Multilayer Perceptron and General Regression Neural Networks for a study in three-phase flow

Autores

  • César Marques Salgado Instituto de Engenharia Nuclear
  • Ross Sophia de Freitas Dam Universidade Federal do Rio de Janeiro
  • William Luna Salgado Universidade Federal do Rio de Janeiro

Resumo

This report presents a methodology for volume fraction (VF) predictions in water-gas-oil multiphase systems based on gamma-ray densitometry and artificial neural networks (ANNs). The simulated geometry uses a dual-energy gamma-ray source and dual-modality (transmitted and scattered beams).

Linha principal do CV-28: lente quadripolar e distribuidor magnético

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Publicado

2021-08-12

Como Citar

Marques Salgado, C., Dam, R. S. de F. ., & Salgado, W. L. (2021). Multilayer Perceptron and General Regression Neural Networks for a study in three-phase flow. Instituto De Engenharia Nuclear: Progress Report, (4). Recuperado de https://revistas.ien.gov.br/index.php/ienprogressreport/article/view/430

Edição

n. 4 (2021): IEN - Progress Report 2018-2020 n.4

Seção

Application of Nuclear Techniques in Industry

Licença

Copyright (c) 2021 César Marques Salgado, Ross Sophia de Freitas Dam, William Luna Salgado

Creative Commons License

Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.