A nuclear simulation design analysis method and system based on Monte Carlo calculation

Abstract

The present invention relates to a nuclear simulation design analysis method and system based on Monte Carlo calculations, comprising: determining multiple primary factors of the nuclear simulation design analysis scheme based on a preset objective and a basic model of the nuclear simulation design analysis scheme, and constructing multiple auxiliary models of the nuclear simulation design analysis scheme based on the multiple primary factors; performing Monte Carlo calculations on the basic model and each auxiliary model separately, obtaining and fitting all first calculation results to obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a set of values ​​of the primary factors of the nuclear simulation design scheme. The present invention obtains a large number of different nuclear simulation design analysis scheme results through multiple Monte Carlo fitting of the basic model and multiple auxiliary models, thereby reducing the computational complexity of the nuclear simulation design analysis while ensuring the stability of the calculation results.

Description

Technical Field

[0001] The present invention relates to the technical field of nuclear simulation analysis, and in particular to a nuclear simulation design analysis method and system based on Monte Carlo calculation. Background Art

[0002] In nuclear and particle physics simulation design and analysis, numerous multi-parameter, multi-objective, and multi-constraint optimization problems arise, representing a significant area of ​​development for artificial intelligence (AI) methods. Currently, evolutionary algorithms are widely used. These algorithms require simultaneous particle transport analysis for numerous design scenarios, followed by iterative optimization to find the optimal solution. This applies to designs such as reactor cores and fusion tritium blankets. However, due to the complex structures and high computational accuracy requirements of many solutions, existing Monte Carlo methods pose significant computational and analysis challenges. Consequently, most current nuclear simulation designs rely solely on manual design optimization, making it difficult to achieve the optimal solution through intelligent methods.

[0003] In particle transport calculations, if the model parameters change slightly, a perturbation method can be used to obtain the calculation results of a large number of schemes after all parameter combinations change in a small number of transport calculations, so as to reduce time consumption. Currently, there are mainly related sampling methods, etc., which calculate the impact of changes in the nuclides, system structure and shape, etc. on particle motion and collision reactions in one calculation, and use this impact to correct the particle weight to obtain the impact value of the parameter change. However, the related sampling method is difficult to give the impact of the common changes between multiple parameters, and when a certain nuclide or material changes from nothing to something, it will be impossible to calculate the final statistical contribution of some particles, and the results are relatively unstable. Most other Monte Carlo calculation methods also have serious problems such as serious calculation time consumption when multiple parameters change, difficulty in applying to situations where parameters change greatly, and unstable results. Therefore, there is an urgent need to provide a technical solution to solve the above technical problems. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a nuclear simulation design analysis method and system based on Monte Carlo calculation.

[0005] The technical solution of a nuclear simulation design analysis method based on Monte Carlo calculation of the present invention is as follows:

[0006] Determining a plurality of main factors of the nuclear simulation design and analysis scheme based on a preset goal and a basic model of the nuclear simulation design and analysis scheme, and constructing a plurality of auxiliary models of the nuclear simulation design and analysis scheme based on the plurality of main factors;

[0007] Monte Carlo calculations are performed on the basic model and each auxiliary model respectively to obtain and fit all the first calculation results to obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of the main factors of the nuclear simulation design scheme.

[0008] The beneficial effects of the nuclear simulation design analysis method based on Monte Carlo calculation of the present invention are as follows:

[0009] The method of the present invention obtains a large number of different scheme results of nuclear simulation design analysis through several Monte Carlo fitting of a basic model and multiple auxiliary models, while ensuring the stability of the calculation results and reducing the calculation amount of nuclear simulation design analysis.

[0010] On the basis of the above solution, the nuclear simulation design and analysis method based on Monte Carlo calculation of the present invention can be further improved as follows.

[0011] Furthermore, it also includes:

[0012] Based on a preset screening method, at least one group of target calculation results is selected from all the second calculation results to determine the values ​​of the main factors of the nuclear simulation design solution corresponding to each group of target calculation results.

[0013] The beneficial effect of adopting the above-mentioned further technical solution is that it is possible to intelligently obtain the optimal solution for nuclear simulation design analysis in a relatively short time.

