Flow regime identification and void fraction prediction in two-phase flows based on gamma ray attenuation-Reference-Cited by-同舟云学术

Flow regime identification and void fraction prediction in two-phase flows based on gamma ray attenuation

Published:2015-02 Issue: Volume:62 Page:25-32
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Roshani G.H.,Nazemi E.,Feghhi S.A.H.,Setayeshi S.

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference19 articles.

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3. Determination of void fraction and flow regime using a neural network trained on simulated data based on gamma-ray densitometry;Abro;Meas. Sci. Technol.,1999

4. C.G. Jing, Q. Bai, Flow regime identification of gas/liquid two-phase flow in vertical pipe using RBF Neural Networks. in: Chinese Control and Decision Conference (CCDC), 2009.

5. Flow regime identification and volume fraction prediction in multiphase flows by means of gamma-ray attenuation and artificial neural networks;Salgado;Prog. Nucl. Energy,2010

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