Use este identificador para citar o ir al link de este elemento: http://hdl.handle.net/1843/56851
Tipo: Artigo de Evento
Título: Artificial neural networks for spatial distribution of fuel assemblies in reload of PWR reactors
Autor(es): Edyene Cely Oliveira
Victor Faria de Castro
Carlos Eduardo Velasquez Cabrera
Claubia Pereira
Resumen: An artificial neural network methodology is being developed in order to find an optimum spatial distribution of the fuel assemblies in a nuclear reactor core during reloading. The main bounding parameter of the modeling was the neutron multiplication factor, keff. The characteristics of the network are defined by the nuclear parame ters: cycle, burnup, enrichment, fuel type, and average power peak of each element. As for the artificial neural network, the ANN Feedforward Multi_Layer_Perceptron with various layers and neurons were constructed. Three algorithms were used and tested: LM (Levenberg-Marquardt), SCG (Scaled Conjugate Gradient) and BayR (Bayesian Regularization). The artificial neural network has implemented using MATLAB 2015a version. As preliminary results, the spatial distribution of the fuel assemblies in the core using a neural network was slightly better than the standard core.
Asunto: Inteligência computacional
Reatores Nucleares
Idioma: por
País: Brasil
Editor: Universidade Federal de Minas Gerais
Sigla da Institución: UFMG
Departamento: ENG - DEPARTAMENTO DE ENGENHARIA NUCLEAR
Tipo de acceso: Acesso Aberto
Identificador DOI: https://doi.org/10.15392/bjrs.v7i2B.770
URI: http://hdl.handle.net/1843/56851
Fecha del documento: 2017
metadata.dc.url.externa: https://www.bjrs.org.br/revista/index.php/REVISTA/article/view/770
metadata.dc.relation.ispartof: International Nuclear Atlantic Conference
Aparece en las colecciones:Artigo de Evento

archivos asociados a este elemento:
archivo Descripción TamañoFormato 
Artificial neural networks for spatial distribution of fuel assemblies in reload of PWR reactors.pdf426.07 kBAdobe PDFVisualizar/Abrir


Los elementos en el repositorio están protegidos por copyright, con todos los derechos reservados, salvo cuando es indicado lo contrario.