[0014] Furthermore, the step of determining a plurality of main factors of the nuclear simulation design and analysis scheme based on the preset objectives and basic model of the nuclear simulation design and analysis scheme includes:

[0015] Obtaining all influencing factors of the nuclear simulation design analysis scheme according to the preset target and the basic model;

[0016] From all the influencing factors, at least one influencing factor that is linearly independent and affects the result of the nuclear simulation design analysis program is determined as a main factor.

[0017] Furthermore, the type of any auxiliary model includes: a single-factor auxiliary model, and any main factor includes: at least one main factor typical value; the step of constructing multiple auxiliary models of the nuclear simulation design analysis solution based on the multiple main factors includes:

[0018] According to the typical value of each main factor of any of the main factors, multiple single-factor auxiliary models corresponding to the any of the main factors are constructed until multiple single-factor auxiliary models corresponding to each main factor are obtained; wherein each main factor typical value corresponds to a single-factor auxiliary model.

[0019] Furthermore, any auxiliary model type also includes: a multi-factor auxiliary model; the step of constructing multiple auxiliary models of the nuclear simulation design analysis solution based on the multiple main factors also includes:

[0020] At least one multi-factor auxiliary model of the nuclear simulation design analysis scheme is constructed based on the combination of multiple main factors.

[0021] Furthermore, it also includes:

[0022] During the Monte Carlo calculation of the basic model and any one of the auxiliary models, the particle flux and weight parameters of any one of the models are calculated using the influence of the multiple main factors on the preset target.

[0023] Furthermore, it also includes:

[0024] During the Monte Carlo calculation of the basic model and any one of the auxiliary models, when the transport particles in any one of the models collide multiple times with any one of the nuclides, bias correction is performed on any one of the nuclides based on the forced collision method so that the transport particles in any one of the models collide with multiple nuclides.

[0025] Furthermore, the step of fitting all first calculation results to obtain multiple sets of second calculation results includes:

[0026] Based on the least square method or the weight conservation method, all the first calculation results are fitted to obtain the multiple groups of second calculation results.

[0027] Furthermore, the preset screening method is a main factor ranking method; the step of selecting at least one group of target calculation results from all the second calculation results based on the preset screening method to determine the values ​​of the main factors of the nuclear simulation design scheme corresponding to each group of target calculation results includes:

[0028] At least one main factor is determined from the multiple main factors, and based on the at least one main factor, all the second calculation results are arranged in descending order to obtain a target sequence, and the first Q second calculation results in the target sequence are respectively determined as target calculation results to determine the value of the main factor of the nuclear simulation design scheme corresponding to each group of target calculation results; wherein Q is a positive integer.

[0029] The technical solution of a nuclear simulation design and analysis system based on Monte Carlo calculation of the present invention is as follows:

[0030] Including: building modules and computing modules;

[0031] The construction module is used to: determine a plurality of main factors of the nuclear simulation design and analysis scheme based on the preset objectives and basic model of the nuclear simulation design and analysis scheme, and construct a plurality of auxiliary models of the nuclear simulation design and analysis scheme according to the plurality of main factors;

[0032] The calculation module is used to perform Monte Carlo calculations on the basic model and each auxiliary model respectively, obtain and fit all first calculation results, and obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of the main factors of the nuclear simulation design scheme.

[0033] The beneficial effects of the nuclear simulation design and analysis system based on Monte Carlo calculation of the present invention are as follows:

[0034] The system of the present invention obtains a large number of different scheme results of nuclear simulation design analysis through several Monte Carlo fitting of the basic model and multiple auxiliary models. While ensuring the stability of the calculation results, it can intelligently obtain the optimal scheme of simulation design analysis in a relatively short time. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic flow chart of a first embodiment of a nuclear simulation design and analysis method based on Monte Carlo calculation provided by the present invention;

[0036] Figure 2 A schematic flow chart of a second embodiment of a nuclear simulation design and analysis method based on Monte Carlo calculation provided by the present invention;

