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The main purpose of this book is introducing application of artificial neural network in gamma radiation-based multiphase flow meters. Artificial neural network is an useful tool for predicting volume fraction and identification of flow pattern in two-phase and three-phase flows.This book is divided into five main chapters. In chapter one, concept and background, history, performance, learning algorithms, models, and application of artificial neural network is introduced. Chapter two is dedicated to multiphase flows. This chapter comprises of history, key definitions, and flow patterns of multiphase flows. In chapter three, different methods of measuring multiphase flow and various performance principles of multiphase flow meters are described. In chapter four, emission of gamma-ray from radioactive sources, different mechanisms of interaction of photon with matter, and using gamma-ray for measuring volume fraction in homogenous flow regime are described. In the last chapter, some examples for applying the artificial neural network in radiation-based multiphase flow meters for measuring volume fraction in non-homogenous flow regime and identifying flow regime, are presented.
About the author
Ehsan Nazemi was born in Isfahan, Iran, on February 7, 1990. He received the BS degree in Nuclear Physics in 2012, Yazd University. He received the MEng degree in Nuclear Engineering in 2014, Shahid Beheshti University. He is currently working toward the PhD degree in Nuclear Engineering, Nuclear Science and Technology Research Institute.
