Please use this identifier to cite or link to this item: http://carpedien.ien.gov.br:8080/handle/ien/2641
Tipo: article
Título: Parallel island genetic algorithm applied to a nuclear power plant auxiliary feedwater system surveillance tests policy optimization
Autor(es): Pereira, Cláudio Márcio Nascimento Abreu
Lapa, Celso Marcelo Franklin
Resumo: In this work, we focus the application of an Island Genetic Algorithm (IGA), a coarse-grained parallel genetic algorithm (PGA) model, to a Nuclear Power Plant (NPP) Auxiliary Feedwater System (AFWS) surveillance tests policy optimization. Here, the main objective is to outline, by means of comparisons, the advantages of the IGA over the simple (non-parallel) genetic algorithm (GA), which has been successfully applied in the solution of such kind of problem. The goal of the optimization is to maximize the system's average availability for a given period of time, considering realistic features such as: i) aging effects on standby components during the tests; ii) revealing failures in the tests implies on corrective maintenance, increasing outage times; iii) components have distinct test parameters (outage time, aging factors, etc.) and iv) tests are not necessarily periodic. In our experiments, which were made in a cluster comprised by 8 1-GHz personal computers, we could clearly observe gains not only in the computational time, which reduced linearly with the number of computers, but in the optimization outcome.
Palavras-chave: Genetic algorithms
Parallel computation
Surveillance Tests Policy Optimization
Idioma: eng
País: Estados unidos
Editor: Instituto de Engenharia Nuclear
Sigla da Instituição: IEN
Tipo de Acesso: embargoedAccess
URI: http://carpedien.ien.gov.br:8080/handle/ien/2641
Data do documento: Apr-2003
Appears in Collections:Realidade Virtual Aplicada na Área Nuclear - Artigos de Periódicos

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