[0037] Figure 3 A schematic structural diagram of an embodiment of a nuclear simulation design and analysis system based on Monte Carlo calculation provided by the present invention. DETAILED DESCRIPTION

[0038] Figure 1 FIG. 1 shows a flow chart of a first embodiment of a nuclear simulation design analysis method based on Monte Carlo calculation provided by the present invention, as shown in FIG. Figure 1 As shown, the following steps are included:

[0039] Step 110: Based on the preset objectives and basic models of the nuclear simulation design and analysis scheme, multiple main factors of the nuclear simulation design and analysis scheme are determined, and multiple auxiliary models of the nuclear simulation design and analysis scheme are constructed according to the multiple main factors.

[0040] ① Nuclear simulation design and analysis solutions primarily include simulation and analysis solutions for device designs involving nuclear reactions or nuclear changes. ② Preset objectives are the objectives that the nuclear simulation design and analysis solution must achieve. For example, when the nuclear simulation design and analysis solution is for a pressurized water reactor core design, the preset objectives are to ensure a Keff coefficient near unity while achieving the highest possible nuclear fission power within the smallest possible space, with specific power distribution requirements. When the nuclear simulation design and analysis solution is for a tritium breeder blanket design for a magnetic confinement fusion thermal nuclear reactor, the preset objectives are to achieve the highest tritium breeding rate possible, while also ensuring the ability to promptly convert and transmit heat generated within the blanket, limiting the blanket's temperature distribution, and meeting radiation shielding requirements. ③ Basic models are the specific models of the nuclear simulation design and analysis solution, primarily encompassing design aspects such as the source term, the nuclide composition and spatial distribution of functional materials, structural materials, and the shape and dimensions of key components. There are several basic templates and design parameters available in this field. ④ Principal factors are those factors that affect the results of the nuclear simulation design and analysis scheme and are linearly independent (i.e., any one principal factor cannot be linearly expressed by the other principal factors). Principal factors include, but are not limited to, source terms, material nuclide type, material nuclide composition ratio, material density, and material geometry. ⑤ Auxiliary models are models generated by modifying the parameters of the basic model based on independent changes in a principal factor or a combination of multiple principal factors in the nuclear simulation design and analysis scheme.

[0041] Specifically, when the nuclear simulation design analysis scheme is a core design scheme for a pressurized water reactor (PWR) nuclear power plant, based on the preset objectives and basic model of the PWR core design scheme, multiple primary factors are selected from all factors that affect the PWR core design scheme results, including: the nuclear composition of the fuel pellets, the number and layout of the fuel assemblies, the number and layout of the control rods, the nuclear composition and density of the structural grid materials, the core geometry, and the refueling cycle. Based on the type of primary factors, auxiliary models corresponding to six categories of primary factors are established: six auxiliary models for independently varying the nuclear composition of the fuel pellets, three models for independently varying the number and layout of the fuel assemblies, three models for independently varying the number and layout of the control rods, three models for independently varying the nuclear composition and density of the structural grid materials, three models for independently varying the core geometry, and three models for independently varying the refueling cycle, for a total of 21 auxiliary models established (this embodiment does not consider auxiliary models corresponding to variations in combinations of factors).

[0042] Step 120: Perform Monte Carlo calculations on the basic model and each auxiliary model respectively, obtain and fit all the first calculation results to obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of the main factors of the nuclear simulation design scheme.

[0043] ① Any first calculation result is the Monte Carlo calculation result obtained by performing a Monte Carlo calculation on the basic model and any auxiliary model of the nuclear simulation design analysis scheme, such as the keff coefficient, reactivity coefficient, core power distribution, etc. ② A set of second calculation results is the calculation result obtained by fitting all first calculation results. ③ The value of a major factor is the specific value of the major factor; for example, the major factor (number and layout of fuel assemblies) is 157.

