Method and device for reactor physics thermal-hydraulic coupling calculation, and electronic equipment

Abstract

The present disclosure provides a reactor physics-thermal coupling calculation method and device and electronic equipment, wherein according to a preset power distribution of a reactor, a temperature distribution and a density distribution of a coolant of the reactor are determined; whether a first iteration process is performed on the temperature distribution and the density distribution is determined based on a first preset convergence criterion; in a case where it is determined that the first iteration process is performed on the temperature distribution and the density distribution, the temperature distribution and the density distribution are updated according to a result of the first iteration process; and a power distribution of the reactor is determined based on the updated temperature distribution and the density distribution. Compared with the related art, the calculation method provided by the present disclosure can reduce the number of coupling iteration calculations and improve the calculation efficiency of reactor physics-thermal coupling calculation.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a method, apparatus, and electronic equipment for reactor physics-thermal coupling calculation. Background Technology

[0002] Traditional reactor physics-thermal coupling methods employ Picard iteration, which is essentially a simple alternation of Monte Carlo (hereinafter referred to as "Monte Carlo") neutron transport physics calculations and thermal-hydraulic calculations. For example... Figure 1 As shown, neutron transport physics calculations obtain the reactor's thermal power distribution and transmit it to thermal-hydraulic calculations. The thermal-hydraulic calculations then calculate the distribution of thermal parameters such as reactor temperature and coolant density based on the power distribution. These thermal parameters are transmitted to the neutron transport physics calculation module, which updates the reaction cross-section data based on the thermal parameters and performs transport calculations again to obtain a new power distribution. This constitutes an iterative process. The iteration cycle terminates when the difference in power distribution between two adjacent iterations is less than a preset value.

[0003] Since the Picard iterative method has a first-order convergence rate, the convergence of this iterative process requires repeated coupled iterations, that is, many Monte Carlo neutron transport calculations and thermal-hydraulic calculations, which in turn require a large amount of computational resources. In addition, the Picard iterative process is subject to certain oscillations, which need to be suppressed by relaxation methods, which also brings additional computational costs. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and electronic equipment for reactor physics-thermal coupling calculations. Its main objective is to improve the efficiency of reactor physics-thermal coupling calculations.

[0005] According to a first aspect of this disclosure, a method for reactor physics-thermal coupling calculation is provided, comprising:

[0006] The temperature distribution and coolant density distribution of the reactor are determined based on the preset power distribution of the reactor.

[0007] The power distribution of the reactor is updated based on the temperature distribution and the density distribution.

[0008] Based on the first preset convergence criterion and the power distribution before and after the update, determine whether to perform the first iterative processing on the temperature distribution and the density distribution;

[0009] If it is determined that the temperature distribution and the density distribution are subjected to the first iterative processing, the temperature distribution and the density distribution are updated according to the result of the first iterative processing;

[0010] The power distribution of the reactor is determined based on the updated temperature distribution and density distribution.

[0011] Optionally, after determining whether to perform a first iterative process on the temperature distribution and the density distribution based on a first preset convergence criterion and the power distribution before and after the update, the method further includes:

[0012] If it is determined that the first iterative process is not performed on the temperature distribution and the density distribution, the power distribution of the reactor is determined based on the temperature distribution and the density distribution.

[0013] Optionally, performing the first iterative process on the temperature distribution and the density distribution includes:

[0014] Based on the temperature distribution and the density distribution, the power distribution and the first preset matrix of the reactor are determined;

[0015] Based on the first preset matrix, the power distribution, the temperature distribution, and the density distribution are subjected to a second iterative process until the second iterative process converges.

[0016] After the second iteration process is completed, the power distribution of the reactor is updated based on the temperature distribution and the density distribution;

[0017] Based on the first preset convergence criterion and the power distribution before and after the update, it is determined whether the result of the first iteration process has converged, and whether to continue the first iteration process.

[0018] Optionally, determining the power distribution of the reactor and the first preset matrix based on the temperature distribution and the density distribution includes:

[0019] The reactor's reaction cross-section data are updated based on the temperature distribution and the density distribution.

[0020] Based on the reaction cross-section data, neutron transport calculations are performed on the reactor to obtain the power distribution;

[0021] Based on the preset iterative relationship, the temperature distribution, and the density distribution, the first preset matrix is ​​generated; wherein, the preset iterative relationship is an iterative relationship generated according to a preset iterative method.

[0022] Optionally, the step of performing a second iterative process on the power distribution, temperature distribution, and density distribution based on the first preset matrix until the second iterative process converges includes:

[0023] The power distribution is calculated and updated based on the first preset matrix, the temperature distribution, and the density distribution;

[0024] Based on the updated power distribution, thermal-hydraulic calculations are performed on the reactor to obtain the updated temperature distribution and density distribution;

[0025] Based on the second preset convergence criterion, it is determined whether the result of the second iteration process has converged, and based on the result of the second iteration process, it is determined whether to continue the second iteration process.

[0026] Optionally, determining whether to continue the second iteration based on the result of the second iteration includes:

[0027] Based on the norm of the rate of change of the power distribution between two consecutive second iterations, determine whether the second iteration process has converged.

[0028] If the result of the second iteration is determined to be non-convergent, the second iteration is continued until the result of the second iteration converges.

[0029] If the result of the second iteration is determined to be converged, the second iteration process is terminated.

[0030] The second preset convergence criterion is:

[0031]

[0032] Where p is the power distribution obtained in the second iteration, n is the number of the first iteration, m is the number of the second iteration, i is the region number corresponding to the current power distribution value, and N is the total number of regions in the entire example; ∈ internal L2 is the preset convergence threshold of the second preset convergence criterion, and L2 is the second norm of the power distribution p.

[0033] Optionally, determining whether the result of the first iterative processing has converged based on the first preset convergence criterion, and determining whether to continue the first iterative processing based on the result of the first iterative processing, includes:

[0034] Based on the effective multiplication factor between two adjacent first iterations and the norm of the rate of change of the power distribution between two adjacent iterations, it is determined whether the first iteration converges.

[0035] If it is determined that the result of the first iteration process does not converge, the first iteration process is continued until the result of the first iteration process converges.

