A Metropolis algorithm combined with Nelder-Mead Simplex applied to nuclear reactor core design

被引：13

作者：

Sacco, Wagner F. ^{[1
]}

Alves Filho, Hermes ^{[1
]}

Henderson, Nelio ^{[1
]}

de Oliveira, Cassiano R. E. ^{[2
]}

机构：

[1] Univ Estado Rio de Janerio, Inst Politecn, Depto Modelagem Computac, BR-28601970 Nova Friburgo, Brazil

[2] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Nucl & Radiol Engn Program, Atlanta, GA 30332 USA

来源：

ANNALS OF NUCLEAR ENERGY | 2008年 / 35卷 / 05期

关键词：

D O I：

10.1016/j.anucene.2007.09.006

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：

A hybridization of the recently introduced Particle Collision Algorithm (PCA) and the Nelder-Mead Simplex algorithm is introduced and applied to a core design optimization problem which was previously attacked by other metaheuristics. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, ill order to minimize the average peak-factor in a three-enrichment-zone reactor, considering restrictions on the average thermal flux, criticality and sub-moderation. The new metaheuristic performs better than the genetic algorithm, particle swarm optimization, and the Metropolis algorithms PCA and the Great Deluge Algorithm, thus demonstrating its potential for other applications. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：861 / 867

页数：7

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