This paper is the optimization of fuel assembly placement in the spent fuel pool according to the categorized rules. Only some specifically reactivity class assemblies could put together as the pattern. The allowable patterns, the number of the fuel assembly for each reactivity class and the number of RCCAs are from the nuclear power plant technique specification. Each assembly in the pool should obey the pattern rules and the user needs the optimal spent fuel pool configuration that could maximize the free space. In this study, the genetic algorithm and greedy algorithm are discussed, and both of two algorithms have the difficulties to the real engineering problem. A new approach that improves the greedy strategy at each step is proposed, make the greedy algorithm is more adapted to the engineering problem. Use the new approach to test Seabrook Unit 1 and Arkansas Unit 2 spent fuel pool at different cases, and show results by the visible figures. The output arrangements by the program shown that the results are satisfied the user requirements.
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2018 26th International Conference on Nuclear Engineering
July 22–26, 2018
London, England
Conference Sponsors:
- Nuclear Engineering Division
ISBN:
978-0-7918-5153-1
PROCEEDINGS PAPER
Optimization of Fuel Storage in Spent Fuel Pool
Xinyu Wang,
Xinyu Wang
Harbin Engineering University, Harbin, China
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Richard Cable Kurwitz,
Richard Cable Kurwitz
Texas A&M University, College Station, TX
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Zhijian Zhang
Zhijian Zhang
Harbin Engineering University, Harbin, China
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Xinyu Wang
Harbin Engineering University, Harbin, China
Richard Cable Kurwitz
Texas A&M University, College Station, TX
Zhijian Zhang
Harbin Engineering University, Harbin, China
Paper No:
ICONE26-81084, V009T16A006; 10 pages
Published Online:
October 24, 2018
Citation
Wang, X, Kurwitz, RC, & Zhang, Z. "Optimization of Fuel Storage in Spent Fuel Pool." Proceedings of the 2018 26th International Conference on Nuclear Engineering. Volume 9: Student Paper Competition. London, England. July 22–26, 2018. V009T16A006. ASME. https://doi.org/10.1115/ICONE26-81084
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