AXIAL: a system for boiling water reactor fuel assembly axial optimization using genetic algorithms |
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| Affiliation: | 1. Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, United Kingdom;2. Paul Scherrer Institut, PSI Aarebrücke, 5232 Villigen, Switzerland;3. Rhode Island Nuclear Science Centre, 16 Reactor Rd, Narragansett, RI 02882, USA;1. Department of Nuclear Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, Republic of Korea;2. China Institute of Atomic Energy, POB 275(95), Beijing, 102413, China;3. Helmholtz-Zentrum Dresden-Rossendorf, Bautzner Landstraße 400, 01328, Dresden, Germany;4. Advanced Nuclear Technology and Services, 406-21 Jonga-ro, Jung-gu, Ulsan, 44429, Republic of Korea;1. School of Electric Power, South China University of Technology, Guangzhou 510640, Guangdong, China;2. School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, PR China;1. Departamento de Sistemas Nucleares, Instituto Nacional de Investigaciones Nucleares de México, Carr. México Toluca S/N, La Marquesa Ocoyoacac, Edo México, Mexico;2. Dept. of Computer Science and AI, CITIC-UGR, ETSI Informática y de Telecomunicaciones, Universidad de Granada, C/Daniel Saucedo Aranda, s/n, 18014 Granada, Spain;1. Department of Mechanical Engineering, University of Suwon, 17 Wauan-gil, Bongdam-eup, Hwaseong-si, Gyeonggi-go, 18323, Republic of Korea;2. Nuclear Data Center, Korea Atomic Energy Research Institute (KAERI), Daedeok-daero 989-111, Yuseong-gu, Daejeon, 34057, Republic of Korea;3. SFR Reactor Design Division, Korea Atomic Energy Research Institute (KAERI), Daedeok-daero 989-111, Yuseong-gu, Daejeon, 34057, Republic of Korea;4. Department of Mechanical and Nuclear Engineering, University of Sharjah, P.O. BOX 27272, Sharjah, United Arab Emirates |
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| Abstract: | A system named AXIAL is developed based on the genetic algorithms (GA) optimization method, using the 3D steady state simulator code Core-Master-PRESTO (CM-PRESTO) to evaluate the objective function. The feasibility of this methodology is investigated for a typical boiling water reactor (BWR) fuel assembly (FA). The axial location of different fuel compositions is found in order to minimize the FA mean enrichment needed to obtain the cycle length under the safety constraints. Thermal limits are evaluated at the end of cycle using the Haling calculation; the hot excess reactivity and the shutdown margin at the beginning of cycle are also evaluated. The implemented objective function is very flexible and complete, incorporating all the thermal and reactivity limits imposed during fuel design analysis; furthermore, additional constraints can be easily introduced in order to obtain an improved solution. The results show a small improvement in the FA average enrichment obtained with the system related to the reference case that has been studied. The results show that the system converge to an optimal solution, it is observed that the mean fuel enrichment decreases while all the constraints are satisfied. A comparison was also performed using one-point and two-points crossover operator and the results of a sensitivity study for different mutation percentage are also showed. |
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