[0036] If the result of the first iteration is determined to be converged, the first iteration process is terminated.

[0037] The first preset convergence criterion is:

[0038]

[0039] Where k is the effective proliferation factor, and its subscript n is the number of the current first iteration, ∈ k Here, N is the preset convergence threshold for the first preset convergence criterion, p is the total number of regions in the entire example, n is the power distribution obtained in the first iteration, and i is the region number corresponding to the power distribution value. extermal L2 is the preset convergence threshold of the first preset convergence criterion, and L2 is the second norm of the power distribution p.

[0040] or,

[0041] Where p is the power distribution obtained during the second iteration in the first iteration, n is the number of the first iteration, m is the number of the second iteration, i is the region number corresponding to the power distribution value, and L2 is the second norm of the power distribution p.

[0042] According to a second aspect of this disclosure, an apparatus for reactor physics-thermal coupling calculation is provided, comprising:

[0043] The first determining unit is used to determine the temperature distribution and coolant density distribution of the reactor based on the preset power distribution of the reactor.

[0044] The first update unit is used to update the power distribution of the reactor based on the temperature distribution and the density distribution;

[0045] The second determining unit is used to determine whether to perform a first iterative process on the temperature distribution and the density distribution based on a first preset convergence criterion and the power distribution before and after the update.

[0046] The second updating unit is used to update the temperature distribution and the density distribution according to the result of the first iteration process when it is determined that the first iteration process has been performed on the temperature distribution and the density distribution.

[0047] The third determining unit is used to determine the power distribution of the reactor based on the updated temperature distribution and density distribution.

[0048] Optionally, the device further includes:

[0049] The fourth determining unit is configured to determine the power distribution of the reactor based on the temperature distribution and the density distribution if the second determining unit determines that the first iterative processing is not performed on the temperature distribution and the density distribution.

[0050] Optionally, the second determining unit includes:

[0051] The first determining module is used to determine the power distribution of the reactor and a first preset matrix based on the temperature distribution and the density distribution;

[0052] The processing module is used to perform a second iterative process on the power distribution, the temperature distribution, and the density distribution based on the first preset matrix until the second iterative process converges.

[0053] An update module is used to update the power distribution of the reactor based on the temperature distribution and the density distribution after the second iteration process ends;

[0054] The second determining module is used to determine whether the result of the first iterative processing has converged based on the first preset convergence criterion and the power distribution before and after the update, and to determine whether to continue the first iterative processing.

[0055] Optionally, the first determining module is further configured to:

[0056] The reactor's reaction cross-section data are updated based on the temperature distribution and the density distribution.

[0057] Based on the reaction cross-section data, neutron transport calculations are performed on the reactor to obtain the power distribution;

[0058] Based on the preset iterative relationship, the temperature distribution, and the density distribution, the first preset matrix is ​​generated; wherein, the preset iterative relationship is an iterative relationship generated according to a preset iterative method.

[0059] Optionally, the processing module is further configured to:

[0060] The power distribution is calculated and updated based on the first preset matrix, the temperature distribution, and the density distribution;

[0061] Based on the updated power distribution, thermal-hydraulic calculations are performed on the reactor to obtain the updated temperature distribution and density distribution;

[0062] Based on the second preset convergence criterion, it is determined whether the result of the second iteration process has converged, and based on the result of the second iteration process, it is determined whether to continue the second iteration process.

[0063] Optionally, the processing module is further configured to:

[0064] Based on the norm of the rate of change of the power distribution between two consecutive second iterations, determine whether the second iteration process has converged.

[0065] If the result of the second iteration is determined to be non-convergent, the second iteration is continued until the result of the second iteration converges.

[0066] If the result of the second iteration is determined to be converged, the second iteration process is terminated.

[0067] The second preset convergence criterion is:

[0068]

[0069] Where p is the power distribution obtained in the second iteration, n is the number of the first iteration, m is the number of the second iteration, i is the region number corresponding to the current power distribution value, and N is the total number of regions in the entire example; ∈ internal L2 is the preset convergence threshold of the second preset convergence criterion, and L2 is the second norm of the power distribution p.

[0070] Optionally, the second determining module is further configured to:

[0071] Based on the effective multiplication factor between two adjacent first iterations and the norm of the rate of change of the power distribution between two adjacent iterations, it is determined whether the first iteration converges.

[0072] If it is determined that the result of the first iteration process does not converge, the first iteration process is continued until the result of the first iteration process converges.

[0073] If the result of the first iteration is determined to be converged, the first iteration process is terminated.

[0074] The first preset convergence criterion is:

[0075]

[0076] Where k is the effective proliferation factor, and its subscript n is the number of the current first iteration, ∈ k Here, N is the preset convergence threshold for the first preset convergence criterion, p is the total number of regions in the entire example, n is the power distribution obtained in the first iteration, and i is the region number corresponding to the power distribution value. external L2 is the preset convergence threshold of the first preset convergence criterion, and L2 is the second norm of the power distribution p.

[0077] or,

[0078] Where p is the power distribution obtained during the second iteration in the first iteration, n is the number of the first iteration, m is the number of the second iteration, i is the region number corresponding to the power distribution value, and L2 is the second norm of the power distribution p.

[0079] According to a third aspect of this disclosure, an electronic device is provided, comprising:

[0080] At least one processor; and

[0081] A memory communicatively connected to the at least one processor; wherein,

[0082] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0083] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0084] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0085] This disclosure provides a method, apparatus, and electronic device for reactor physics-thermal coupling calculation. The method involves determining the temperature distribution and coolant density distribution of the reactor based on a preset power distribution; updating the power distribution of the reactor based on the temperature and density distributions; determining whether to perform a first iterative process on the temperature and density distributions based on a first preset convergence criterion and the power distributions before and after the update; updating the temperature and density distributions based on the result of the first iterative process if it is determined to perform the first iterative process; and determining the power distribution of the reactor based on the updated temperature and density distributions. Compared with related technologies, the calculation method provided in this disclosure can reduce the number of calculations in the coupled iterative calculation and improve the computational efficiency of reactor physics-thermal coupling calculation.

