A method and system for optimizing neutron spectrum for improving reactor radioisotope production efficiency

Abstract

The present application relates to a kind of neutron energy spectrum optimization method and system for improving reactor radioisotope production efficiency, method includes the following steps: initial population of genetic algorithm is randomly generated, these population individuals are all neutron energy spectrum divided into n energy group, the body average neutron energy spectrum in target piece when the neutron energy spectrum of each individual is calculated as irradiation hole incident spectrum, the radioisotope production under the body average neutron energy spectrum in target piece corresponding to each individual is calculated, the evolution of population is realized by the mutation and crossing operation of genetic algorithm, the above-mentioned process is repeatedly executed until iteration converges, obtains the neutron energy spectrum regulation scheme for realizing the maximization of radioisotope production.Compared with prior art, the present application efficiently realizes the accurate regulation of neutron energy spectrum in reactor, can provide technical support for the energy spectrum regulation process of radioisotope irradiation production in reactor.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear reactor design, in particular to a neutron energy spectrum optimization method and system for improving the production efficiency of radioisotopes in a reactor. BACKGROUND

[0002] The neutron energy spectrum has a significant impact on the production efficiency of radioisotopes irradiated in a reactor, and regulating the neutron energy spectrum in the irradiation hole can effectively improve the efficiency of the reactor in producing radioisotopes. The traditional method of regulating the neutron energy spectrum in the reactor has defects such as narrow adjustable energy range, low energy spectrum resolution, low regulation accuracy, and poor universality, which makes it difficult to effectively improve the efficiency of radioisotopes irradiated in the reactor. SUMMARY

[0003] The purpose of the present application is to provide a neutron energy spectrum optimization method and system for improving the production efficiency of radioisotopes in a reactor, and to improve the production efficiency of radioisotopes in a reactor.

[0004] The purpose of the present application can be achieved by the following technical solution: a neutron energy spectrum optimization method for improving the production efficiency of radioisotopes in a reactor, comprising the following steps:

[0005] Randomly generate initial populations of genetic algorithms, and each individual of the population is a neutron energy spectrum divided into n energy groups. Calculate the volume-averaged neutron energy spectrum in the target when each individual neutron energy spectrum is used as the incident energy spectrum of the irradiation hole. Calculate the radioisotope yield under the volume-averaged neutron energy spectrum in the target corresponding to each individual. Through mutation and crossover operations of the genetic algorithm, the population evolves. Repeat the above process until the iteration converges, and obtain the neutron energy spectrum regulation scheme that maximizes the radioisotope yield.

[0006] Preferably, the full energy region is divided into n energy groups, and the probability of energy transfer between each energy group after a nuclear reaction between a neutron and m kinds of nuclei is calculated using the Monte Carlo method, thereby constructing m n x n matrices, called energy spectrum response matrices.

[0007] Based on the energy spectrum response matrix, the volume-averaged neutron energy spectrum in the target corresponding to each individual neutron energy spectrum when used as the incident energy spectrum of the irradiation hole is obtained.

[0008] Further preferably, the volume-averaged neutron energy spectrum in the target is calculated by the following formula:

[0009] φ1=R·φ2;

[0010] In the formula: φ1 is the volume-averaged neutron energy spectrum in the target, φ2 is the incident energy spectrum of the irradiation hole, and R is the energy spectrum response matrix of the target after weighting of multiple nuclei.

[0011] wherein,

[0012] in the formula: K is the number of species of nuclides contained in the target, R i is the energy spectrum response matrix of the i-th nuclide in the target, F i is the nuclear reaction fraction of the i-th nuclide in the target, i.e. the ratio of the total cross section of the nuclide to the total cross section of the target.

[0013] Preferably, the radioisotope yield of each individual in the target under the body-averaged neutron energy spectrum is obtained by performing a burnup calculation.

