Method and system for optimizing irradiation spectrum of a reactor producing radioisotopes

Abstract

This invention relates to a method and system for optimizing the irradiation energy spectrum of reactors producing radioisotopes. The method employs an intelligent optimization algorithm (genetic algorithm) to construct a large number of irradiation energy spectra, builds a burnup database based on these spectra, and performs burnup calculations to determine the yield of various radioisotopes. This determines the optimal energy spectrum for producing various radioisotopes and their theoretically highest yield, thereby improving the production efficiency of reactors irradiating various radioisotopes. Compared with existing technologies, the method of this invention can determine the optimal irradiation energy spectrum and theoretically highest yield for reactors producing multiple radioisotopes, overcoming the limitations of traditional methods that struggle to determine the optimal irradiation energy spectrum for reactor irradiation production of various radioisotopes and achieve energy spectrum optimization.

Description

Technical Field

[0001] This invention relates to a technology in the field of reactor radioisotope production, and in particular to a method and system for optimizing the irradiation energy spectrum of reactor radioisotope production. Specifically, it uses intelligent optimization technology to determine the optimal irradiation energy spectrum and yield of various radioisotopes produced in a reactor. Background Technology

[0002] Irradiating a target within a reactor is the mainstream method for producing radioisotopes. However, it faces challenges such as the unknown optimal irradiation energy spectrum and the difficulty in achieving energy spectrum optimization, resulting in low isotope yields and poor production economics. Achieving energy spectrum optimization in reactor isotope production can effectively improve the yield of radioisotopes and the economics of actual production, demonstrating significant engineering value and application prospects. Summary of the Invention

[0003] This invention addresses the difficulty in determining the optimal irradiation energy spectrum for reactor irradiation production of various radioisotopes and the challenge in achieving energy spectrum optimization in existing technologies. It proposes a method and system for optimizing the energy spectrum of reactor radioisotope production. This method employs an intelligent optimization algorithm to construct a large number of irradiation energy spectra, builds a burnup database based on these spectra, and performs burnup calculations to determine the yield of various radioisotopes. This allows for the determination of the optimal energy spectrum for producing various radioisotopes and their theoretically highest yield, thereby improving the production efficiency of reactor irradiation for producing various radioisotopes.

[0004] This invention is achieved through the following technical solution:

[0005] The first objective of this invention is to provide a method for optimizing the energy spectrum of radioactive isotopes produced in a reactor, the specific implementation steps of which are as follows:

[0006] Step 1: Determine the parameters of the intelligent optimization process: This invention uses a genetic algorithm as the core of the intelligent optimization unit. The initialization process requires determining the number of generations G and the population size P, randomly generating P individuals, and constructing an initial irradiation spectrum library;

[0007] Step 2: Based on the various irradiation energy spectra in the irradiation energy spectrum library obtained in Step 1 or Step 4, construct a fuel consumption database for various irradiation energy spectra: different irradiation energy spectra correspond to different macroscopic single-group cross sections. Compress and merge the groups to obtain the single-group cross sections corresponding to various irradiation energy spectra, thus obtaining a fuel consumption database based on various irradiation energy spectra, providing a fuel consumption database for subsequent ignition fuel consumption calculation.

[0008] Step 3: Quantify the production efficiency of various irradiation energy spectra: Based on the fuel consumption database of various irradiation energy spectra, call the fuel consumption calculation program, execute the fuel consumption calculation, and obtain the actual output of radioactive isotopes under various irradiation energy spectra. This output is the production efficiency of various irradiation energy spectra, and the production efficiency of various irradiation energy spectra is obtained.

[0009] Step 4: Constructing an irradiation spectrum library: Based on the production efficiency of various irradiation spectra obtained in Step 3, select the irradiation spectra with the highest production efficiency and perform crossover and mutation operations to generate the next generation of irradiation spectrum library.

[0010] Step 5: Iteration Termination: Repeat steps (2)-(4) until the G generation population has completed its evolution, and output the optimal irradiation spectrum (the irradiation spectrum corresponding to the highest theoretical radioactive isotope yield is the optimal irradiation spectrum) and the highest theoretical radioactive isotope yield of that isotope.

[0011] Furthermore, the aforementioned radioactive isotope refers to: 99 Mohe 188 Medical isotopes represented by Re and those with 252 Cf and 238 Pu is a transuranic isotope.

[0012] Furthermore, the radioactive isotope is selected from... 99 Mo、 188 Re、 252 Cf、 238 One or more of Pu, etc.

[0013] Furthermore, the aforementioned crossover operation refers to randomly exchanging the neutron flux in certain energy segments of two irradiation spectra to obtain two new irradiation spectra.

