Flow regime identification using pressure fluctuation signals in an aerated vessel stirred

A novel method was proposed to determine the flow regime based on the bottom pressure fluctuations of the stirred tank. Statistical, Hurst, Shannon entropy and chaos analysis methods were used to analyze the pressure time series in an aerated stirred tank with a Rushton impeller, and the relationship between the characteristic parameters and the flow regimes was established. The results showed that the bubble motion in the loading regime was obviously stronger than that in the flooding regime, and the homogeneity of the system was rapidly improved. Compared with the first two stages, the chaotic extent of the complete dispersion regime was slightly weaker, and the benefit generated by continuously increasing the speed was limited at this time. In addition, considering the sensitivity of pressure pulsations to the gas-liquid dispersion state, the transition points of the three flow regimes were successfully identified by the standard deviation and the largest Lyapunov exponent. The data were well consistent with the measurements from the visual method and power method, with a maximum deviation of 16%. This demonstrated that it was a reliable non-invasive method for flow regime identification in gas-liquid stirred tanks.