[0014] Further preferably, the burnup calculation refers to solving the burnup equation:

[0015]

[0016] in the formula: n i is the density of the i-th nuclide; λ i eff is the effective decay coefficient of the i-th nuclide; λ j eff is the effective decay coefficient of the j-th nuclide; b i,j eff is the branching ratio of the i-th nuclide to the j-th nuclide;

[0017] wherein, the λ i eff and b i,j eff are calculated from the following formula:

[0018]

[0019] in the formula: λ i is the decay constant of the i-th nuclide; Ψ is the neutron flux density; σ i,j is the single-group microscopic cross section of the i-th nuclide to produce the j-th nuclide by nuclear reaction; b i,j is the branching ratio of the i-th nuclide to the j-th nuclide after decay; λ i is the decay constant of the i-th nuclide;

[0020] Based on σ i,j , the single-group macroscopic cross section Σ r required for burnup calculation is obtained by compressing and grouping the neutron energy spectrum:

[0021]

[0022] in the formula: the subscript p represents the number of energy groups, σ r,p is the microscopic cross section of the reaction type r in the p-th energy group, φ prepresents the normalized neutron energy spectrum, i.e. the neutron flux density of the pth energy group after normalization.

[0023] In the present application, n i represents the radioisotope yield, which corresponds to the volume-averaged neutron energy spectrum φ1 in the target after normalization of Ψ, and the volume-averaged neutron energy spectrum φ1 in the target can be obtained after normalization of Ψ.

[0024] Preferably, the neutron energy spectrum optimization method for improving the radioisotope production efficiency of a reactor further comprises dispersing a plurality of nuclides in the target to obtain a different energy spectrum response matrix.

[0025] Further preferably, the plurality of nuclides are dispersed in the target to obtain a different energy spectrum response matrix R weighted by the plurality of nuclides in the target.

[0026] Preferably, the iterative convergence condition is that the relative deviation of the radioisotope yield of the two generations is less than 0.0001.

[0027] Preferably, based on the neutron energy spectrum regulation scheme that can maximize the radioisotope yield, the nuclides are dispersed in the target to be optimized to improve the radioisotope production efficiency of the reactor.

[0028] Preferably, the neutron energy spectrum optimization method for improving the radioisotope production efficiency of a reactor comprises the following steps:

[0029] Step 1: Construct a neutron energy spectrum fast response module, divide the full energy region into n energy groups, use the Monte Carlo method to count the probability of energy transfer between energy groups after a nuclear reaction of neutrons with m kinds of nuclides, thereby constructing m n x n matrices, called energy spectrum response matrices, which describe the energy transfer relationship of various nuclides and neutrons after a nuclear reaction. For a large number of neutron nuclear reaction processes, the macroscopic response relationship between neutron energy spectra is manifested, so that the neutron energy spectrum can be calculated quickly by iteratively solving the formula φ1 = R·φ2.

[0030] In the formula, φ1 is the volume-averaged neutron energy spectrum in the target, φ2 is the incident energy spectrum of the irradiation hole, and R is the energy spectrum response matrix weighted by the plurality of nuclides in the target, which is calculated by .

[0031] In the formula, K is the number of nuclides contained in the target, R i is the energy spectrum response matrix of the ith nuclide in the target, and F i is the nuclear reaction proportion of the ith nuclide in the target, i.e. the ratio of the total cross section of the nuclide to the total cross section of the target.

[0032] Step 2: Constructing neutron spectrum regulation module, in order to convert the incident neutron spectrum of irradiation channel into a neutron spectrum beneficial to the production of radioisotopes, so that the target is in the best neutron spectrum environment, the present application obtains different spectrum response matrices by dispersing various nuclides in the target, and realizes the regulation of neutron spectrum.

[0033] Step 3: Constructing radioisotope yield calculation module, based on the neutron spectrum regulation module, a plurality of neutron spectra can be obtained, at this time, by performing burnup calculation, the radioisotope yield under the neutron spectrum can be obtained, and the efficiency of the neutron spectrum for radioisotope production can be evaluated.

