Neural Networks in Two���phase Flow

Two–phase flows are commonly found in many industrial processes. Numerous theoretical and experimental studies have been carried out and reported in literature for modeling of two–phase flow. However because of the inherent complexity of two-phase flow it is still a challenge to make accurate predictions for the different parameters of two–phase flow such as flow pattern in–situ phase fraction pressure drop and heat transfer coefficient. Artificial neural network (ANN) technique has been proposed as a powerful and computational tool for modeling and solving complex problems that cannot be described with simple mathematical models. This book consists of three chapters. The first chapter presents a review of gas–liquid and liquid–liquid two–phase flows in horizontal vertical and inclined pipes. In the second chapter an overview about the most commonly used network architectures in the field of two–phase flow is provided. Finally in the third chapter some examples of artificial neural network applications in the field of two–phase flow are presented.