[0086] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0087] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0088] Figure 1 A schematic flowchart illustrating a method for reactor physics-thermal coupling calculation provided in an embodiment of this disclosure;

[0089] Figure 2 A schematic flowchart of another method for reactor physics-thermal coupling calculation provided in an embodiment of this disclosure;

[0090] Figure 3 A flowchart of a method for reactor physics thermal-engineering coupling calculation based on Newton's iteration method;

[0091] Figure 4 A schematic diagram of a device for reactor physics-thermal coupling calculation provided in an embodiment of this disclosure;

[0092] Figure 5 A schematic diagram of the structure of another apparatus for reactor physics-thermal coupling calculation provided in an embodiment of this disclosure;

[0093] Figure 6 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0094] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0095] The following description, with reference to the accompanying drawings, describes a method, apparatus, and electronic equipment for reactor physics-thermal coupling calculations according to embodiments of the present disclosure.

[0096] Figure 1 This is a flowchart illustrating a method for reactor physics-thermal coupling calculation provided in an embodiment of this disclosure.

[0097] like Figure 1 As shown, the method includes the following steps:

[0098] Step 101: Determine the temperature distribution and coolant density distribution of the reactor based on the preset power distribution of the reactor.

[0099] In the embodiments of this disclosure, the preset power distribution is assumed based on the power distribution generated by the reactor. The reactor physical-thermal coupling system mainly involves two physical processes: neutron transport and thermal fluid (specifically thermal hydraulics in reactors using water as a moderator). In terms of thermal hydraulics, the mass, momentum, and energy conservation equations need to be solved, where the heat source term in the energy conservation equation actually originates from the heat generated by neutron transport. Based on the preset power distribution, thermal hydraulic calculations are performed to obtain the thermal parameter distribution (including but not limited to the reactor temperature distribution and coolant density distribution).

[0100] Step 102: Update the power distribution of the reactor based on the temperature distribution and the density distribution.

[0101] The basic idea behind reactor physics-thermal coupling calculations is to connect the original neutron transport calculations and thermal-hydraulic calculations in a specific order, executing them alternately and exchanging data. Those skilled in the art will understand that in Picard iterations, the exchanged data is the direct result obtained from one module of the coupled system. Because thermal feedback in a reactor is a negative feedback effect, the deviation between the power distribution and other distribution quantities during the iteration process and the actual converged solution will oscillate positively and negatively. In some cases, the amplitude may even gradually increase, leading to non-convergence.

[0102] In the embodiments of this disclosure, the power distribution of the reactor can be obtained by performing neutron transport calculations on the temperature distribution and coolant density distribution, thereby enabling the power distribution to be updated. By alternately performing calculations on the preset power distribution using thermal-hydraulic calculations and neutron transport calculations, data can be exchanged between them.

[0103] Step 103: Based on the first preset convergence criterion and the power distribution before and after the update, determine whether to perform the first iterative processing on the temperature distribution and the density distribution.

[0104] In the embodiments of this disclosure, the transmitted data is processed using the Newton iteration method, which essentially utilizes the Jacobian matrix, to bring it closer to the convergent solution. This accelerates the coupled iteration process, reduces the number of iterations, and also lowers the oscillation amplitude of the coupled iteration. The first iterative processing is based on the iterative processing method generated by the Newton iteration method; the first preset convergence criterion is a preset relational formula used to determine whether the first iterative processing has converged, and is a convergence criterion for determining when the first iterative processing can break out of the loop. The first preset convergence criterion determines whether convergence has occurred based on the values ​​of the power distribution before and after the update.

[0105] Step 104: If it is determined that the temperature distribution and the density distribution have undergone the first iterative processing, update the temperature distribution and the density distribution according to the result of the first iterative processing.

[0106] In the embodiments of this disclosure, after the first iteration process is completed according to the first preset convergence criterion, the temperature distribution and coolant density distribution of the reactor are updated based on the results of the first iteration process. The temperature and density distributions obtained through the first iteration process can better describe the thermal parameters of the reactor compared to the temperature and density distributions before the iteration process, providing more accurate data for subsequent calculations.

[0107] Step 105: Determine the power distribution of the reactor based on the updated temperature distribution and density distribution.

[0108] In the embodiments of this disclosure, after obtaining the temperature distribution and density distribution according to the first iteration process, the reactor's reaction cross-section data are updated according to the updated temperature distribution and density distribution, and the reactor's power distribution is obtained through neutron transport calculation.

[0109] This disclosure provides a method for coupled thermal-physical calculations of a reactor. The method involves determining the temperature distribution and coolant density distribution of the reactor based on a preset power distribution; updating the power distribution of the reactor based on the temperature and density distributions; determining whether to perform a first iterative process on the temperature and density distributions based on a first preset convergence criterion and the power distributions before and after the update; if the first iterative process is performed, updating the temperature and density distributions based on the result of the first iterative process; and determining the power distribution of the reactor based on the updated temperature and density distributions. Compared with related technologies, the calculation method provided in this disclosure can reduce the number of calculations in coupled iterative calculations and improve the computational efficiency of coupled thermal-physical calculations of reactors.

[0110] To clearly illustrate the embodiments of this disclosure, a flowchart of another method for reactor physics-thermal coupling calculation is provided.

[0111] like Figure 2 As shown, the method includes the following steps:

[0112] Step 201: Determine the temperature distribution and coolant density distribution of the reactor based on the preset power distribution of the reactor.

[0113] Specifically, in the embodiments disclosed herein, thermal-hydraulic calculations are performed based on the preset power distribution of the reactor to solve the mass, momentum, and energy conservation equations; the heat source term in the energy conservation equation is calculated based on the preset power distribution.

[0114] Step 202: Based on the temperature distribution and the density distribution, determine the power distribution and the first preset matrix of the reactor.

[0115] As a refinement of an embodiment of this disclosure, determining the power distribution and the first preset matrix of the reactor based on the temperature distribution and the density distribution includes: updating the reactor's reaction cross-section data according to the temperature distribution and the density distribution; performing neutron transport calculations on the reactor based on the reaction cross-section data to obtain the power distribution; and generating the first preset matrix based on a preset iterative relationship, the temperature distribution, and the density distribution; wherein the preset iterative relationship is an iterative relationship generated according to a preset iterative method.