[0034] The burnup calculation refers to solving the burnup equation:

[0035]

[0036] In the above formula, n i is the density of the i th nuclide; λ i eff is the effective decay coefficient of the i th nuclide; b i,j eff is the branching ratio of the i th nuclide converted into the j th nuclide; wherein λ i eff and b i,j eff are calculated by the following formula:

[0037]

[0038] λ i is the decay constant of the i th nuclide; Ψ is the neutron flux density; σ i,j is the single-group microscopic cross section of the i th nuclide producing the j th nuclide by nuclear reaction, based on σ i,j According to the neutron spectrum compression and group, the single-group macroscopic cross section Σ r required for burnup calculation can be obtained:

[0039]

[0040] In the formula, subscript p represents the number of energy groups, σ r,p is the microscopic cross section of reaction type r in the p th energy group, and φ p represents the normalized neutron spectrum, i.e. the neutron flux density of the p th energy group after normalization.

[0041] Step 4: Constructing the intelligent optimization module, first randomly generating the initial population of genetic algorithm, these population individuals are all the neutron energy spectrum divided into n energy groups, then using the neutron energy spectrum fast response module to calculate the neutron energy spectrum as the irradiation hole incident spectrum in the target, then using the radioisotope yield calculation module to evaluate the efficiency of the neutron energy spectrum for radioisotope production, finally through the mutation and crossover operation of genetic algorithm, the evolution of the population is realized, and the above process is repeatedly executed until the iteration converges, and the neutron energy spectrum regulation scheme for maximizing the radioisotope yield is obtained.

[0042] A system for implementing the above-mentioned neutron energy spectrum optimization method, comprising:

[0043] A neutron energy spectrum fast response module for calculating the volume-averaged neutron energy spectrum in the target when each individual neutron energy spectrum is used as the irradiation hole incident spectrum;

[0044] A radioisotope yield calculation module for calculating the radioisotope yield in the target under the volume-averaged neutron energy spectrum corresponding to each individual;

[0045] A neutron energy spectrum regulation module for obtaining different energy spectrum response matrices;

[0046] And a genetic algorithm optimization module (intelligent optimization module) for obtaining a neutron energy spectrum regulation scheme for maximizing the radioisotope yield.

[0047] The present application aims at the defects of narrow adjustable energy range, low energy spectrum resolution, low regulation precision and poor method universality of the traditional reactor neutron energy spectrum regulation method, and proposes a full-energy-domain neutron energy spectrum accurate regulation method. The method first constructs a neutron energy spectrum fast response module to realize fast calculation of the neutron energy spectrum; then constructs a neutron energy spectrum regulation module to obtain various neutron energy spectra by dispersing various spectrum-shifting nuclides in the target; then constructs a radioisotope yield calculation module to calculate the yield of radioisotopes under various neutron energy spectra using the point-burn algorithm; finally, an intelligent optimization module is constructed, and a genetic algorithm is used to connect the above modules to obtain a neutron energy spectrum regulation scheme for maximizing the radioisotope yield. The present application can provide technical support for the energy spectrum regulation process of irradiation production of radioisotopes in a reactor.

[0048] Compared with the prior art, the present application has the following beneficial effects:

[0049] 1. The present application provides a method for improving the efficiency of irradiation production of radioisotopes in a reactor by full-energy-domain neutron energy spectrum regulation.

[0050] 2. The present application solves the problems of narrow adjustable energy range, low energy spectrum resolution, low regulation accuracy and poor universality of the traditional reactor neutron spectrum regulation method.

[0051] 3. Compared with the traditional method, the present application can realize neutron spectrum regulation in the full energy range, has no restriction on energy group division during the regulation process, can realize very high energy spectrum resolution, uses genetic algorithm to realize optimization, improves the accuracy of neutron spectrum regulation, and the method does not introduce theoretical assumptions and approximations, and has universality. The present application efficiently realizes the accurate regulation of reactor neutron spectrum, and can provide technical support for the energy spectrum regulation process of the irradiation production of radioisotopes in the reactor.

[0052] 4. The present application proposes a reactor neutron spectrum regulation technology, which improves the production efficiency of radioisotopes in the reactor by constructing a neutron spectrum fast response module, a neutron spectrum regulation module, a radioisotope yield calculation module and an intelligent optimization module. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 is a flowchart of embodiment 1 of the present application;

[0054] Figure 2 is a geometric diagram of a high flux isotope reactor (HFIR). DETAILED DESCRIPTION

[0055] The present application will be described in detail below in combination with the drawings and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present application, and gives a detailed implementation manner and specific operation process, but the protection scope of the present application is not limited to the following embodiments.