[0044] It should be noted that: ① It should be noted that the corresponding variables in the second calculation result are the same as those in the first calculation result, namely, the reactivity coefficient, K eff coefficient, core power distribution, etc. The difference between the second calculation result and the first settlement result is that the design parameter range (type of main factors) corresponding to the second calculation result has been expanded through fitting, that is, it is not limited to the values ​​of the six main factors mentioned above (nuclides composition of fuel pellets, number and plane arrangement of fuel assemblies, number and plane arrangement of control rods, nuclides composition and density of structural grid materials, core geometry, and refueling cycle) when constructing the auxiliary model in this embodiment. By fitting all the first calculation results, a large number of scheme results can be obtained by performing a small amount of Monte Carlo calculations on the nuclear simulation design analysis scheme. ② The Monte Carlo calculation method is an existing technology. In order to better illustrate the technical content of step 120, this embodiment uses the auxiliary model corresponding to the change of the main factor (nuclides composition of fuel pellets) in the core design scheme of a pressurized water reactor nuclear power plant to perform Monte Carlo calculation as an example for illustration, but it is not limited to the following content. The reactivity coefficient is used to describe the change of system reactivity when the system coolant temperature coefficient, fuel temperature coefficient, coolant density coefficient, fuel density coefficient, cavitation coefficient, etc. change. The definition is shown in formula (1):

[0045]

[0046] In formula (1): ρ is the reactivity value; α i is the i-th parameter x of the system i The reactivity coefficient, α i It is any one of the coolant temperature coefficient, fuel temperature coefficient, coolant density coefficient, fuel density coefficient, and cavitation coefficient.

[0047] Specifically, the Monte Carlo calculation method is used to obtain the first calculation result of any model. First, the history of the random motion of a single neutron in a given geometric system medium is established. Then, by tracking a large number of neutron histories, sufficient sampling values ​​of the random variable are obtained. Finally, an estimate of a certain numerical characteristic of the random variable is statistically obtained, and this estimate is used as the solution to the problem. Generally, three steps are included: sampling the source distribution, random walk of spatial energy and motion direction, and recording contributions and analyzing results. This embodiment specifically uses perturbation theory to calculate the reactivity coefficient. The calculation formula (2) is as follows:

[0048]

[0049] Among them, Keff i Represents the Keff coefficient under state i. Assuming an operator P = MF / Keff consisting of the transport operator M and the fission operator F, the transport equation before perturbation is:

[0050] Pφ=0 (3)

[0051] Where φ is the neutron flux density before the disturbance. The corresponding conjugate equation is:

[0052] P * φ * =0 (4)

[0053] φ * is the conjugate neutron flux density, P * is the conjugate P operator. Assuming that some small temperature changes, density changes, and size changes are introduced into the system, so that the operator P becomes P′=P+δP, then the neutron transport equation after the parameter changes becomes:

[0054] P′φ′=Pφ′+δPφ′=0 (5)

[0055] Where φ′=φ+δφ is the neutron flux density after perturbation. Using the solution of the conjugate equation before perturbation, φ * Doing the inner product with the transport equation (5) after the disturbance gives:

[0056] <φ * , Pφ′>+<φ * ,δPφ′>=0 (6)

[0057] Since P and P * Conjugate, assuming the boundary conditions are not perturbed, then

[0058] <φ′,P * φ * >+<φ * ,δPφ′>=0 (7)

[0059] According to formula (4), we can get:

[0060] <φ * ,δPφ′>=0 (8)

[0061] The above formula is valid regardless of whether δP is large or small. We can also discard the second-order trace δφ of the flux change, then φ′=φ+δφ≈φ, and then the basic equation of perturbation theory can be calculated from formula (8)

[0062] <φ * ,δPφ>=0 (9)

[0063] The perturbation operator δP includes small changes in various parameters, including the corresponding changes in Keff. In the Monte Carlo neutron transport calculation, the conjugate neutron flux density φ is calculated based on the repeated fission probability method. * At the same time, the neutron flux density φ before the disturbance is obtained statistically. On this basis, the corresponding change of Keff can be calculated according to the small disturbance of the temperature, density, size, shape, etc. of the nuclear energy system, and then substituted into formula (2) to calculate the reactivity coefficient corresponding to the auxiliary model.