[0116] Specifically, in the embodiments of this disclosure, the reactor's reaction cross-section data are updated based on the obtained reactor temperature distribution and coolant density distribution, and the reactor's power distribution is obtained through neutron transport calculations.

[0117] The preset iterative relationship is derived from the Newton iterative method, and the first preset matrix is ​​the Jacobian matrix based on the preset iterative relationship. The derivation process is as follows: In a reactor physics-thermal coupling system, the main physical processes are neutron transport and thermal fluid (specifically thermal hydraulics in water-moderated reactors). Regarding neutron transport, the Boltzmann equations actually need to be solved.

[0118]

[0119] Where Ω is the direction vector, φ is the neutron fluence rate distribution, and ∑ t (r,E) represents the macroscopic total reaction cross section of a neutron with energy E at position r, Σ s (r,Ω·Ω′,E→E′) represents the macroscopic scattering reaction cross section at position r, where the neutron energy changes from E to E′ and the direction variable changes from Ω to Ω′; χ(r,E) represents the probability that the neutron produced after the fission reaction of the neutron at position r has energy E; v(E′) is the average number of neutrons produced by the fission reaction of the neutron with energy E′; Σ f (r,E′) represents the macroscopic fission reaction cross section of a neutron with energy E′ at position r.

[0120] Its operator form is as follows:

[0121]

[0122] Where L, R, and F are the leakage operator, removal operator, and fission operator, respectively, and φ is the neutron fluence rate distribution. These operators are related to the corresponding macroscopic cross-sections, which are in turn affected by thermal parameters such as temperature and density fields. Therefore, the equation can be expressed as:

[0123] Ψ θ (φ)=0——(3)

[0124] Where θ represents the thermal parameters and Ψ represents the neutron transport equation.

[0125] Furthermore, since the power distribution p must also be determined when the model and neutron fluence rate distribution φ are fixed, the above equation can also be expressed as:

[0126] Ψ θ (p)=0——(4)

[0127] In thermal hydraulics, the equations for the conservation of mass, momentum, and energy need to be solved. The heat source term in the energy conservation equation actually originates from the heat generated by neutron transport, i.e., the heat power distribution p, and can therefore be expressed as:

[0128] Θ P (θ)=0——(5)

[0129] Where Θ represents the conservation equation of thermal hydraulics, and p represents the thermal power distribution.

[0130] Furthermore, if we express equations (4) and (5) in the form of solutions, that is...

[0131] p = Ψ * (θ)——(6)

[0132] θ=Θ * (p)——(7)

[0133] These two equations represent the neutron transport process Ψ given the thermal parameter distribution θ. * The power distribution solution p can be given; after providing the power distribution p, the thermal calculation process Θ... * The distribution of thermal parameters θ can be given.

[0134] Therefore, we can construct an iterative relation:

[0135] φ n+1 =Ψ * (Θ * (φ n ))=G(φ n )——(8)

[0136] Where G is the iteration operator, and G(·) is equivalent to Ψ. *(Θ * (·)).

[0137] To achieve a higher convergence rate, the Newton iteration method should be used. A more efficient second-order convergent iterative solution method within the Newton iteration method is to calculate the residual of formula (8) and update φ using the residual, i.e.

[0138] r = Ψ * (Θ * (φ n ))-φ n ——(9)

[0139] J G δ φ =-r——(10)

[0140] φ n+1 =φ n +δ φ ——(11)

[0141] Where r is the residual vector of the neutron flux rate calculation result in this iteration, J G Let δ be the Jacobian matrix of operator G. φ Let n be the solution vector of the residual equation (10), and let n be the subscript of the neutron fluence rate φ, representing the iteration. n Let J be the neutron flux rate calculated in the nth iteration. If the neutron flux rate φ is discretized into N regions, then J... G Let G be an N×N matrix. The iterative process constructed in (9)-(11) is a second-order convergent iterative process using the Newton method with Jacobian matrix. It can be understood as using the partial derivative information of operator G to guide the optimal direction and magnitude of iterative optimization, thereby accelerating the convergence process.

[0142] J G This can be written as the product of two Jacobian matrices representing neutron transport and thermohydraulics, i.e.

[0143]

[0144] in, Here is the Jacobian matrix for neutron transport processes. This is the Jacobian matrix for the thermal-hydraulic calculation process. M is the total number of all thermal parameters θ in N regions. Each subscript of power p represents the corresponding region number, and each subscript of thermal parameter θ represents the corresponding thermal parameter sequence number.

[0145] Among them, the Jacobian matrix of the neutron transport process The source perturbation algorithm can be used to directly obtain the Jacobian matrix for thermal applications. The matrix still needs to be calculated using the difference method. The product of the power difference vector is used, but the Krylov subspace is no longer used when solving (10). Instead, the eigenmodes represented by the eigenvectors of the iterative fission matrix are used for spatial decomposition. Since the statistical error of the eigenvectors of the first few eigenvalues ​​is relatively small, the influence of the Monte Carlo statistical uncertainty is reduced. However, a series of assumptions are made in this algorithm process, including only considering the coolant density feedback (i.e., there is only coolant density distribution in θ, no fuel rod temperature, coolant temperature distribution, etc.), and all power comes from the fission reaction, etc., so there is a certain degree of approximation of the results. In addition, although this method reduces the number of neutron transport calculations in a single coupling iteration to 1, it still cannot avoid the need to perform N thermal differential calculations in each iteration. The advantages of this technical solution are that it supports more comprehensive and accurate thermal feedback, achieves smaller computational load in a single coupling iteration, and has more efficient coupling iteration calculation.

[0146] Step 203: Based on the first preset matrix, perform a second iterative process on the power distribution, the temperature distribution, and the density distribution until the second iterative process converges.

[0147] As one possible implementation of this disclosure, the step of performing a second iterative process on the power distribution, temperature distribution, and density distribution based on the first preset matrix until the second iterative process converges includes: calculating and updating the power distribution based on the first preset matrix, the temperature distribution, and the density distribution; performing thermal-hydraulic calculations on the reactor based on the updated power distribution to obtain the updated temperature distribution and the density distribution; determining whether the result of the second iterative process has converged based on a second preset convergence criterion, and determining whether to continue the second iterative process based on the result of the second iterative process.

