following formula.

[0089] (26) The outer surface boundary of the shell is defined by the following formula.

[0090] (27) in, This is the distance from the inner surface of the casing to the center; This is the distance from the outer surface of the fuel pellet to the center. This is the distance from the outer surface of the casing to the center. The heat transfer coefficient is the gas transfer coefficient between the cladding and the outer surface of the core. It is the heat transfer coefficient between the outer surface of the casing and the coolant.

[0091] Multiplying both sides of the formula by the area factor A and integrating radially in space, the diffusion term (first term on the right) and the source term (second term on the right) can be discretized and expressed as follows.

[0092] (28) (29) in, For the geometrically related area factor, j=1 for plate, j=2 for cylinder, and j=3 for sphere.

[0093] The heat conduction equation can be expressed as the following formula.

[0094] (30) Third, the above tridiagonal matrix is ​​solved using the LU decomposition method to obtain the radial temperature distribution of the fuel.

[0095] Fourth, calculate the fuel Doppler temperature.

[0096] Specifically, (31); among which, This refers to the center temperature of the fuel pellet. The surface temperature of the fuel pellets; This is the temperature weighting factor.

[0097] Furthermore, the thermal-hydraulic parameters are mapped from the thermal-hydraulic field to the neutron physics field, as shown in formula (32).

[0098] (32) The thermal-hydraulic parameters include coolant temperature, coolant density, fuel Doppler temperature, and cavitation fraction. Coolant temperature, coolant density, and fuel Doppler temperature are intensive quantities (independent of volume), while cavitation fraction is extensive.

[0099] Mapping weighting coefficient of void fraction The calculation method is the same as the mapping weighting coefficient for power. However, the mapping weighting coefficients for intensive parameters such as coolant density... The calculation method is the proportion of the intersection volume of the target field grid i and the source field grid j to the sum of the intersection volumes of the target field grid i and all source field grids.

[0100] Fourth, based on the second mapping relationship from the thermal-hydraulic grid to the neutron physics grid, the first cooling parameter and the first Doppler temperature are respectively mapped and converted into the second cooling parameter and the second Doppler temperature.

[0101] Fifth, the second cooling parameter and the second Doppler temperature are determined as the thermal-hydraulic parameters for this cycle operation.

[0102] The specific steps in step S12 above for determining the neutron cross section of the current cycle operation based on the predicted coupling parameters of the current cycle operation include: determining the neutron cross section of the current cycle operation corresponding to the second coolant temperature, second coolant density, second coolant cavitation fraction, and second Doppler temperature in the second cooling parameters based on the correlation mapping relationship between coolant temperature, coolant density, coolant cavitation fraction, Doppler temperature and neutron cross section change.

[0103] In some implementations, the neutron cross section is updated based on state parameters (including thermal-hydraulic parameters). Specifically, it is characterized by the following formula.

[0104] in, This refers to the fraction of voids; To determine the share of the control rod insertion; The fuel Doppler temperature; This refers to the coolant temperature. The density of the moderator; Boron concentration; The neutron section is the reference state point; This refers to the change in neutron cross-section caused by the insertion of the control rod; This represents the change in neutron cross section caused by the fuel Doppler temperature. This represents the change in neutron cross-section caused by coolant temperature. This represents the change in neutron cross-section caused by coolant density; This represents the change in neutron cross-section caused by boron concentration. This represents the change in neutron cross-section caused by the cavitation fraction.

[0105] Furthermore, the convergence of the neutron physics field and the thermal-hydraulic field in the two iterations is determined by the following formulas (34) to (37). Moderator density and fuel Doppler temperature were selected as parameters to determine the convergence of the two iterations in the thermal-hydraulic calculations. Effective multiplication coefficient and neutron flux were selected as parameters to determine the convergence of the two iterations in the neutron physics calculations.

[0106] (33) (34) (35) (36) (37) The above To achieve convergence criteria, generally Values ​​can be retrieved , Corresponding value .

