Neural network based objective flow regime identification in air‐water two phase flow

Abstract

Abstract The Kohonen self‐organising neural network was applied to identify flow regimes in horizontal air‐water flow. The neural network was trained with stochastic features derived from turbulent absolute pressure signals obtained across a range of flow regimes. The feature map succeeded in classifying samples into distinctive flow regime classes consistent with the visual flow regime observation.