Volume fraction measurement and flow regime recognition in dynamic gas–liquid two phase flow using gamma ray radiation technique

Abstract

Gas–liquid two phase f low is probably the most important form of multiphase f lows and is found widely in industrial applications, particularly in the oil and petrochemical industry. In this study, in the first instance a gas–liquid two phase f low test loop with both vertical and horizontal test tube was designed and constructed. Different volume fractions and f low regimes were generated using this test loop. The measuring system consists of a ¹³⁷Cs single energy source which emits photons with 662 keV energy and two 1-inch NaI (Tl) scintillation detectors for recording the scattered and transmitted counts. The registered counts in the scattering detector were applied to the Multi-Layer Perceptron neural network as inputs. The output of the network was gas volume fraction which was predicted with the Mean Relative Error percentage of less than 0.9660%. Finally, the predicted volume fraction via neural network and the total count in transmission detector were chosen as inputs for another neural network with f low regime type as output. The f low regimes were identified with mean relative error percentage of less than 7.5%.