[0148] For specific embodiments in this disclosure, please refer to Figure 3 The iterative relational reasoning for the second iteration is as follows:

[0149] In the second iteration, the Jacobian matrix of the neutron transport component is used. Refined thermal parameter value θ n+1 This allows the Jacobian matrix to accelerate the entire iterative process. Specifically, the initial values ​​for the second iteration are first given during the first iteration (e.g., ...). Figure 3 (Temperature and density distribution in the previous iteration):

[0150] p n =Ψ * (θ n )——(13)

[0151] p n,0 =p n ——(14)

[0152] θ n,0 =θ n _(15)

[0153] In equations (14) and (15), n, 0, n is the number of the first iteration, 0 is the number of the second iteration, p is the power distribution, and θ is the distribution of thermal parameters such as temperature and density.

[0154] Then, calculate the updated power distribution p. n,0 thermal parameter distribution

[0155] θ n,1 =Θ * (p n,0 )_(16)

[0156] Next, using p n Jacobian matrix of the neutron transport part at the location Update power distribution

[0157]

[0158] in This is the updated power distribution. Further, the updated power distribution can be normalized.

[0159]

[0160] Where p n,1 This is the updated power distribution after normalization.

[0161] Then, this power distribution can be used to obtain the updated thermal parameter distribution, thus constituting the second iterative process.

[0162] θ n,j+1 =Θ * (p j,j )——(19)

[0163]

[0164]

[0165] Where j is the number of the second iteration.

[0166] The second iterative process represented by (19)(20)(21) is actually the high-dimensional straight line φ=J in N-dimensional space. pn (θ-θn,j )+φ n,j The intersection process with the thermal equation (7) is highly efficient in the high-dimensional plane intersection iteration process, thus enabling the calculation of thermal parameters θ during the second iteration. n+1 Refinement is performed to accelerate convergence.

[0167] Jacobian matrix The items in the middle are In the Monte Carlo neutron transport process, the derivative of power with respect to temperature and density at a certain state of the system can be solved using the differential operator method, thereby completely solving the matrix. The process is briefly described below:

[0168] The power count during neutron transport is estimated by the following formula.

[0169]

[0170] Where p i,j Let f be the probability of the j-th track of the i-th neutron, and let f be the particle transport correlation quantity. i,j p represents the power generated by this track, where N is the total number of tracks in the transport process. i,j It can be further broken down into:

[0171]

[0172] Where S is the probability that the parent neutron produces the i-th neutron in a specific phase space after fission. This phase space is determined by the position vector R0, the energy value E0, and the direction vector Ω0. The subscript 0 of these three variables indicates that each variable is related to the initial parent neutron; r m Let r be the probability of the m-th track appearing given that the first m-1 tracks have already appeared. m It can be further decomposed into transport term T m and collision term C m :

[0173] r m =T m (R m-1 →R m E m-1 ,Ω m-1 C m (R m E m-1 →E m ,Ω m-1 →Ω m )——(24) where T m (R m-1 →R m E m-1 ,Ω m-1This indicates that, given the first m-1 tracks have already appeared, the neutron energy is E. m-1 The direction of motion is Ω m-1 During the m-th track, the position changes from R m-1 Move to R m The probability of C; m (R m E m-1 →E m ,Ω m-1 →Ω m This indicates that, given the first m-1 tracks have already appeared, after transporting from R... m-1 Move to R m A collision occurred, causing the neutron energy to change from E m-1 Change to E m And the direction of motion is from Ω m-1 Transform into Ω m The probability of.

[0174] Therefore, the derivative of power P with respect to temperature T is:

[0175]

[0176] Similarly, the derivative of power P with respect to density ρ is:

[0177]

[0178] Where w i,j To add weight, although the two equations above have the same form, the specific statistical content will differ under different perturbation parameters (such as temperature or density). i,j The following formula can be used for statistical calculations.

[0179]

[0180] Therefore, the Jacobian matrix for neutron transport is... All parameters can be solved. For large-scale examples, the matrix... If the scale is relatively large, then regional merging can be considered to accelerate the iteration process by utilizing the partial derivative relationships between blocks.

[0181] Therefore, the Jacobian matrix for neutron transport is... In this context, the partial derivatives of power with respect to all thermal parameters such as temperature and density can be obtained through counting and statistics. When the power distribution is discretized into N regions, the total number of perturbation coefficients (partial derivatives) that need to be statistically analyzed is 2N. 2 The counting and statistics of these perturbation coefficients require a certain amount of additional statistical time during transport, but this can be further optimized using the methods described in the next section, thereby further reducing the time required for neutron transport calculations.

[0182] As a refinement of an embodiment of this disclosure, the step of determining whether to continue the second iteration process based on the result of the second iteration process includes: determining whether the second iteration process has converged based on the norm of the rate of change of the power distribution between two adjacent iterations; if it is determined that the result of the second iteration process has not converged, continuing the second iteration process until the result of the second iteration process converges; if it is determined that the result of the second iteration process has converged, ending the second iteration process.

[0183] The second preset convergence criterion is:

[0184]

[0185] Where p represents the power distribution obtained during the second iteration, and its three subscripts represent the current first iteration number, the second iteration number, and the region number corresponding to the power distribution value, respectively. For example, p n,m,i This represents the power value of region i obtained in the m-th iteration of the first iteration process; N is the total number of regions in the entire example; ∈ internal The preset convergence threshold for the second preset convergence criterion is a method parameter, generally related to the standard deviation of the power statistics; L2 is the letter representation of the second norm of the power distribution p, in this formula... The specific calculation form is the radical expression after the first equal sign.

[0186] Specifically, based on the second preset convergence criterion, it is determined whether to continue the second iteration; the convergence criterion for the second iteration process is measured by the L2 norm of the power distribution change rate between two adjacent iterations.

[0187]

[0188] At that point, it is considered that the second iteration has converged.

