Density prediction using artificial neural networks and gamma ray
Keywords:
gamma-rays densitometer, artificial neural network, MCNP-X codeAbstract
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.References
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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Published
2021-07-08
How to Cite
Salgado, C. M. (2021). Density prediction using artificial neural networks and gamma ray. Instituto De Engenharia Nuclear: Progress Report, (3), 16. Retrieved from https://revistas.ien.gov.br/index.php/ienprogressreport/article/view/314
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Section
Application of Nuclear Techniques in Health and Environment
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Copyright (c) 2018 César Marques Salgado
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
