Density prediction using artificial neural networks and gamma ray
Palavras-chave:
gamma-rays densitometer, artificial neural network, MCNP-X codeResumo
This work presents a study for density prediction of petroleum and derivatives for products’ monitoring application. The approach is based on pulse height distributions pattern recognition by means of artificial neural network (ANN). Theoretical models for different materials have been developed using MCNP-X code, which was also used to provide training, test and validation data for the ANN.Referências
KHORSANDI, M.; FEGHHI, S. A. H. Design and construction of a prototype gamma-ray densitometer for petroleum products monitoring applications. Measurement, Amsterdam, v. 44, n. 9, p. 1512-1515, 2011.
SALGADO, C. M. et al. Salinity independent volume fraction prediction in annular and stratified (water-gas-oil) multiphase flows using artificial neural networks. Progress in Nuclear Energy, Amsterdam, v. 76, p. 17-23, set. 2014.
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Publicado
2021-07-08
Como Citar
Salgado, C. M. (2021). Density prediction using artificial neural networks and gamma ray. Instituto De Engenharia Nuclear: Progress Report, (3), 16. Recuperado de https://revistas.ien.gov.br/index.php/ienprogressreport/article/view/314
Edição
Seção
Application of Nuclear Techniques in Health and Environment
Licença
Copyright (c) 2018 César Marques Salgado
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