[0014] Furthermore, the mutation operation refers to randomly modifying the neutron flux of certain energy segments of certain irradiation energy spectra to obtain a new irradiation energy spectrum.

[0015] Furthermore, the aforementioned compressed group refers to: weighted accumulation of microscopic cross-sections based on the neutron energy spectrum to obtain a single-group macroscopic cross-section. Weighted accumulation: based on the distribution of the neutron energy spectrum, the microscopic cross-sections of each energy group are weighted and averaged to obtain a single, averaged cross-section value.

[0016] Furthermore, the aforementioned selection of the irradiation spectrum with the highest production efficiency for crossover and mutation operations refers to selecting the top 50% of the irradiation spectrum with the highest output to enter the next generation for crossover and mutation operations.

[0017] Furthermore, the theoretically highest radioactive isotope yield is the highest single radioactive isotope yield.

[0018] The second objective of this invention is to provide an energy spectrum optimization system for reactor production of radioactive isotopes, which is used for the aforementioned energy spectrum optimization method for reactor production of radioactive isotopes, including: an intelligent optimization unit, which is used for an intelligent optimization process of the irradiation energy spectrum.

[0019] Furthermore, the intelligent optimization unit includes an irradiation energy spectrum library unit, a fuel consumption database unit, and a fuel consumption calculation unit, wherein: the irradiation energy spectrum library unit is used to collect, sort, and construct various irradiation energy spectra; the fuel consumption database unit is used to construct a fuel consumption database for various irradiation energy spectra; and the fuel consumption calculation unit is used to evaluate the economics of using various irradiation energy spectra for the production of radioactive isotopes.

[0020] Furthermore, the method for optimizing the irradiation energy spectrum of the reactor for producing radioactive isotopes is used to determine the optimal energy spectrum under different irradiation conditions and the theoretically highest radioactive isotope yield for that isotope.

[0021] Furthermore, the irradiation conditions include flux level and / or irradiation duration.

[0022] Compared with the prior art, the technical effects of the present invention are as follows:

[0023] 1) This invention uses a genetic algorithm to construct a large number of irradiation energy spectra, builds a burnup database for these irradiation energy spectra, performs burnup calculations to determine the yield of various radioactive isotopes, thereby determining the optimal energy spectrum for producing various radioactive isotopes and their theoretical maximum yield, improving the production efficiency of reactor irradiation for producing various radioactive isotopes. It can determine the optimal irradiation energy spectrum for reactor production of multiple radioactive isotopes and their theoretical maximum yield, breaking through the limitations of traditional methods that make it difficult to determine the optimal irradiation energy spectrum for reactor irradiation for producing various radioactive isotopes and achieve energy spectrum optimization.

[0024] 2) This invention avoids multiple blind Monte Carlo burnup calculations, is efficient and universal, and can provide more quantitative physical information references for the design and optimization of reactor isotope production schemes. Attached Figure Description

[0025] Figure 1 This is a flowchart of the present invention;

[0026] Figure 2 For different flux levels and irradiation durations 188 Re production limits;

[0027] Figure 3 For different flux levels and irradiation durations 252 Cf production limit;

[0028] Figure 4For different flux levels and irradiation durations 188 The optimal energy spectrum of Re;

[0029] Figure 5 For different flux levels and irradiation durations 252 The optimal energy spectrum of Cf. Detailed Implementation

[0030] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Component models, material names, connection structures, control methods, and other features not explicitly described in this technical solution are considered common technical features disclosed in the prior art.

[0031] This invention provides a method for optimizing the irradiation energy spectrum of reactors for producing radioactive isotopes, comprising the following steps:

[0032] Step 1: Determine the parameters of the intelligent optimization process: This invention uses a genetic algorithm as the core of the intelligent optimization unit. The initialization process requires determining the number of generations G and the population size P, randomly generating P individuals, and constructing an initial irradiation spectrum library;

[0033] Step 2: Construct a fuel consumption database for various irradiation energy spectra: Different irradiation energy spectra correspond to different macroscopic single-group cross sections. By compressing and merging the groups, we can obtain single-group cross sections corresponding to various irradiation energy spectra, providing a fuel consumption database for subsequent ignition fuel consumption calculations.

[0034] Step 3: Quantify the production efficiency of various irradiation energy spectra: Based on the fuel consumption database of various irradiation energy spectra, call the fuel consumption calculation program, execute the fuel consumption calculation, and obtain the actual output of radioactive isotopes under various irradiation energy spectra. This output is the production efficiency of various irradiation energy spectra.

[0035] Step 4: Constructing an irradiation spectrum library: Select the irradiation spectrum with the highest production efficiency and perform crossover and mutation operations to generate the next generation of irradiation spectrum library;

[0036] Step 5: Iteration Termination: Repeat steps (2)-(4) until the G generation population has evolved and outputs the optimal irradiation spectrum and its theoretically highest radioactive isotope yield.

