Core map generation for the ITU TRIGA Mark II research reactor using Genetic Algorithm coupled with Monte Carlo method

被引:0
|
作者
Turkmen, Mehmet [1 ]
Colak, Uner [2 ]
Ergun, Sule [1 ]
机构
[1] Hacettepe Univ, Dept Nucl Engn, Ankara, Turkey
[2] Istanbul Tech Univ, Energy Inst, TR-80626 Istanbul, Turkey
关键词
FUEL-MANAGEMENT; LOADING PATTERN; OPTIMIZATION; BURNUP;
D O I
10.1016/j.nucengdes.2015.08.022
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
The main purpose of this study is to present the results of Core Map (CM) generation calculations for the Istanbul Technical University TRIGA Mark II Research Reactor by using Genetic Algorithms (GA) coupled with a Monte Carlo (MC) based-particle transport code. Optimization problems under consideration are: (i) maximization of the core excess reactivity (rho(ex)) using Single-Objective GA when the burned fuel elements with no fresh fuel elements are used, (ii) maximization of the rho(ex) and minimization of maximum power peaking factor (ppf(max)) using Multi-Objective GA when the burned fuels with fresh fuels are used. The results were obtained when all the control rods are fully withdrawn. rho(ex) and ppf(max) values of the produced best CMs were provided. Core-averaged neutron spectrum, and variation of neutron fluxes with respect to radial distance were presented for the best CMs. The results show that it is possible to find an optimum CM with an excess reactivity of 1.17 when the burned fuels are used. In the case of a mix of burned fuels and fresh fuels, the best pattern has an excess reactivity of 1.19 with a maximum peaking factor of 1.4843. In addition, when compared with the fresh CM, the thermal fluxes of the generated CMs decrease by about 2% while change in the fast fluxes is about 1%.Classification: J. Core physics (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:84 / 95
页数:12
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