[0064] In addition, since the Monte Carlo calculation method is very complicated, this section provides a more in-depth explanation of the calculation process of the weight factor corresponding to the first calculation result, including the calculation of parameters such as particle flux and weight, which should be performed in a way that can reflect the influence of the selected factors on the preset target. Among them, there are many physical quantities that need to be calculated in the core design scheme of the pressurized water reactor nuclear power plant. Here, the weight factor formula for neutron transport calculation is taken as an example. Based on the principle of weight conservation, the neutron flux value under each disturbance is statistically obtained in the Monte Carlo neutron transport process to illustrate the implementation method of this embodiment in terms of the parameter calculation formula. In addition, there are other basic particles / microscopic particles such as photons, electrons, mesons, Alpha particles, and the application of these particles in different systems such as hybrid reactors and fusion reactors, including combined applications. Specifically:

[0065] When neutrons are transported in the basic model, they are transported from position p1 to position p2. After the reaction occurs, the direction is converted from Ω1 to Ω2, the energy is converted from E1 to E2, and the weight is converted from w1 to w2. Based on the neutron transport process, the transformation relationship between w1 and w2 can be obtained, as shown in formula (10):

[0066]

[0067] In formula (10), ∑0 is the total reaction cross section of the material in the basic model. At the same time, formula (11) can be used to calculate the weight value of the neutron arriving at position p2 and reacting with nuclide j under different auxiliary models, and the energy and direction are converted from (E1, Ω1) to (E2, Ω2).

[0068]

[0069] In formula (11), ∑ i is the total reaction cross section of the material in auxiliary model i, is the nucleon density of nuclide j in the ith auxiliary model, is the nucleon density of nuclide j in the basic model. Using formula (11), a series of collision points can be obtained during the transport of a single particle, as shown below:

[0070]

[0071] In formula (12), n represents the number of collision points during single neutron transport, p i Represents a series of positions, w i Represents a series of weights, and N represents the number of auxiliary models. In the neutron transport process, the neutron flux values ​​under different auxiliary models can be obtained based on the track length method, as shown in formula (13):

[0072]

[0073] In formula (13), Ψ i (x) is the neutron flux under the i-th auxiliary model, m is the total number of simulated neutrons, k is the k-th neutron in the current simulation, j is the j-th step of the current neutron, is the weight of the kth neutron in the jth step under the i-th auxiliary model, l k，j is the track length of the kth neutron in the jth step. The statistical error estimation method used in the auxiliary model is consistent with that used in the basic model.

[0074] The technical solution of this embodiment obtains a large number of different scheme results of nuclear simulation design analysis through several Monte Carlo fitting of the basic model and multiple auxiliary models, while ensuring the stability of the calculation results and reducing the calculation amount of nuclear simulation design analysis.

[0075] Figure 2 FIG. 4 shows a flow chart of a second embodiment of a nuclear simulation design analysis method based on Monte Carlo calculation provided by the present invention, as shown in FIG. Figure 2 As shown, the following steps are included:

[0076] Step 210: Based on the preset objectives and basic models of the nuclear simulation design and analysis scheme, multiple main factors of the nuclear simulation design and analysis scheme are determined, and multiple auxiliary models of the nuclear simulation design and analysis scheme are constructed according to the multiple main factors.

[0077] Step 220: Perform Monte Carlo calculations on the basic model and each auxiliary model respectively, obtain and fit all the first calculation results to obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of the main factors of the nuclear simulation design scheme.

[0078] Step 230: Based on a preset screening method, select at least one group of target calculation results from all the second calculation results to determine the values ​​of the main factors of the nuclear simulation design solution corresponding to each group of target calculation results.

[0079] Wherein, ① the preset screening method includes but is not limited to: a main factor ranking method. ② the target calculation result is: the second calculation result of the nuclear simulation design solution selected according to the preset screening method.

[0080] In this embodiment, step 230 includes: determining at least one main factor from the multiple main factors, and based on the at least one main factor, arranging all the second calculation results in descending order to obtain a target sequence, and determining the first Q second calculation results in the target sequence as target calculation results, so as to determine the value of the main factor of the nuclear simulation design scheme corresponding to each group of target calculation results; wherein Q is a positive integer.