[0107] In some implementations, during nuclear thermal coupling calculations, the user specifies the number of neutron flux iterations. Once the required number of iterations is reached, the neutron flux equation solution terminates. The following criterion is used to determine whether the neutron physics field and fuel temperature field converge in two consecutive iterations. This iterative strategy is called a semi-convergent technique in this invention, meaning that it does not require full convergence of the neutron physics field before proceeding to the thermal-hydraulic calculations.

[0108] If the neutron physics and thermal hydraulic calculations converge after two iterations, the coupled calculation of the neutron physics field and the thermal hydraulic field ends, and the search for critical parameters begins.

[0109] Critical search includes searching for critical boron concentration, critical rod position, critical power, etc., that is, adjusting boron concentration, rod position, and power to make the effective core multiplication factor close to 1.0.

[0110] The formula for calculating the critical boron concentration is as follows.

[0111] (38) As one implementation method, determining the initial neutron flux distribution at the gate level and the initial effective multiplication factor of the reactor core includes the following steps.

[0112] First, based on the correlation mapping relationship between the total order of the reactor, the neutron flux of adjacent orders, the concentration of delayed neutron precursor nuclei, the decay constant, the delayed neutron fraction, the fission cross section and the effective multiplication coefficient, the neutron transport model is determined.

[0113] Secondly, from the neutron transport model, we determine the odd-order general quantum model composed of odd-order terms with odd order.

[0114] Third, based on the odd-order term flux quantum model, the even-order terms in the neutron transport model are replaced to obtain the even-order term flux model.

[0115] Fourth, the finite difference method is used to discretize the flux model of even-order terms.

[0116] Fifth, based on the even-order multi-group neutron flux in the even-order flux model after discretization, the initial neutron flux distribution and the initial effective multiplication coefficient are determined.

[0117] As one implementation, determining the parameter difference between the predicted coupling parameters of each cycle and the predicted coupling parameters of the previous cycle includes the following steps: determining the neutron distribution difference between the neutron flux distribution of the current cycle and the neutron flux distribution of the previous cycle; determining the difference in multiplication coefficient between the effective multiplication coefficient of the current cycle and the effective multiplication coefficient of the previous cycle; determining the density difference between the coolant density of the current cycle and the coolant density of the previous cycle; and determining the Doppler temperature difference between the Doppler temperature of the fuel in the current cycle and the Doppler temperature of the fuel in the previous cycle.

[0118] As one implementation method, determining the first Doppler temperature of the fuel includes: constructing a fuel temperature thermal conductivity model based on the fuel radial temperature and the specific heat capacity, material density, material thermal conductivity, volumetric heat flux density, and area factor of the material; determining the radial temperature distribution of the fuel based on the fuel temperature thermal conductivity model; and determining the first Doppler temperature based on the temperature mapping relationship between the fuel pellet center temperature and the fuel pellet surface temperature and the radial temperature distribution.

[0119] Through the above implementation methods, based on the objective feedback phenomenon between neutron physics and thermal hydraulics in the reactor core, the SPn equation is used to simulate the neutron physics field in the core grid-level nuclear thermal coupling calculation. The simulation of void fraction is added to the thermal hydraulic calculation, providing the radial distribution of fuel temperature. Based on these models, a more refined and accurate distribution of thermal hydraulic parameters can be provided, particularly the vapor content of local channels. Furthermore, the neutron cross-section changes caused by these more realistic thermal hydraulic parameters are considered in the neutron cross-section calculation, resulting in more accurate nuclear thermal coupling calculation results. This contributes to a deeper understanding of the reactor's coupling characteristics, providing more reliable results for reactor design optimization and safety assessment. Compared with existing methods, the method adopted in this invention 1) supports calculations for reactors with various geometries, such as rod-shaped fuel, flat-plate fuel, and spherical fuel; 2) except for the void fraction model and heat transfer model which are water-based models, by replacing these models with corresponding models under other media, the entire method can also be applied to the grid-level steady-state coupling simulation of reactor cores with other coolant media; 3) the order of SPn can be specified by the user to obtain higher-order fluxes, improving the calculation accuracy of neutron physics; 4) the number of radial grid divisions for fuel heat conduction can be specified by the user to provide a finer radial temperature distribution of the fuel, and the calculation accuracy of Doppler temperature can be improved by specifying the Doppler temperature calculation mode by the user; 5) it can simulate the critical search process of steady-state processes.

