Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame
The optimization design of fast reactors faces two major problems: insufficient design or operation experience and more complicated optimization objectives, compared with pressurized water reactor (PWR). An optimization method which is independent of application banckground and experience is require...
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| Format: | Article |
| Language: | English |
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Editorial Board of Atomic Energy Science and Technology
2022-01-01
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| Series: | Yuanzineng kexue jishu |
| Subjects: | |
| Online Access: | https://www.aest.org.cn/CN/10.7538/yzk.2021.youxian.0494 |
| _version_ | 1811216767929810944 |
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| author | LI Xiaoqi;ZHENG Youqi;DU Xianan;WANG Yongping |
| author_facet | LI Xiaoqi;ZHENG Youqi;DU Xianan;WANG Yongping |
| author_sort | LI Xiaoqi;ZHENG Youqi;DU Xianan;WANG Yongping |
| collection | DOAJ |
| description | The optimization design of fast reactors faces two major problems: insufficient design or operation experience and more complicated optimization objectives, compared with pressurized water reactor (PWR). An optimization method which is independent of application banckground and experience is required. Intelligent optimization algorithm is a strategy for the search of optimal or satisfactory solution for given design objectives and satisfies above requirements. In the process of search, multiple design objectives and constraints are considered simultaneously and the times of search and calculation are limited. Genetic algorithm is a classical and representative method in numerous of optimization algorithms, which performs well in solving multi-objective problems with constraints. Genetic algorithm has inherent parallel characteristics as well for which the searching efficiency is able to be increased. Based on a genetic algorithm module in an open source toolkit DAKOTA and a self-developed neutron transport program SARAX, an optimal design frame for fast reactors with multivariable, multi-objective and multi-constraint problems was constructed in this work. Both genetic algorithm module and neutron transport program performed as a black-box. A coding system that could transform a decimal integer and a loading pattern to each other was suggested and applied to this optimal frame. This coding strategy realized the coverage of the multi-dimensional search space, so that the optimal frame can deal with the problems of continuous and discrete variables. For the constrained multi-objective problem, the direct ranking method and the weighted sum method were both applied and compared. Two cases were analyzed to test this frame: 1) Rearrange the subassemblies of ABTR to find a scheme whose keff and power peak factor meet the given expectations, the searching result was compared with the enumeration results; 2) Optimizing the design of the loading position of the 237Np-containing subassemblies for China Experimental Fast Reactor (CEFR). The objective of this case was obtaining more 238Pu after a cycle of burnup, ensuring safety constraints. The first calculation example was used to verify the feasibility of the new coding scheme. The second case demonstrated the specific application of the optimal frame in engineering practice. According to the numerical results, the fast reactor optimal frame proposed in this work achieves the research objectives of finding the best solutions and meeting the requirements under a limited number of searches with multiple variables, multiple design objectives and multiple constraints. What’s more, the coding of variables, the optimization objectives setting and the given of constraints are all of strong flexibility. To sum up, this frame can cope with the complex requirements of fast reactor engineering design. |
| first_indexed | 2024-04-12T06:44:56Z |
| format | Article |
| id | doaj.art-8e0df355d96147a7aaa70e4ab87e2ef3 |
| institution | Directory Open Access Journal |
| issn | 1000-6931 |
| language | English |
| last_indexed | 2024-04-12T06:44:56Z |
| publishDate | 2022-01-01 |
| publisher | Editorial Board of Atomic Energy Science and Technology |
| record_format | Article |
| series | Yuanzineng kexue jishu |
| spelling | doaj.art-8e0df355d96147a7aaa70e4ab87e2ef32022-12-22T03:43:37ZengEditorial Board of Atomic Energy Science and TechnologyYuanzineng kexue jishu1000-69312022-01-0156196105Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal FrameLI Xiaoqi;ZHENG Youqi;DU Xianan;WANG Yongping 0School of Nuclear Science and Technology, Xi’an Jiaotong University, Xi’an 710049, ChinaThe optimization design of fast reactors faces two major problems: insufficient design or operation experience and more complicated optimization objectives, compared with pressurized water reactor (PWR). An optimization method which is independent of application banckground and experience is required. Intelligent optimization algorithm is a strategy for the search of optimal or satisfactory solution for given design objectives and satisfies above requirements. In the process of search, multiple design objectives and constraints are considered simultaneously and the times of search and calculation are limited. Genetic algorithm is a classical and representative method in numerous of optimization algorithms, which performs well in solving multi-objective problems with constraints. Genetic algorithm has inherent parallel characteristics as well for which the searching efficiency is able to be increased. Based on a genetic algorithm module in an open source toolkit DAKOTA and a self-developed neutron transport program SARAX, an optimal design frame for fast reactors with multivariable, multi-objective and multi-constraint problems was constructed in this work. Both genetic algorithm module and neutron transport program performed as a black-box. A coding system that could transform a decimal integer and a loading pattern to each other was suggested and applied to this optimal frame. This coding strategy realized the coverage of the multi-dimensional search space, so that the optimal frame can deal with the problems of continuous and discrete variables. For the constrained multi-objective problem, the direct ranking method and the weighted sum method were both applied and compared. Two cases were analyzed to test this frame: 1) Rearrange the subassemblies of ABTR to find a scheme whose keff and power peak factor meet the given expectations, the searching result was compared with the enumeration results; 2) Optimizing the design of the loading position of the 237Np-containing subassemblies for China Experimental Fast Reactor (CEFR). The objective of this case was obtaining more 238Pu after a cycle of burnup, ensuring safety constraints. The first calculation example was used to verify the feasibility of the new coding scheme. The second case demonstrated the specific application of the optimal frame in engineering practice. According to the numerical results, the fast reactor optimal frame proposed in this work achieves the research objectives of finding the best solutions and meeting the requirements under a limited number of searches with multiple variables, multiple design objectives and multiple constraints. What’s more, the coding of variables, the optimization objectives setting and the given of constraints are all of strong flexibility. To sum up, this frame can cope with the complex requirements of fast reactor engineering design.https://www.aest.org.cn/CN/10.7538/yzk.2021.youxian.0494fast reactormulti-objective optimizationgenetic algorithmsarax |
| spellingShingle | LI Xiaoqi;ZHENG Youqi;DU Xianan;WANG Yongping Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame Yuanzineng kexue jishu fast reactor multi-objective optimization genetic algorithm sarax |
| title | Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame |
| title_full | Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame |
| title_fullStr | Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame |
| title_full_unstemmed | Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame |
| title_short | Research on Multi-objective Optimization of Fast Reactor and Development of SARAX/DAKOTA Optimal Frame |
| title_sort | research on multi objective optimization of fast reactor and development of sarax dakota optimal frame |
| topic | fast reactor multi-objective optimization genetic algorithm sarax |
| url | https://www.aest.org.cn/CN/10.7538/yzk.2021.youxian.0494 |
| work_keys_str_mv | AT lixiaoqizhengyouqiduxiananwangyongping researchonmultiobjectiveoptimizationoffastreactoranddevelopmentofsaraxdakotaoptimalframe |