[0081] Specifically, taking the number and plane layout of fuel assemblies as an example, the main factors are: the number and plane layout of fuel assemblies. In this case, Q is 3. The values ​​of the main factors of the nuclear simulation design scheme corresponding to the three sets of target calculation results are shown in Table 1 below.

[0082] Table 1:

[0083]

[0084] The technical solution of this embodiment can further realize intelligent acquisition of the optimal solution for nuclear simulation design analysis in a relatively short time.

[0085] Preferably, based on any of the above embodiments, the step of determining the multiple main factors of the nuclear simulation design and analysis scheme based on the preset objectives and basic model of the nuclear simulation design and analysis scheme includes:

[0086] According to the preset target and the basic model, all influencing factors of the nuclear simulation design analysis program are obtained.

[0087] Among them, all influencing factors are: every factor that affects the result (goal) of the nuclear simulation design analysis program.

[0088] From all the influencing factors, at least one influencing factor that is linearly independent and affects the result of the nuclear simulation design analysis program is determined as a main factor.

[0089] It should be noted that linear independence means that any one selected primary factor cannot be linearly expressed by the other primary factors. For example, in this example, the change in "nuclidic composition of the fuel pellets" and its impact on the preset objectives (reactivity, power, etc.) of the pressurized water reactor nuclear simulation design and analysis plan cannot be replaced by changes in the other five primary factors or their combinations.

[0090] Preferably, based on any of the above embodiments, the type of any auxiliary model includes: a single-factor auxiliary model, and any main factor includes: at least one main factor typical value.

[0091] Among them, ① a single-factor auxiliary model is an auxiliary model generated based on the changes in a single main factor. ② Each main factor corresponds to at least one main factor representative value. ③ A main factor representative value is the representative value of any main factor. For example, when the main factor is the nuclide composition of the fuel pellets, there are six options for the nuclide composition of the fuel pellets: RFA-1 / RFA-1(XL), RFA-2 / RFA-2(XL), and RFA-3 / RFA-3(XL). The main factor representative values ​​corresponding to the main factor (nuclide composition of the fuel pellets) are: RFA-1, RFA-1(XL), RFA-2, RFA-2(XL), RFA-3, and RFA-3(XL). When the main factor is the number and layout of the fuel assemblies, there are three options for the number and layout of the fuel assemblies: 157, 241, and 265. The main factor representative values ​​corresponding to the main factor (the number and layout of the fuel assemblies) are: 157, 241, and 265.

[0092] It should be noted that the values ​​of other factors in the auxiliary model are the same as those in the basic model.

[0093] The step of constructing a plurality of auxiliary models of the nuclear simulation design analysis solution according to the plurality of main factors includes:

[0094] According to the typical value of each main factor of any of the main factors, multiple single-factor auxiliary models corresponding to the any of the main factors are constructed until multiple single-factor auxiliary models corresponding to each of the main factors are obtained.

[0095] Among them, the typical value of each main factor corresponds to a single-factor auxiliary model.

[0096] Preferably, based on any of the above embodiments, the type of any auxiliary model also includes: a multi-factor auxiliary model.

[0097] Among them, the multi-factor auxiliary model is an auxiliary model generated based on the changes in the combination of multiple main factors.

[0098] The step of constructing a plurality of auxiliary models of the nuclear simulation design analysis solution according to the plurality of main factors further includes:

[0099] At least one multi-factor auxiliary model of the nuclear simulation design analysis scheme is constructed based on the combination of multiple main factors.

[0100] The combination of multiple main factors may be the combination of two main factors to construct a multi-factor auxiliary model, or the combination of more than two main factors to construct a multi-factor auxiliary model, and there is no limitation here.

[0101] Preferably, based on any of the above embodiments, the method further includes:

[0102] During the Monte Carlo calculation of the basic model and any one of the auxiliary models, the particle flux and weight parameters of any one of the models are calculated using the influence of the multiple main factors on the preset target.

[0103] Preferably, based on any of the above embodiments, the method further includes:

[0104] During the Monte Carlo calculation of the basic model and any one of the auxiliary models, when the transport particles in any one of the models collide multiple times with any one of the nuclides, bias correction is performed on any one of the nuclides based on the forced collision method so that the transport particles in any one of the models collide with multiple nuclides.

