Pressurized water reactor reloading optimization using genetic algorithms

Wu Hongchun

doi:10.1016/S0306-4549(00)00122-5

Pressurized water reactor reloading optimization using genetic algorithms

Wu Hongchun

School of Energy and Power Engineering

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

The application of genetic algorithms (GAs) to pressurized water reactor (PWR) reloading pattern optimization is described. Standard bit-based genetic operators are used to optimize the arrangement of assemblies, burnable absorber, and burnt assembly orientations. The developed system has a modular structure. The GAs operators, reactor physics code, constraint conditions and objective function are all flexible. Test examples illustrating the effectiveness and flexibility of this system are presented and optimization results are discussed.

Original language	English
Pages (from-to)	1329-1341
Number of pages	13
Journal	Annals of Nuclear Energy
Volume	28
Issue number	13
DOIs	https://doi.org/10.1016/S0306-4549(00)00122-5
State	Published - Sep 2001

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title = "Pressurized water reactor reloading optimization using genetic algorithms",

abstract = "The application of genetic algorithms (GAs) to pressurized water reactor (PWR) reloading pattern optimization is described. Standard bit-based genetic operators are used to optimize the arrangement of assemblies, burnable absorber, and burnt assembly orientations. The developed system has a modular structure. The GAs operators, reactor physics code, constraint conditions and objective function are all flexible. Test examples illustrating the effectiveness and flexibility of this system are presented and optimization results are discussed.",

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AB - The application of genetic algorithms (GAs) to pressurized water reactor (PWR) reloading pattern optimization is described. Standard bit-based genetic operators are used to optimize the arrangement of assemblies, burnable absorber, and burnt assembly orientations. The developed system has a modular structure. The GAs operators, reactor physics code, constraint conditions and objective function are all flexible. Test examples illustrating the effectiveness and flexibility of this system are presented and optimization results are discussed.

UR - https://www.scopus.com/pages/publications/0035452819

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DO - 10.1016/S0306-4549(00)00122-5

M3 - 文章

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JO - Annals of Nuclear Energy

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Pressurized water reactor reloading optimization using genetic algorithms

Abstract

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