[0189] First iteration processing, second iteration processing ∈ k ,∈ external ,∈ internal The setting is based on the average relative standard deviation of the power calculation results. In practical use, since the second iteration process converges more efficiently, a fixed number of iterations can be set for the second iteration process.

[0190] Furthermore, if the first calculation result of the second iteration already satisfies the convergence criterion, then it must be true that:

[0191]

[0192] If the thermal parameters have converged, or the changes in thermal parameters have little impact on the neutron transport module, then neutron transport has actually converged. Even if the thermal parameters have not converged, due to their orthogonality with neutron transport Jφ(n), there is little point in continuing the iteration, so the iteration process can also be terminated.

[0193] Step 204: After the second iteration process ends, update the power distribution of the reactor based on the temperature distribution and the density distribution.

[0194] Step 205: Based on the first preset convergence criterion and the power distribution before and after the update, determine whether the result of the first iteration process has converged, and determine whether to continue the first iteration process.

[0195] As one possible implementation of this disclosure, determining whether the result of the first iterative process converges based on the first preset convergence criterion, and determining whether to continue the first iterative process based on the result of the first iterative process, includes: determining whether the first iterative process converges based on the effective multiplication factor between two adjacent iterative processes and the norm of the rate of change of the power distribution between two adjacent iterations; if it is determined that the result of the first iterative process does not converge, continuing the first iterative process until the result of the first iterative process converges; if it is determined that the result of the first iterative process converges, ending the first iterative process.

[0196] The first preset convergence criterion is:

[0197]

[0198] Where k is the effective proliferation factor of the system, and its subscript is the current iteration number, for example, k n Represents the effective proliferation factor calculated during the first iteration in the nth iteration; ∈ k The preset convergence threshold for the first preset convergence criterion is a method parameter, generally related to the standard deviation of the effective proliferation factor k; N is the total number of regions in the entire example; p is the power distribution obtained in the first iteration, where its two subscripts represent the current first iteration number and the region number corresponding to the power distribution value, respectively. For example, p n,i This represents the power value of region i obtained in the nth iteration of the first process; N is the total number of regions in the entire example. external is the preset convergence threshold for the first preset convergence criterion, a method parameter generally related to the standard deviation of the power statistics; L2 is the letter representation of the second norm of the power distribution p, in this formula... The specific calculation form is the radical expression after the first equal sign;

[0199] or,

[0200] Where p represents the power distribution obtained during the second iteration in the first iteration, and its three subscripts represent the current first iteration number, the second iteration number, and the region number corresponding to the power distribution value, respectively. For example, p n,m,i Let represent the power value of the i-th region obtained in the m-th second iteration during the n-th first iteration; L2 is the letter representation of the second norm of the power distribution p, in this formula... The specific calculation form is the radical expression after the first equal sign. That is, this convergence criterion uses the relative change in power distribution in the second iteration to determine the convergence of the first iteration.

[0201] For details, please continue to refer to [the website / information]. Figure 3 If the second iteration process ends, based on the result of the second iteration process and according to the first preset convergence criterion, it is determined whether to continue the first iteration process.

[0202] The first iteration process uses the total set between the two iterations (e.g., the effective growth factor k). eff In formula (30), k represents the norm of the change in the distribution quantity (such as power distribution p) and the distribution quantity (such as power distribution p) are used as convergence criteria.

[0203]

[0204]

[0205] In actual operation, using formula (32) as the convergence criterion can better reflect the convergence state of coupled iteration.

[0206]

[0207] Step 206: If it is determined that the temperature distribution and the density distribution have undergone the first iterative processing, update the temperature distribution and the density distribution according to the result of the first iterative processing.

[0208] Step 207: Determine the power distribution of the reactor based on the updated temperature distribution and density distribution.

[0209] Specifically, in the embodiments of this disclosure, after the first iteration process is completed according to the first preset convergence criterion, the temperature distribution and coolant density distribution of the reactor are updated based on the results of the first iteration process. After obtaining the temperature distribution and density distribution based on the first iteration process, the reactor's reaction cross-section data are updated based on the updated temperature distribution and density distribution, and the reactor's power distribution is obtained through neutron transport calculations.

[0210] Step 208: If it is determined that the first iterative processing is not performed on the temperature distribution and the density distribution, the power distribution of the reactor is determined based on the temperature distribution and the density distribution.

[0211] For specific embodiments in this disclosure, please refer to Figure 3 If the temperature and density distributions obtained from the thermohydraulic calculations based on the preset power distribution converge, then the neutron transport calculations can be performed using the temperature and density distributions obtained from the thermohydraulic calculations to obtain the power distribution of the reactor.

[0212] As one possible implementation of this disclosure, the neutron transport portion of the Jacobian matrix is ​​performed in step 203. In addition to the above, this disclosure also provides a computational acceleration method using "multi-diagonal" optimization. In the computation process of the Newton iterative method based on Monte Carlo perturbation theory, the main additional time consumption is 2N. 2 The counting and statistics process of each perturbation operator is involved. Therefore, to optimize the overall computation time, we need to focus on appropriately reducing the perturbation computation time.

[0213] In the actual calculations using the Newton iterative method based on Monte Carlo perturbation theory, it can be found that the Jacobian matrix for the neutron transport component is actually... The importance of elements at different locations varies. The power p in region i... i For the thermal parameters θ of region j j response The Jacobian matrix only exhibits a relatively large value when regions i and j are relatively close. Therefore, in practical calculations, the Jacobian matrix can be used. The multi-diagonal approximation is used to perform the inner iteration process, thus reducing the number of perturbation operators required for computation from O(N) to O(N). 2 The order of magnitude is reduced to the O(N) order of magnitude.

[0214] Specifically, for the regional division of a one-dimensional power distribution, if M = N in formula (12), then the positions of adjacent regions in the matrix are actually the positions of the diagonals, as shown in the following formula.

[0215]

[0216] Where d i,j express

[0217] For two-dimensional or three-dimensional power distributions, the specific form depends on how they are unfolded into one-dimensional numbering, but they are all a series of numbers equidistant from the main diagonal. For example, in a typical two-dimensional power distribution, the values ​​corresponding to the four directions are located on two secondary diagonals and four other diagonals, respectively. Including the main diagonal corresponding to the region-to-region response, a total of seven diagonals retain values.

