Abstract
Flow induced vibration due to internal gas-liquid two-phase flow is a significant issue for various engineering applications. Gas-liquid two-phase flow is known for its unsteady and oscillatory behavior, and fluctuating force is generated when undergoing fluid-structure interaction. In order to properly assess the fluctuating force behavior of two-phase flow, identification of the flow regime is particular importance for the safety of the operation. Aim of the present study is to identify two-phase flow regime from fluctuating force signal. In this study, a new methodology of two-phase flow regime identification is presented by patterning the fluctuating force signal obtained from the experiment using neural network.