[0056] A neutron spectrum optimization method for improving the production efficiency of radioisotopes in a reactor, as shown in Figure 1 , includes the following steps:

[0057] S1: Randomly adding various nuclides in the target;

[0058] S2: Initializing / updating the genetic algorithm population;

[0059] S3: Determining the energy spectrum response matrix corresponding to each individual;

[0060] S4: Calculating the volume average neutron flux of the target corresponding to each individual;

[0061] S5: Calculating the single-group cross section required for burnup calculation;

[0062] S6: Calculating the radioisotope yield corresponding to each individual;

[0063] S7: judging whether the evolution is finished, outputting the best energy spectrum regulation scheme when the iterative convergence condition is met, and returning to step S2 to repeat the above process when the iterative convergence condition is not met.

[0064] Example 1

[0065] In Figure 2 The production of super-uranium isotopes in the high flux isotope reactor (HFIR) is taken as an example. The reactor and the super-uranium isotope production scheme based on the reactor are the best schemes in the world at present.

[0066] The target nuclide composition for the production of californium-252 in the HFIR is shown in Table 1 below. The californium-252 yield of the target irradiated in the HFIR for 25 days is 1.33 x 10 18 atoms / cm 3 .

[0067] Table 1. Target nuclide composition for the production of californium-252 in the HFIR

[0068]

[0069] In this example, the local neutron energy spectrum for the production of californium-252 in the HFIR is optimized using the present application, and the specific implementation process is shown in Figure 1 .

[0070] In this example, the energy transfer matrix of 423 nuclides is constructed for energy spectrum regulation, and the size of each energy transfer matrix is 238 x 238. Therefore, the neutron energy spectrum fast response module can realize the fast calculation of the neutron energy spectrum of 238 energy groups under the matching of 423 nuclides.

[0071] When the genetic algorithm is used to search for the best neutron energy spectrum regulation scheme, the population number of each generation is 400, and the population evolves for 400 generations. During the evolution process, the crossover rate of the population is 20%, and the mutation rate is 20%.

[0072] The target nuclide composition in Table 1 is the nuclide matching of the initial population, and the total density of the initial nuclides is 5.52 x 10 22 atoms / cm 3 In the subsequent genetic algorithm optimization process, the bulk average neutron energy spectrum of the target is changed by dispersing the 423 nuclides (excluding the nuclides with atomic mass > 350) in the target, and the total density of the dispersed nuclides is 5.52 x 10 20 atoms / cm 3 Therefore, the genetic algorithm needs to search for the nuclide matching of the 423 nuclides to be added.

[0073] In this example, the reactor Monte Carlo program RMC is used to perform the point depletion calculation, which is developed by Tsinghua University and is currently a well-known reactor physics calculation program internationally.

[0074] The energy spectrum optimization scheme is realized by dispersing the nuclide proportioning shown in Table 2 in the target. At this time, the production of californium-252 is 1.49×10 18 atoms / cm2 3 The production of californium-252 is increased by 12.16%.

[0075] Table 2. The added target nuclide proportioning required by the energy spectrum optimization scheme for producing californium-252 in the HFIR reactor

[0076]

[0077] It can be seen that the production efficiency of californium-252 can be improved by neutron energy spectrum optimization, and the neutron energy spectrum regulation process only needs to disperse some nuclides in the target, without modifying the design parameters of the reactor or the irradiation hole, and has the advantages of simplicity and feasibility.

[0078] The above description of the embodiments is for facilitating the understanding and use of the application by ordinary skilled in the art. Those skilled in the art can easily make various modifications to the embodiments, and apply the general principles described herein to other embodiments without creative labor. Therefore, the application is not limited to the above embodiments, and the improvements and modifications made by those skilled in the art according to the disclosure of the application without departing from the scope of the application should be within the protection scope of the application.