[0218] This method has also achieved better performance than the Picard iteration in practical applications. Here, we use a physical-thermal-hydraulic coupling example of a pressurized water reactor fuel rod grid with ten axially uniform layers for verification. This example includes water, cladding, air gaps, and fuel pellets throughout the entire grid. The radial square boundary of the entire model is a total reflection boundary, and the axial end face is a vacuum boundary.

[0219] During the verification process, the method was compared with the Picard iterative method. The specific calculation parameters are shown in Table 1 below.

[0220] Table 1 Calculation parameters for pressurized water reactor fuel rod grid examples

[0221]

[0222] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0223] Corresponding to the aforementioned method for reactor physics-thermal coupling calculations, this invention also proposes an apparatus for reactor physics-thermal coupling calculations. Since the apparatus embodiments of this invention correspond to the aforementioned method embodiments, details not disclosed in the apparatus embodiments can be referred to the aforementioned method embodiments, and will not be repeated here.

[0224] Figure 4 A schematic diagram of a device for reactor physics-thermal coupling calculation provided in an embodiment of this disclosure is shown below. Figure 4 As shown,

[0225] The first determining unit 31 is used to determine the temperature distribution and coolant density distribution of the reactor based on the preset power distribution of the reactor.

[0226] The first update unit 32 is used to update the power distribution of the reactor based on the temperature distribution and the density distribution;

[0227] The second determining unit 33 is used to determine whether to perform a first iterative process on the temperature distribution and the density distribution based on the first preset convergence criterion and the power distribution before and after the update.

[0228] The second updating unit 34 is used to update the temperature distribution and the density distribution according to the result of the first iteration process when it is determined that the first iteration process is performed on the temperature distribution and the density distribution.

[0229] The third determining unit 35 is used to determine the power distribution of the reactor based on the updated temperature distribution and density distribution.

[0230] This disclosure provides an apparatus for coupled thermal-physical calculations of a reactor. Based on a preset power distribution of the reactor, the apparatus determines the temperature distribution and coolant density distribution of the reactor; based on the temperature distribution and the density distribution, it updates the power distribution of the reactor; based on a first preset convergence criterion and the power distributions before and after the update, it determines whether to perform a first iterative process on the temperature distribution and the density distribution; if it is determined that the first iterative process should be performed on the temperature distribution and the density distribution, the apparatus updates the temperature distribution and the density distribution based on the result of the first iterative process; based on the updated temperature distribution and the density distribution, it determines the power distribution of the reactor. Compared with related technologies, the calculation method provided in this disclosure can reduce the number of calculations in coupled iterative calculations and improve the computational efficiency of coupled thermal-physical calculations of reactors.

[0231] Furthermore, in one possible implementation of this embodiment, such as Figure 5 As shown, the device further includes:

[0232] The fourth determining unit 36 ​​is used to determine the power distribution of the reactor based on the temperature distribution and the density distribution when the second determining unit 33 determines that the first iterative processing is not performed on the temperature distribution and the density distribution.

[0233] Furthermore, in one possible implementation of this embodiment, such as Figure 5 As shown, the second determining unit 33 includes:

[0234] The first determining module 331 is used to determine the power distribution of the reactor and a first preset matrix based on the temperature distribution and the density distribution;

[0235] Processing module 332 is used to perform a second iterative process on the power distribution, the temperature distribution, and the density distribution based on the first preset matrix until the second iterative process converges;

[0236] The update module 333 is used to update the power distribution of the reactor based on the temperature distribution and the density distribution after the second iteration process ends.

[0237] The second determining module 334 is used to determine whether the result of the first iterative processing has converged based on the first preset convergence criterion and the power distribution before and after the update, and to determine whether to continue the first iterative processing.

[0238] Furthermore, in one possible implementation of this embodiment, the first determining module 331 is further configured to:

[0239] The reactor's reaction cross-section data are updated based on the temperature distribution and the density distribution.

[0240] Based on the reaction cross-section data, neutron transport calculations are performed on the reactor to obtain the power distribution;

[0241] Based on the preset iterative relationship, the temperature distribution, and the density distribution, the first preset matrix is ​​generated; wherein, the preset iterative relationship is an iterative relationship generated according to a preset iterative method.

[0242] Furthermore, in one possible implementation of this embodiment, the processing module 332 is further configured to:

[0243] The power distribution is calculated and updated based on the first preset matrix, the temperature distribution, and the density distribution;

[0244] Based on the updated power distribution, thermal-hydraulic calculations are performed on the reactor to obtain the updated temperature distribution and density distribution;

[0245] Based on the second preset convergence criterion, it is determined whether the result of the second iteration process has converged, and based on the result of the second iteration process, it is determined whether to continue the second iteration process.

[0246] Furthermore, in one possible implementation of this embodiment, the processing module 332 is further configured to:

[0247] Based on the norm of the rate of change of the power distribution between two consecutive second iterations, determine whether the second iteration process has converged.

[0248] If the result of the second iteration is determined to be non-convergent, the second iteration is continued until the result of the second iteration converges.

[0249] If the result of the second iteration is determined to be converged, the second iteration process is terminated.

[0250] The second preset convergence criterion is:

[0251]

[0252] Where p is the power distribution obtained in the second iteration, n is the number of the first iteration, m is the number of the second iteration, i is the region number corresponding to the current power distribution value, and N is the total number of regions in the entire example; ∈ internal L2 is the preset convergence threshold of the second preset convergence criterion, and L2 is the second norm of the power distribution p.

[0253] Furthermore, in one possible implementation of this embodiment, the second determining module 334 is further configured to:

[0254] Based on the effective multiplication factor between two adjacent first iterations and the norm of the rate of change of the power distribution between two adjacent iterations, it is determined whether the first iteration converges.

[0255] If it is determined that the result of the first iteration process does not converge, the first iteration process is continued until the result of the first iteration process converges.

[0256] If the result of the first iteration is determined to be converged, the first iteration process is terminated.

