In-core refueling optimization for a nuclear reactor
Corressponding author's email:
binhqd@hcmute.edu.vnKeywords:
Nuclear reactor, Reactor calculation, Refueling optimization, Refueling pattern, Genetic algorithm, Elitism strategyAbstract
This paper presents results from the problem of in-core refueling optimization for a nuclear research reactor. The aim of the optimization problem is to maximize the effective multiplication factor while satisfying the safety-related neutron parameters of the reactor. A genetic algorithm combined with the elitism strategy is used to solve the problem. The genetic algorithm works on the populations of chromosomes which are one-dimensional integer chromosomes. An investigation is performed for a nuclear research reactor type TRIGA MARK II to search for the optimal fuel loading patterns for its second operational cycle. Global reactor calculation is carried out using the nuclear reactor core analysis code CITATION
Downloads: 0
References
J.H. Holland, Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor, Michigan, 1975.
D.F. Goldberg, Genetic algorithms in search optimization and machine learning, Addison Wesley, Reading, Massachusetts, 1989.
S.M. Yang, D.G. Shao, Y.J. Luo, “A novel evolution strategy for multiobjective optimization problem,” Appl. Math. Comput. , 170, 2005, 850–873.
A. Yamamoto, “A quantitative comparison of loading pattern optimization methods for in-core fuel management of PWR,” J. Nucl. Sci.Technol., 34, 1997, 339–347.
T.B. Fowler, D.R. Vondy, F.B. Kemshell, Nuclear reactor core analysis code: CITATION, ORNL-TM-2496, RSICC, 1971.
Q. B. Do and P. L. Nguyen, “Application of a genetic algorithm to the fuel reload optimization for a research reactor”. Applied Mathematics and Computation, USA, Vol. 187, 2007, 977-988.
Đỗ Quang Bình, Nguyễn Hoàng Hải, “Nghiên cứu tối ưu hóa thay đảo nhiên liệu lò phản ứng hạt nhân bằng thuật toán di truyền”, Tuyển tập báo cáo khoa học Hội nghị KH- CNHN lần VIII Nha Trang-2009.
Downloads
Published
How to Cite
Issue
Section
Categories
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright © JTE.
