Predictions of flow transitions in a bubble column by chaotic time series analysis of pressure fluctuation signals

Abstract

In this study, predictions of flow transitions of a bubble column are carried out by chaotic time series analysis of pressure fluctuation signals. Pressure signals are measured for four different distributor plates with the superficial gas velocity varying from 0 to approximately 0.22 m/ s . Methodology of the chaotic time series analysis is presented, including procedures of the time-delayed phase-space reconstruction and calculation of the chaotic invariants. Four chaotic invariants, which include the largest Lyapunov exponent, metric entropy, correlation dimension and mutual information, of all pressure signals are computed. The critical gas velocities are determined by the sharp increase or decrease of the obtained chaotic invariants at the flow regime transitions. This simple criterion is consistent with the experimental observations. The obtained critical gas velocities by various chaotic measures for the four different distributor plates are quantitatively consistent and are in good agreement with the results by the gas holdup data.