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• W2320950607 abstract "Abstract A gamma-ray transmission technique is present to measure the void fraction and identify the flow regime of a two-phase flow using two detectors which were optimized in terms of detector orientation. Using Monte-Carlo simulation, experimental results were utilized for training an artificial neural network. Radial Basis Function was used to classify flow regimes (annular, stratified and bubbly) and predict the value of void fraction. All of the training and testing data sets were determined correctly and the mean relative error percentage of predicted void fraction was less than 1.5%. Although the method was applied to a certain pipe size in a static flow configuration, it provides a framework for application to other configurations." @default.
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• W2320950607 date "2016-05-01" @default.
• W2320950607 modified "2023-09-26" @default.
• W2320950607 title "Optimization of a method for identifying the flow regime and measuring void fraction in a broad beam gamma-ray attenuation technique" @default.
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• W2320950607 doi "https://doi.org/10.1016/j.ijhydene.2015.12.098" @default.
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