[0037] like Figure 1As shown, the present invention also provides an energy spectrum optimization system for reactor production of radioisotopes, used in the aforementioned method for energy spectrum optimization in reactor production of radioisotopes. The system includes an intelligent optimization unit for intelligent optimization of the irradiation energy spectrum. The intelligent optimization unit comprises an irradiation energy spectrum library unit, a fuel consumption database unit, and a fuel consumption calculation unit. Specifically, the irradiation energy spectrum library unit collects, sorts, and constructs various irradiation energy spectra; the fuel consumption database unit constructs a fuel consumption database for various irradiation energy spectra; and the fuel consumption calculation unit evaluates the economic viability of various irradiation energy spectra for radioisotope production.

[0038] Example

[0039] This embodiment focuses on the production of medical isotopes. 188 Re and transuranic isotopes 252 Taking Cf as an example, production 188 The target for Re is WO3, and its nucleon density is shown in Table 1. Production 252 The target for Cf is a mixture of plutonium-americium-curium, and its nucleon density is shown in Table 2.

[0040] Table 1. Production 188 Target nucleus density of Re

[0041]

[0042]

[0043] Table 2. Production 252 Cf target nucleon density

[0044]

[0045] This embodiment uses a genetic algorithm as the core of the intelligent optimization unit. The number of generations G and the population size are both selected as 200. Therefore, the initialization process constructs 200 initial energy spectra. Each irradiation energy spectrum consists of 238 groups of neutron flux. That is, the neutron flux in the full energy range is divided into 238 groups of neutron flux according to the SCALE-238 energy group framework, and the neutron flux of these 238 groups is normalized.

[0046] In constructing the fuel consumption database for various irradiation energy spectra, this embodiment uses the 238 group cross sections in the JANIS kernel database software. By compressing and merging the groups, single group cross sections corresponding to various irradiation energy spectra are obtained, providing a fuel consumption database for subsequent ignition fuel consumption calculations.

[0047] In quantifying the production efficiency of various irradiation energy spectra, this embodiment uses the OpenMC program to calculate the actual production of radioactive isotopes corresponding to various irradiation energy spectra.

[0048] In constructing the next-generation irradiation spectrum library, this embodiment selects an inheritance rate of 50% (selecting the top 50% of the energy spectrum to enter the next generation), a crossover rate of 40% (40% of the energy range between two energy spectra is exchanged), and a mutation rate of 40% (40% of the energy range of a single energy spectrum is changed).

[0049] To determine the optimal energy spectrum for different flux levels and irradiation durations, the flux levels considered in this embodiment include: 1×10⁻⁶. 12 5×10 12 1×10 13 2×10 13 3×10 13 4×10 13 5×10 13 6×10 13 7×10 13 8×10 13 9×10 13 1×10 14 2×10 14 3×10 14 4×10 14 5×10 14 6×10 14 7×10 14 8×10 14 9×10 14 1×10 15 2×10 15 3×10 15 4×10 15 5×10 15 6×10 15 7×10 15 8×10 15 9×10 15 1×10 16 2×10 16 3×10 16 4×10 16 5×10 16 1×10 17 (cm -2 ·s -1 This embodiment considers irradiation durations including: 5 days, 10 days, 20 days, 40 days, 60 days, 80 days, 100 days, 120 days, 140 days, 160 days, 180 days, and 200 days. Therefore, this embodiment targets... 188 Re and 252 Cf determined the optimal energy spectrum under 12×35=420 irradiation conditions.

[0050] Different flux levels and irradiation durations 188 Re production limits such as Figure 2 As shown, under different flux levels and irradiation durations 252 Cf production limit such as Figure 3 As shown, the overall trend is that the higher the flux level and the longer the irradiation time, the higher the production of radioactive isotopes. However, the irradiation process also has the problem of excessive burn-off. That is, when the flux level and irradiation time reach a certain level, the production of radioactive isotopes will be gradually consumed after reaching its limit, thus leading to a decrease in production.