[0120] To achieve the above functions, the reactor core grid-level nuclear thermal steady-state coupling determination device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art will readily recognize that, based on the algorithmic steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0121] This disclosure also provides an embodiment such as Figure 2 The reactor core grid-level nuclear thermal steady-state coupling determination device shown includes: a determination unit 21 configured to determine the initial neutron flux distribution of the grid level and the initial effective multiplication factor of the core; and a coupling unit 22 configured to use the initial neutron flux distribution and the initial effective multiplication factor as the initial coupling parameters corresponding to the first prediction, sequentially perform preset operations to obtain the predicted coupling parameters for each cycle, and determine the parameter difference between the predicted coupling parameters of each cycle and the predicted coupling parameters of the previous cycle, until a parameter difference less than the corresponding predicted parameter difference is detected, at which point the parameter difference is set to less than the predicted parameter difference. The reactor under the predicted coupling parameters corresponding to the parameter difference is determined as a steady-state reactor. The preset operation includes: determining the neutron flux distribution and effective multiplication factor of the current cycle operation based on the neutron cross section of the previous cycle operation; determining the thermal-hydraulic parameters of the current cycle operation based on the neutron flux distribution obtained in the current cycle operation; determining the coolant density and fuel Doppler temperature in the neutron flux distribution, effective multiplication factor, and thermal-hydraulic parameters of the current cycle operation as the predicted coupling parameters of the current cycle operation; and determining the neutron cross section of the current cycle operation based on the predicted coupling parameters of the current cycle operation.

[0122] In one embodiment, the coupling unit 22 is specifically configured to: determine a first power distribution of the reactor core based on the neutron flux distribution; map the first power distribution to a second power distribution based on a first mapping relationship from the neutron physical grid to the thermal-hydraulic grid; determine a first cooling parameter of the coolant and a first Doppler temperature of the fuel based on the second power distribution; the first cooling parameter includes a first coolant temperature, a first coolant density, and a first coolant cavitation fraction; map the first cooling parameter and the first Doppler temperature to a second cooling parameter and a second Doppler temperature based on a second mapping relationship from the thermal-hydraulic grid to the neutron physical grid; and determine the second cooling parameter and the second Doppler temperature as the thermal-hydraulic parameters for this cycle operation.

[0123] In another embodiment, the coupling unit 22 is specifically configured to: determine the neutron cross section of the second coolant temperature, second coolant density, second coolant cavitation fraction, and second Doppler temperature corresponding to the current cycle operation based on the correlation mapping relationship between coolant temperature, coolant density, coolant cavitation fraction, Doppler temperature and neutron cross section change in the second cooling parameters.

[0124] In another embodiment, the coupling unit 22 is specifically configured as follows: Based on the second power distribution, a coolant energy conservation model is constructed; the coolant energy conservation model characterizes the relationship between coolant density, linear power density, channel flow area, coolant mass flow rate, and coolant specific enthalpy at the axial position; the coolant energy conservation model is discretized using a central difference method; based on the discretized coolant energy conservation model, the equilibrium vapor content and the first coolant density at the axial position are determined; based on the coolant liquid phase at the point where bubbles detach from the wall... The correlation mapping between pressure specific heat capacity, liquid phase thermal conductivity, heat flux density, thermodynamic equivalent diameter, mass flow rate, and coolant temperature is used to determine the first coolant temperature at the starting point of bubble detachment from the wall. Based on the Ahmad method or Levy method, the true vapor content is determined according to the equilibrium vapor content at the starting point of bubble detachment from the wall. Based on the correlation mapping between the true vapor content, coolant vapor saturation density, coolant liquid saturation density, correction factor, coolant mass flow rate, and coolant cavitation fraction, the first coolant cavitation fraction corresponding to the true vapor content is determined.