[0257] The first preset convergence criterion is:

[0258]

[0259] Where k is the effective proliferation factor, and its subscript n is the number of the current first iteration, ∈ k Here, N is the preset convergence threshold for the first preset convergence criterion, p is the total number of regions in the entire example, n is the power distribution obtained in the first iteration, and i is the region number corresponding to the power distribution value. external L2 is the preset convergence threshold of the first preset convergence criterion, and L2 is the second norm of the power distribution p.

[0260] or,

[0261] Where p is the power distribution obtained during the second iteration in the first iteration, n is the number of the first iteration, m is the number of the second iteration, i is the region number corresponding to the power distribution value, and L2 is the second norm of the power distribution p.

[0262] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0263] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0264] Figure 6 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0265] like Figure 6 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0266] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0267] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the method of reactor physics thermal coupling calculation. For example, in some embodiments, the method of reactor physics thermal coupling calculation may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured by any other suitable means (e.g., by means of firmware) to perform the aforementioned reactor physics-thermal coupling calculations.

[0268] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0269] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0270] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0271] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0272] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0273] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0274] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0275] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0276] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for reactor physics-thermal coupling calculation, characterized in that, include: Based on the preset power distribution of the reactor, the temperature distribution and coolant density distribution of the reactor are determined; The power distribution of the reactor is updated based on the temperature distribution and the density distribution. Based on the first preset convergence criterion and the power distribution before and after the update, determine whether to perform the first iterative processing on the temperature distribution and the density distribution; If it is determined that the temperature distribution and the density distribution are subjected to the first iterative processing, the temperature distribution and the density distribution are updated according to the result of the first iterative processing. The power distribution of the reactor is determined based on the updated temperature distribution and density distribution.

2. The method according to claim 1, characterized in that, After determining whether to perform a first iterative process on the temperature distribution and the density distribution based on a first preset convergence criterion and the power distribution before and after the update, the method further includes: If it is determined that the first iterative process is not performed on the temperature distribution and the density distribution, the power distribution of the reactor is determined based on the temperature distribution and the density distribution.

3. The method according to claim 1, characterized in that, The first iterative processing of the temperature distribution and the density distribution includes: Based on the temperature distribution and the density distribution, the power distribution and the first preset matrix of the reactor are determined; Based on the first preset matrix, the power distribution, the temperature distribution, and the density distribution are subjected to a second iterative process until the second iterative process converges. After the second iteration process is completed, the power distribution of the reactor is updated based on the temperature distribution and the density distribution; Based on the first preset convergence criterion and the power distribution before and after the update, it is determined whether the result of the first iteration process has converged, and whether to continue the first iteration process.

4. The method according to claim 3, characterized in that, Determining the power distribution and the first preset matrix of the reactor based on the temperature distribution and the density distribution includes: The reactor's reaction cross-section data are updated based on the temperature distribution and the density distribution. Based on the reaction cross-section data, neutron transport calculations are performed on the reactor to obtain the power distribution; Based on the preset iterative relationship, the temperature distribution, and the density distribution, the first preset matrix is ​​generated; wherein, the preset iterative relationship is an iterative relationship generated according to a preset iterative method.

5. The method according to claim 3, characterized in that, The step of performing a second iterative process on the power distribution, temperature distribution, and density distribution based on the first preset matrix until the second iterative process converges includes: The power distribution is calculated and updated based on the first preset matrix, the temperature distribution, and the density distribution; Based on the updated power distribution, thermal-hydraulic calculations are performed on the reactor to obtain the updated temperature distribution and density distribution; Based on the second preset convergence criterion, it is determined whether the result of the second iteration process has converged, and based on the result of the second iteration process, it is determined whether to continue the second iteration process.

6. The method according to claim 5, characterized in that, The step of determining whether to continue the second iteration based on the result of the second iteration includes: Based on the norm of the rate of change of the power distribution between two consecutive second iterations, determine whether the second iteration process has converged. If the result of the second iteration is determined to be non-convergent, the second iteration is continued until the result of the second iteration converges. If the result of the second iteration is determined to be converged, the second iteration process is terminated. The second preset convergence criterion is: Where p represents the power distribution obtained during the second iteration, n represents the number of the first iteration, m represents the number of the second iteration, and i represents the region number corresponding to the current power distribution value. The total number of regions in the entire example; This is the preset convergence threshold for the second preset convergence criterion. Let p be the second norm of the power distribution p.

7. The method according to claim 3, characterized in that, The step of determining whether the result of the first iteration process has converged based on the first preset convergence criterion, and determining whether to continue the first iteration process based on the result of the first iteration process, includes: Based on the effective multiplication factor between two adjacent first iterations and the norm of the rate of change of the power distribution between two adjacent iterations, it is determined whether the first iteration converges. If it is determined that the result of the first iteration process does not converge, the first iteration process is continued until the result of the first iteration process converges. If the result of the first iteration is determined to be converged, the first iteration process is terminated. The first preset convergence criterion is: Where k is the effective proliferation factor, and its subscript n is the number of the first iteration. The preset convergence threshold is the first preset convergence criterion. Let p be the total number of regions in the entire example, n be the power distribution obtained in the first iteration, i be the number of the first iteration, and i be the region number corresponding to the current power distribution value. The preset convergence threshold is the first preset convergence criterion. Let p be the second norm of the power distribution p; or, Where p represents the power distribution obtained during the second iteration in the current first iteration, n is the number of the first iteration, m is the number of the second iteration, and i is the region number corresponding to the current power distribution value. Let p be the second norm of the power distribution p.

8. An apparatus for reactor physics-thermal coupling calculations, characterized in that, include: The first determining unit is used to determine the temperature distribution and coolant density distribution of the reactor based on the preset power distribution of the reactor. The first update unit is used to update the power distribution of the reactor based on the temperature distribution and the density distribution; The second determining unit is used to determine whether to perform a first iterative process on the temperature distribution and the density distribution based on a first preset convergence criterion and the power distribution before and after the update. The second updating unit is used to update the temperature distribution and the density distribution according to the result of the first iteration process when it is determined that the first iteration process has been performed on the temperature distribution and the density distribution. The third determining unit is used to determine the power distribution of the reactor based on the updated temperature distribution and density distribution.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-7.

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