Time Irreversibility from Time Series for Analyzing Oil-in-Water Flow Transition

Abstract EN

We first experimentally collect conductance fluctuation signals of oil-in-water two-phase flow in a vertical pipe.

Then we detect the flow pattern asymmetry character from the collected signals with multidimensional time irreversibility and multiscale time irreversibility index.

Moreover, we propose a novel criterion, that is, AMSI (average of multiscale time irreversibility), to quantitatively investigate the oil-in-water two-phase flow pattern dynamics.

The results show that AMSI is sensitive to the flow pattern evolution that can be used to predict the flow pattern transition and bubble coalescence.