[0125] In another implementation, the determining unit 21 is specifically configured as follows: A neutron transport model is determined based on the correlation mapping relationship between the total order of the reactor, the neutron flux of adjacent orders, the concentration of delayed neutron precursor nuclei, the decay constant, the delayed neutron fraction, the fission cross section, and the effective multiplication coefficient; from the neutron transport model, an odd-order term quantum model composed of odd-order terms of odd order is determined; based on the odd-order term quantum model, even-order terms of even order in the neutron transport model are replaced to obtain an even-order term flux model; the even-order term flux model is discretized using the finite difference method; and the initial neutron flux distribution and the initial effective multiplication coefficient are determined based on the even-order multigroup neutron flux in the discretized even-order term flux model.

[0126] In another embodiment, the coupling unit 22 is specifically configured to: determine the neutron distribution difference between the neutron flux distribution of the current cycle and the neutron flux distribution of the previous cycle; determine the difference in multiplication coefficient between the effective multiplication coefficient of the current cycle and the effective multiplication coefficient of the previous cycle; determine the density difference between the coolant density of the current cycle and the coolant density of the previous cycle; and determine the Doppler temperature difference between the Doppler temperature of the fuel in the current cycle and the Doppler temperature of the fuel in the previous cycle.

[0127] In another embodiment, the coupling unit 22 is specifically configured to: construct a fuel temperature thermal conductivity model based on the fuel radial temperature and the specific heat capacity, material density, material thermal conductivity, volumetric heat flux density, and area factor of the material; determine the radial temperature distribution of the fuel based on the fuel temperature thermal conductivity model; and determine the first Doppler temperature based on the temperature mapping relationship between the fuel pellet center temperature and the fuel pellet surface temperature and the radial temperature distribution.

[0128] Regarding the apparatus in the above embodiments, the specific manner in which each unit module performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0129] Figure 3 This is a schematic diagram of an electronic device provided in this application. (For example...) Figure 3 The electronic device 60 may include at least one processor 601 and a memory 603 for storing processor-executable instructions. The processor 601 is configured to execute the instructions in the memory 603 to implement the reactor core grid-level nuclear thermal steady-state coupling determination method described in the following embodiments.

[0130] In addition, the electronic device 60 may also include a communication bus 602, at least one communication interface 604, an input device 606, and an output device 605.

[0131] The processor 601 may be a processor (central processing unit, CPU), a microprocessor unit, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0132] The communication bus 602 may include a path for transmitting information between the aforementioned components.

[0133] Communication interface 604 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0134] Input device 606 is used to receive input signals and output device 605 is used to output signals.

[0135] The memory 603 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed discs, laser discs, optical discs, digital universal discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory may exist independently and be connected to the processing unit via a bus. The memory may also be integrated with the processing unit.

[0136] The memory 603 stores instructions for executing the scheme of this application, and the processor 601 controls the execution. The processor 601 executes the instructions stored in the memory 603 to realize the functions of the method of this application.

[0137] In a specific implementation, as one example, processor 601 may include one or more CPUs, for example... Figure 3 CPU0 and CPU1 in the CPU.

[0138] In a specific implementation, as one example, the electronic device 60 may include multiple processors, such as... Figure 3 Processors 601 and 607 are described herein. Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor here may refer to one or more devices, circuits, and / or processing cores used to process data (such as computer program instructions).

[0139] The electronic device is as follows Figure 3 The diagram includes a processor 601 and a memory 603 for storing executable instructions of the processor 601. The processor 601 is configured to execute the executable instructions to implement the reactor core grid-level nuclear thermal steady-state coupling determination method as described in any of the possible embodiments above. Furthermore, it achieves the same technical effects, and to avoid repetition, will not be elaborated further here.

[0140] This application also provides a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by the processor of a reactor core grid-level nuclear thermal steady-state coupling determination device or electronic device, the reactor core grid-level nuclear thermal steady-state coupling determination device or electronic device is able to perform the reactor core grid-level nuclear thermal steady-state coupling determination method as described in any of the above possible embodiments. And it can achieve the same technical effect; to avoid repetition, it will not be described again here.