[0051] Because each optimal energy spectrum consists of 238 neutron flux groups, and a total of 420 irradiation conditions are considered, the amount of data is enormous. Therefore, this embodiment presents the optimal energy spectrum distribution under different flux levels and different irradiation durations using a color scale diagram. 188 The optimal energy spectrum of Re is as follows Figure 4 As shown, 252 The optimal energy spectrum of Cf is as follows Figure 5 As shown, it can be seen that the higher the flux level and the longer the irradiation time, the worse the continuity of the optimal energy spectrum. That is, the optimal energy spectrum is not a continuous spectrum, but is composed of multiple discrete neutron fluxes in different energy ranges. Figure 4 , Figure 5 In the vertical axis, the flux level and irradiation duration are sorted as follows: first, flux levels are arranged from low to high; then, within each flux level, irradiation duration is arranged from short to long, starting with 1 and numbered sequentially, such as flux level 1×10. 12 cm -2 ·s -1 When the irradiation duration is 5 days, the value is 1, and the flux level is 1×10⁻⁶. 12 cm -2 ·s -1 When the irradiation duration is 10 days, the flux level is 2, ..., 1×10⁻⁶. 17 cm -2 ·s -1 The irradiation duration is 420 for 200 days. Figure 4 , Figure 5 In the diagram, the energy ranges labeled 1-238 on the horizontal axis represent the 238 energy regions of the neutron flux in the 238 group.

[0052] This invention can determine the optimal irradiation energy spectrum and the theoretical maximum yield of various radioactive isotopes produced by reactors, providing theoretical guidance for the optimization of the energy spectrum of reactor irradiation for the production of radioactive isotopes.

[0053] The above-described specific implementations can be partially adjusted by those skilled in the art in different ways without departing from the principles and purpose of the present invention. The scope of protection of the present invention is defined by the claims and is not limited to the above-described specific implementations. All implementation schemes within the scope of the claims are bound by the present invention.

Claims

1. A method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes, characterized in that, The method includes the following steps: Step 1: Determine the generation number G and population size P, randomly generate P individuals, and construct the initial irradiation spectrum library; Step 2: Based on the various irradiation energy spectra in the irradiation energy spectrum library obtained in Step 1 or Step 4, construct a fuel consumption database for various irradiation energy spectra. Step 3: Based on the fuel consumption database of various irradiation energy spectra obtained in Step 2, perform fuel consumption calculation to obtain the actual output of radioactive isotopes under various irradiation energy spectra. This output is the production efficiency of various irradiation energy spectra. Step 4: Based on the production efficiency of various irradiation energy spectra obtained in Step 3, select the irradiation energy spectra with the highest production efficiency for cross-operation and mutation operation to generate the next generation of irradiation energy spectrum library. Step 5: Repeat steps (2)-(4) until the G generation population has evolved and outputs the best irradiation spectrum and the theoretically highest radioactive isotope yield.

2. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 1, characterized in that, The radioisotope is selected from one or more of 99 Mo, 188 Re, 252 Cf, 238 Pu.

3. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 1, characterized in that, The aforementioned crossover operation refers to randomly exchanging the neutron flux in certain energy segments of two irradiation spectra to obtain two new irradiation spectra.

4. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 1, characterized in that, The mutation operation refers to randomly modifying the neutron flux in certain energy ranges of certain irradiation spectra to obtain a new irradiation spectrum.

5. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 1, characterized in that, The process of step 2 is as follows: Based on the various irradiation energy spectra in the irradiation energy spectrum library obtained in step 1 or step 4, different irradiation energy spectra correspond to different macroscopic single-group cross sections. By compressing and grouping, the single-group cross sections corresponding to various irradiation energy spectra are obtained, providing a fuel consumption database for subsequent ignition fuel consumption calculation.

6. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 5, characterized in that, The term "compressed group" refers to the process of weighting and accumulating microscopic cross sections based on neutron energy spectra to obtain a single-group macroscopic cross section.

7. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 1, characterized in that, The process of step 3 is as follows: Based on a fuel consumption database of various irradiation energy spectra, the ignition fuel consumption calculation program is called to perform the ignition fuel consumption calculation and obtain the actual output of radioactive isotopes under various irradiation energy spectra. This output is the production efficiency of various irradiation energy spectra.

8. The method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes according to claim 1, characterized in that, The selection of the irradiation spectrum with the highest production efficiency for crossover and mutation operations refers to selecting the top 50% of the irradiation spectrum with the highest output to enter the next generation for crossover and mutation operations.

9. A system for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes, said system being used in the method for optimizing the irradiation energy spectrum of a reactor for producing radioactive isotopes as described in any one of claims 1-8, characterized in that, The irradiation energy spectrum optimization system for producing radioisotopes in the reactor includes an intelligent optimization unit. The intelligent optimization unit is used for the intelligent optimization process of the irradiation energy spectrum, and a genetic algorithm is used as the core algorithm of the intelligent optimization unit.

10. The irradiation energy spectrum optimization system for reactor production of radioactive isotopes according to claim 9, characterized in that, The intelligent optimization unit includes: Irradiation spectrum library unit, used to collect, sort and construct various irradiation spectra; The fuel consumption database unit is used to construct fuel consumption databases for various irradiation energy spectra. The ignition consumption calculation unit is used to evaluate the economics of using various irradiation energy spectra for the production of radioactive isotopes.

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