[0105] Among them, the transport particles are: the transport particles in any model can collide with the nuclides in the model.

[0106] It should be noted that instability control is required during the Monte Carlo calculation process. Specifically, during the Monte Carlo calculation of any model, a group analysis method is used to identify instability factors affecting the calculation results due to parameter changes. When statistics show that a certain nucleus exhibits multiple scattering, a forced collision method is used to bias the nuclide species in the collision reaction. This ensures that the transported particles react with multiple nuclides as much as possible during transport in the model, rather than reacting with the same nuclide multiple times. The calculation is then continued, thus resolving the instability of the calculation results caused by multiple scattering of a single nuclide.

[0107] Preferably, based on any of the above embodiments, the step of fitting all first calculation results to obtain multiple sets of second calculation results includes:

[0108] Based on the least square method or the weight conservation method, all the first calculation results are fitted to obtain the multiple groups of second calculation results.

[0109] Specifically, under different models After the value is obtained, other response values ​​can be obtained accordingly. The corresponding relationship between the response value and the variable is shown in formula (14).

[0110]

[0111] In the formula is the first calculation result of the i-th auxiliary model, and N represents the number of auxiliary models. The least squares method is then used to perform parameter fitting on the values ​​corresponding to each variable in formula (14) to obtain the parameters affecting the calculation results, minimizing the sum of squares of their errors. When the design parameters are within the range of non-auxiliary models or undergo extreme changes (such as when a certain material is created from scratch), the calculation results can be obtained through function fitting and extrapolation. The statistical error of the calculation results is obtained through error propagation.

[0112] Figure 3 FIG1 shows a structural diagram of an embodiment of a nuclear simulation design and analysis system based on Monte Carlo calculation provided by the present invention. Figure 3 As shown, the system 300 includes: a construction module 310 and a calculation module 320;

[0113] The construction module 310 is used to: determine a plurality of main factors of the nuclear simulation design and analysis scheme based on the preset objectives and basic models of the nuclear simulation design and analysis scheme, and construct a plurality of auxiliary models of the nuclear simulation design and analysis scheme according to the plurality of main factors;

[0114] The calculation module 320 is used to perform Monte Carlo calculations on the basic model and each auxiliary model respectively, obtain and fit all the first calculation results, and obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of the main factors of the nuclear simulation design scheme.

[0115] The technical solution of this embodiment obtains a large number of different scheme results of nuclear simulation design analysis through several Monte Carlo fitting of the basic model and multiple auxiliary models, while ensuring the stability of the calculation results and reducing the calculation amount of nuclear simulation design analysis.

[0116] The above-mentioned parameters and steps for each module to implement corresponding functions in the nuclear simulation design and analysis system 300 based on Monte Carlo calculation in this embodiment can refer to the parameters and steps in the first embodiment or the second embodiment of the nuclear simulation design and analysis method based on Monte Carlo calculation above, and will not be repeated here.

[0117] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present invention may be practiced without these specific details. Similarly, in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. The claims that follow the detailed description are hereby expressly incorporated into that detailed description, with each claim itself serving as a separate embodiment of the present invention.

[0118] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A nuclear simulation design analysis method based on Monte Carlo calculation, characterized in that: include: Determining a plurality of main factors of the nuclear simulation design and analysis scheme based on a preset goal and a basic model of the nuclear simulation design and analysis scheme, and constructing a plurality of auxiliary models of the nuclear simulation design and analysis scheme based on the plurality of main factors; Performing Monte Carlo calculations on the basic model and each auxiliary model respectively to obtain and fit all first calculation results to obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of main factors of the nuclear simulation design analysis scheme; The types of any auxiliary model include: a single-factor auxiliary model and a multi-factor auxiliary model, and any main factor includes: at least one main factor typical value; the step of constructing multiple auxiliary models of the nuclear simulation design analysis solution based on the multiple main factors includes: According to each main factor typical value of any one of the main factors, construct multiple single factor auxiliary models corresponding to the any one of the main factors, until multiple single factor auxiliary models corresponding to each main factor are obtained; wherein each main factor typical value corresponds to one single factor auxiliary model; Constructing at least one multi-factor auxiliary model of the nuclear simulation design analysis scheme based on a combination of multiple main factors; It also includes: during the Monte Carlo calculation of any one of the basic model and each auxiliary model, when the transport particles in any one of the models collide multiple times with any one of the nuclides, bias correction is performed on the any one of the nuclides based on the forced collision method so that the transport particles in any one of the models collide with multiple nuclides.