[0141] This application also provides a computer program product, including a computer program or instructions, which are executed by a processor as described in any of the possible embodiments above for determining the reactor core grid-level nuclear thermal steady-state coupling method. This achieves the same technical effect, and to avoid repetition, it will not be described again here.

[0142] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0143] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for determining the nuclear thermal steady-state coupling at the grid level in a reactor core, characterized in that, The method includes: Determine the initial neutron flux distribution at the grid level and the initial effective multiplication factor of the core; Using the initial neutron flux distribution and the initial effective multiplication coefficient as the initial coupling parameters corresponding to the first prediction, the preset operation is executed in sequence to obtain the prediction coupling parameters for each cycle operation, and the parameter difference between the prediction coupling parameters of each cycle operation and the prediction coupling parameters of the previous cycle operation is determined, until the parameter difference is detected to be less than the corresponding prediction parameter difference, the reactor with the prediction coupling parameters corresponding to the parameter difference being less than the prediction parameter difference is determined as a steady-state reactor; The preset operation includes: determining the neutron flux distribution and effective multiplication coefficient of the current cycle operation based on the neutron cross section of the previous cycle operation; determining the thermal-hydraulic parameters of the current cycle operation based on the neutron flux distribution obtained in the current cycle operation; determining the coolant density and fuel Doppler temperature in the neutron flux distribution, effective multiplication coefficient, and thermal-hydraulic parameters of the current cycle operation as the predicted coupling parameters of the current cycle operation; and determining the neutron cross section of the current cycle operation based on the predicted coupling parameters of the current cycle operation.

2. The method according to claim 1, characterized in that, The determination of the thermo-hydraulic parameters for this cycle of operation based on the neutron flux distribution obtained in this cycle includes: Based on the neutron flux distribution, the first power distribution of the reactor core is determined; Based on the first mapping relationship from the neutron physics grid to the thermal-hydraulic grid, the first power distribution is mapped and transformed into the second power distribution; Based on the second power distribution, a first cooling parameter for the coolant and a first Doppler temperature for the fuel are determined; the first cooling parameter includes a first coolant temperature, a first coolant density, and a first coolant cavitation fraction. Based on the second mapping relationship from the thermal-hydraulic grid to the neutron physics grid, the first cooling parameter and the first Doppler temperature are respectively mapped and converted into the second cooling parameter and the second Doppler temperature. The second cooling parameter and the second Doppler temperature are determined as the thermo-hydraulic parameters for this cycle operation.

3. The method according to claim 2, characterized in that, Based on the predicted coupling parameters of this cycle operation, the neutron cross section of this cycle operation is determined, including: Based on the correlation mapping relationship between coolant temperature, coolant density, coolant cavitation fraction, Doppler temperature and neutron cross-section change, the neutron cross-section of the second coolant temperature, second coolant density, second coolant cavitation fraction and second Doppler temperature in the second cooling parameters is determined for the current cycle operation.

4. The method according to claim 2, characterized in that, Based on the second power distribution, the first cooling parameters of the coolant are determined, including: Based on the second power distribution, a coolant energy conservation model is constructed; the coolant energy conservation model characterizes the relationship between coolant density, linear power density, channel flow area, coolant mass flow rate and coolant specific enthalpy at the axial position; The coolant energy conservation model is discretized using the central difference method; Based on the discretized coolant energy conservation model, the equilibrium vapor content of the coolant and the first coolant density at the axial position are determined. The first coolant temperature at the starting point of bubble detachment from the wall is determined based on the correlation mapping relationship between the specific heat capacity of the coolant liquid phase at constant pressure, the thermal conductivity of the liquid phase, the heat flux density, the thermal equivalent diameter, the mass flow rate, and the coolant temperature at the starting point of bubble detachment from the wall. Based on the Ahmad method or the Levy method, the true vapor content is determined according to the equilibrium vapor content at the starting point of the bubble detachment from the wall. Based on the correlation mapping relationship between the true vapor content, the vapor saturation density of the coolant, the liquid saturation density of the coolant, the correction factor, the mass flow rate of the coolant, and the cavitation fraction of the coolant, the first cavitation fraction of the coolant corresponding to the true vapor content is determined.

