Flow regime identification and volume fraction prediction in multiphase flows by means of gamma-ray attenuation and artificial neural networks

By C. Salgado, C. Pereira, R. Schirru, L. E. Brandão. 2010

174 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Biomedical Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/f05188e645a20e225caf700ffad452f91e66eeec

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1. S. Setayeshi
2. S. Feghhi

Citations in the corpus

• Flow regime identification and void fraction prediction in two-phase flows based on gamma ray attenuation (2015, methodology): “Many researchers have used the different types of ANNs in gamma densitometry [3–13] in order to classification, clustering and prediction.”