Identification of two-phase water–air flow patterns in a vertical pipe using fuzzy logic and genetic algorithm

Abstract An automatic and intelligent system to recognize the two-phase water–air flow regime in a vertical tube based on fuzzy logic and genetic algorithm is proposed. Two approaches, volume of fluid (VOF) and Eulerian model, were used for the numerical simulation of gas–liquid two-phase flow. Four different turbulence models, i.e., k–e RNG, k–e standard, Reynolds stress and k–e realizable, were employed. Image processing procedure was implemented to obtain the flow pattern. It was found that the k–e RNG gives best results for turbulence modeling and the fuzzy logic code predicts the flow pattern well.

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