5. The method according to any one of claims 1 to 4, characterized in that, The determination of the initial neutron flux distribution at the gate level and the initial effective multiplication factor of the core includes: The neutron transport model is determined based on the correlation mapping relationship between the total order of the reactor, the neutron flux of adjacent orders, the concentration of delayed neutron precursor nuclei, the decay constant, the delayed neutron fraction, the fission cross section and the effective multiplication coefficient. From the neutron transport model, an odd-order general quantum model composed of odd-order terms of odd order is determined; Based on the odd-order term flux quantum model, the even-order terms with even order in the neutron transport model are replaced to obtain the even-order term flux model. The even-order flux model is discretized using the finite difference method. The initial neutron flux distribution and the initial effective multiplication coefficient are determined based on the even-order multi-group neutron flux in the even-order flux model after discretization.

6. The method according to any one of claims 2 to 4, characterized in that, Determining the parameter difference between the predicted coupling parameters of each loop operation and the predicted coupling parameters of the previous loop operation includes: Determine the difference in neutron flux distribution between the current cycle and the previous cycle. In addition, determine the difference in multiplication coefficient between the effective multiplication coefficient of the current cycle and the effective multiplication coefficient of the previous cycle; In addition, determine the density difference between the coolant density of the current cycle and the coolant density of the previous cycle; In addition, determine the Doppler temperature difference between the fuel Doppler temperature in this cycle and the fuel Doppler temperature in the previous cycle.

7. The method according to any one of claims 2 to 4, characterized in that, The determination of the first Doppler temperature of the fuel includes: A fuel temperature thermal conductivity model is constructed based on the fuel radial temperature and the specific heat capacity, material density, material thermal conductivity, volumetric heat flux density, and area factor of the material. Based on the aforementioned fuel temperature thermal conductivity model, the radial temperature distribution of the fuel; The first Doppler temperature is determined based on the temperature mapping relationship between the fuel pellet center temperature and the fuel pellet surface temperature and the radial temperature distribution.

8. A reactor core grid-level nuclear thermal steady-state coupling determination apparatus for performing the reactor core grid-level nuclear thermal steady-state coupling determination method as described in any one of claims 1 to 7, characterized in that, The device includes: The determination unit is configured to determine the initial neutron flux distribution at the gate level and the initial effective multiplication factor of the core; The coupling unit is configured to use the initial neutron flux distribution and the initial effective multiplication coefficient as the initial coupling parameters corresponding to the first prediction, and sequentially perform preset operations to obtain the predicted coupling parameters for each cycle operation, and determine the parameter difference between the predicted coupling parameters of each cycle operation and the predicted coupling parameters of the previous cycle operation, until it is detected that the parameter difference is less than the corresponding predicted parameter difference, and the reactor with the predicted coupling parameters corresponding to the parameter difference being less than the predicted parameter difference is determined as a steady-state reactor; The preset operation includes: determining the neutron flux distribution and effective multiplication coefficient of the current cycle operation based on the neutron cross section of the previous cycle operation; determining the thermal-hydraulic parameters of the current cycle operation based on the neutron flux distribution obtained in the current cycle operation; determining the coolant density and fuel Doppler temperature in the neutron flux distribution, effective multiplication coefficient, and thermal-hydraulic parameters of the current cycle operation as the predicted coupling parameters of the current cycle operation; and determining the neutron cross section of the current cycle operation based on the predicted coupling parameters of the current cycle operation.

9. A reactor core grid-level nuclear thermal steady-state coupling determination system, characterized in that, The system is configured to perform the reactor core grid-level nuclear thermal steady-state coupling determination method as described in any one of claims 1-7.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is able to perform the reactor core grid-level nuclear thermal steady-state coupling determination method as described in any one of claims 1-7.

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