2. The nuclear simulation design analysis method based on Monte Carlo calculation according to claim 1, characterized in that: Also includes: Based on a preset screening method, at least one group of target calculation results is selected from all the second calculation results to determine the values ​​of the main factors of the nuclear simulation design analysis scheme corresponding to each group of target calculation results.

3. The nuclear simulation design analysis method based on Monte Carlo calculation according to claim 1 or 2, characterized in that: The step of determining a plurality of main factors of the nuclear simulation design and analysis scheme based on the preset objectives and basic model of the nuclear simulation design and analysis scheme includes: Obtaining all influencing factors of the nuclear simulation design analysis scheme according to the preset target and the basic model; From all the influencing factors, at least one influencing factor that is linearly independent and affects the result of the nuclear simulation design analysis program is determined as a main factor.

4. The nuclear simulation design analysis method based on Monte Carlo calculation according to claim 1 or 2, characterized in that: Also includes: During the Monte Carlo calculation of the basic model and any one of the auxiliary models, the particle flux and weight parameters of any one of the models are calculated using the influence of the multiple main factors on the preset target.

5. The nuclear simulation design analysis method based on Monte Carlo calculation according to claim 1 or 2, characterized in that: The step of fitting all first calculation results to obtain multiple groups of second calculation results includes: Based on the least square method or the weight conservation method, all the first calculation results are fitted to obtain the multiple groups of second calculation results.

6. The nuclear simulation design analysis method based on Monte Carlo calculation according to claim 2, characterized in that: The preset screening method is a main factor sorting method; the step of selecting at least one group of target calculation results from all the second calculation results based on the preset screening method to determine the values ​​of the main factors of the nuclear simulation design analysis scheme corresponding to each group of target calculation results includes: At least one main factor is determined from the multiple main factors, and based on the at least one main factor, all the second calculation results are arranged in descending order to obtain a target sequence, and the first Q second calculation results in the target sequence are respectively determined as target calculation results to determine the value of the main factor of the nuclear simulation design analysis scheme corresponding to each group of target calculation results; wherein Q is a positive integer.

7. A nuclear simulation design and analysis system based on Monte Carlo calculation, characterized in that: include: Building blocks and computational modules; The construction module is used to: determine a plurality of main factors of the nuclear simulation design and analysis scheme based on the preset objectives and basic model of the nuclear simulation design and analysis scheme, and construct a plurality of auxiliary models of the nuclear simulation design and analysis scheme according to the plurality of main factors; The calculation module is used to perform Monte Carlo calculations on the basic model and each auxiliary model respectively, obtain and fit all first calculation results, and obtain multiple groups of second calculation results; wherein each group of second calculation results corresponds to a group of values ​​of main factors of the nuclear simulation design analysis scheme; The types of any auxiliary model include: single-factor auxiliary model and multi-factor auxiliary model, and any main factor includes: at least one main factor typical value; the construction module is specifically used to: According to each main factor typical value of any one of the main factors, construct multiple single factor auxiliary models corresponding to the any one of the main factors, until multiple single factor auxiliary models corresponding to each main factor are obtained; wherein each main factor typical value corresponds to one single factor auxiliary model; Constructing at least one multi-factor auxiliary model of the nuclear simulation design analysis scheme based on a combination of multiple main factors; It also includes: a collision simulation module, which is used to, during the process of Monte Carlo calculation of any model in the basic model and each auxiliary model, when the transport particles in any model collide multiple times with any nuclide, perform bias correction on the any nuclide based on the forced collision method to make the transport particles in any model collide with multiple nuclides.

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