Proposta de utilização de redes neurais feedforward multicamadas para a otimização de padrões de recarga do combustível em um reator PWR
DOI:
https://doi.org/10.15392/bjrs.v7i3A.834Keywords:
Reator PWR, Redes neurais artificiais, Carga de combustívelAbstract
O gerenciamento de recarga de combustível em um reator de potência tem como principal foco o padrão de recarga no núcleo de modo a alcançar melhor rendimento no ciclo observando todos os parâmetros de segurança adotados. Neste artigo apresentamos a estratégia de um algoritmo baseado em redes neurais artificiais que poderia ser usado para otimizar a recarga de combustível num reator nuclear. A ideia é apresentar uma metodologia baseada em rede neural feedforward multicamadas baseada em neurônios multi-valorados, que poderá ser usada para desenvolver uma metodologia capaz de escolher as melhores combinações que satisfaçam o fator de pico de potência radial e maximizem o fator de multiplicação efetivo no início do ciclo, e também satisfaçam a relação de potência crítica mínima e taxa máxima de geração de calor no final do ciclo.
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