Energy group structure determination using particle swarm optimization

被引：15

作者：

Yi, Ce ^{[1
]}

Sjoden, Glenn ^{[1
]}

机构：

[1] Georgia Inst Technol, Atlanta, GA 30313 USA

来源：

ANNALS OF NUCLEAR ENERGY | 2013年 / 56卷

关键词：

Cross section down-sampling; Group structure; Particle swarm optimization;

D O I：

10.1016/j.anucene.2012.12.020

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：

Multi-group theory is widely applied for the energy domain discretization when solving the Linear Boltzmann Equation. To reduce the computational cost, fine group cross libraries are often down-sampled into broad group cross section libraries. Cross section data collapsing generally involves two steps: Firstly, the broad group structure has to be determined; secondly, a weighting scheme is used to evaluate the broad cross section library based on the fine group cross section data and the broad group structure. A common scheme is to average the fine group cross section weighted by the fine group flux. Cross section collapsing techniques have been intensively researched. However, most studies use a pre-determined group structure, open based on experience, to divide the neutron energy spectrum into thermal, epi-thermal, fast, etc. energy range. In this paper, a swarm intelligence algorithm, particle swarm optimization (PSO), is applied to optimize the broad group structure. A graph representation of the broad group structure determination problem is introduced. And the swarm intelligence algorithm is used to solve the graph model. The effectiveness of the approach is demonstrated using a fuel-pin model. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：53 / 56

页数：4

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