Claims

1. A neutron spectrum optimization method for improving the efficiency of reactor radioisotope production, characterized in that: The following steps are involved: The initial population of the genetic algorithm is randomly generated, and the full energy range is divided into n energy groups. The Monte Carlo method is used to calculate the probability of energy transfer between energy groups after a nuclear reaction between neutrons and m types of nuclides, thereby constructing m n×n matrices, called energy spectrum response matrices. Based on the energy spectrum response matrix, the neutron energy spectrum of each individual is obtained as the volume-averaged neutron energy spectrum in the target corresponding to the incident energy spectrum of the irradiation channel. Multiple nuclides are diffused in the target to obtain different energy spectrum response matrices. The radioactive isotope yield under the volume-averaged neutron energy spectrum in the target corresponding to each individual is obtained by performing ignition consumption calculations. The population evolution is achieved through mutation and crossover operations of the genetic algorithm. The above process is repeated until iterative convergence to obtain a neutron energy spectrum control scheme that maximizes radioactive isotope yield.

2. The neutron spectrum optimization method for improving reactor radioisotope production efficiency according to claim 1, characterized in that: The volume average neutron energy spectrum in the target is calculated by the following formula: φ1=R·φ2; Where: φ1 is the volume average neutron energy spectrum in the target, φ2 is the incident energy spectrum of the irradiation channel, and R is the weighted energy spectrum response matrix of multiple nuclides in the target; in, Where: K is the number of nuclides contained in the target, R i is the energy spectrum response matrix of the i-th nuclide in the target, F i is the nuclear reaction ratio of the i-th nuclide in the target, that is, the ratio of the total cross section of the nuclide to the total cross section of the target.

3. The neutron spectrum optimization method for improving reactor radioisotope production efficiency according to claim 1, characterized in that: The ignition consumption calculation refers to solving the ignition consumption equation: Where: n i is the density of the ith nuclide; λ i eff is the effective attenuation coefficient of the ith nuclide; λ j eff is the effective attenuation coefficient of the jth nuclide; b i,j eff is the branching ratio of the i-th nuclide to the j-th nuclide; Among them, the λ i eff and b i,j eff Calculated by the following formula: Where: i is the decay constant of the ith nuclide; Ψ is the neutron flux density; σ i,j is the single group microscopic cross section of the nuclear reaction of the i-th nuclide to produce the j-th nuclide; b i,j is the branching ratio of the i-th nuclide to the j-th nuclide after decay; λ i is the decay constant of the ith nuclide; Based on σ i,j The single group macroscopic cross section Σ required for ignition consumption calculation is obtained by compressing and grouping the neutron energy spectrum. r : Where: subscript p represents the number of the energy group, σ r,p is the microscopic cross section of reaction type r in the pth energy group, φ p represents the normalized neutron energy spectrum, that is, the neutron flux density of the pth energy group after normalization.

4. The neutron spectrum optimization method for improving reactor radioisotope production efficiency according to claim 1, characterized in that: A variety of nuclides are diffused in the target, and the weighted energy spectrum response matrix R of the multiple nuclides in different targets is obtained.

5. The neutron spectrum optimization method for improving reactor radioisotope production efficiency according to claim 1, characterized in that: The iterative convergence condition is that the relative deviation of the isotope yields of the previous and next two generations is less than 0.0001.

6. The neutron spectrum optimization method for improving reactor radioisotope production efficiency according to claim 1, characterized in that: Based on a neutron spectrum control scheme that can maximize the yield of radioactive isotopes, nuclides are diffused in the target to be optimized.

7. A system for implementing the neutron spectrum optimization method according to any one of claims 1 to 6, characterized in that: include: A neutron energy spectrum rapid response module for calculating the volume average neutron energy spectrum in the target when each volume neutron energy spectrum is used as the incident energy spectrum of the irradiation channel; A radioactive isotope yield calculation module for calculating the radioactive isotope yield under the volume-averaged neutron energy spectrum within the target corresponding to each body; Neutron energy spectrum control module for obtaining different energy spectrum response matrices; and a genetic algorithm optimization module for obtaining a neutron spectrum control scheme that maximizes radioisotope production.

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