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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2016.1
- 수록면
- 1,126 - 1,139 (14page)
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초록· 키워드
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In this research, for the first time, a new optimization method, i.e., strength Pareto evolutionary algorithm II (SPEA-II), is developed for the burnable poison placement (BPP) optimization of a nuclear reactor core. In the BPP problem, an optimized placement map of fuel assemblies with burnable poison is searched for a given core loading pattern according to defined objectives. In this work, SPEA-II coupled with a nodal expansion code is used for solving the BPP problem of Kraftwerk Union AG (KWU) pressurized water reactor. Our optimization goal for the BPP is to achieve a greater multiplication factor (Keff) for gaining possible longer operation cycles along with more flattening of fuel assembly relative power distribution, considering a safety constraint on the radial power peaking factor. For appraising the proposed methodology, the basic approach, i.e., SPEA, is also developed in order to compare obtained results. In general, results reveal the acceptance performance and high strength of SPEA, particularly its new version, i.e., SPEA-II, in achieving a semioptimized loading pattern for the BPP optimization of KWU pressurized water reactor.
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등록된 정보가 없습니다.
참고문헌 (18)
참고문헌 신청
S. Kashi / 2014 / Bat algorithm for the fuel arrangement optimization of reactor core / Ann. Nucl. Eng 64:144~151
T.J. Rogers / 2008 / PWR Fuel Assembly Optimization Using Adaptive Simulated Annealing Coupled with TRANSLAT
S. Yilmaz / 2006 / Application of genetic algorithms to optimize burnable poison placement in pressurizedwater reactors / Ann.Nucl. Energy 33:446~456
T. Rogers / 2009 / Optimization of PWR fuel assembly radial enrichment and burnable poison location based on adaptive simulated annealing / Nucl. Sci. Eng 239:1019~1029
F. Alim / 2008 / New genetic algorithms (GA)to optimize PWR reactors part I: loading pattern and burnable poison placement optimization techniques for PWRs / Ann. Nucl. Energy 35:93~112
T.J. Rogers / 2008 / PWR Fuel Assembly Optimization Using Adaptive Simulated Annealing Coupled with TRANSLAT
S. Yilmaz / 2006 / Application of genetic algorithms to optimize burnable poison placement in pressurizedwater reactors / Ann.Nucl. Energy 33:446~456
T. Rogers / 2009 / Optimization of PWR fuel assembly radial enrichment and burnable poison location based on adaptive simulated annealing / Nucl. Sci. Eng 239:1019~1029
F. Alim / 2008 / New genetic algorithms (GA)to optimize PWR reactors part I: loading pattern and burnable poison placement optimization techniques for PWRs / Ann. Nucl. Energy 35:93~112
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