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http://dx.doi.org/10.1016/j.net.2015.09.005

Precise Void Fraction Measurement in Two-phase Flows Independent of the Flow Regime Using Gamma-ray Attenuation  

Nazemi, E. (Young Researchers and Elite Club, Kermanshah Branch, Islamic Azad University)
Feghhi, S.A.H. (Radiation Application Department, Shahid Beheshti University)
Roshani, G.H. (Radiation Application Department, Shahid Beheshti University)
Gholipour Peyvandi, R. (Nuclear Science and Technology Research Institute)
Setayeshi, S. (Department of Energy Engineering and Physics, Amirkabir University of Technology)
Publication Information
Nuclear Engineering and Technology / v.48, no.1, 2016 , pp. 64-71 More about this Journal
Abstract
Void fraction is an important parameter in the oil industry. This quantity is necessary for volume rate measurement in multiphase flows. In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gas-liquid two-phase flows by using ${\gamma}-ray$ attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam ${\gamma}-ray$ attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used. Using fewer detectors is of advantage in industrial nuclear gauges because of reduced expense and improved simplicity. In this work, an artificial neural network is also implemented to predict the void fraction percentage independent of the flow regime. To do this, a multilayer perceptron neural network is used for developing the artificial neural network model in MATLAB. The required data for training and testing the network in three different regimes (annular, stratified, and bubbly) were obtained using an experimental setup. Using the technique developed in this work, void fraction percentages were predicted with mean relative error of <1.4%.
Keywords
Artificial Neural Network; Gamma; Independent Flow Regime; Multilayer Perceptron; Void Fraction;
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