Multiscale entropy and dynamic characteristics of two-phase flow patterns

Abstract

Multiscale entropy is a new method to analyze nonlinear time series on multiple temporal and spatial scales. Firstly，multiscale entropy characteristics of several typical nonlinear series were studied，and then based on this，the fluctuant conductance signals of 144 two-phase flow conditions were analyzed，which were collected by using array conductance sensors in upward vertical gas-liquid two-phase flow. The results indicated that the changing rate of sample entropy at small scales could be used to classify the three typical flow patterns （bubble flow，slug flow and churn flow），and the fluctuation of sample entropy of large scales reflected the dynamic characteristics of each flow pattern. The stochastic characteristic of bubble flow was shown as higher and oscillating sample entropy at large scales; the intermittence of gas slug and liquid slug of slug flow was represented as lower and stable sample entropy of large scales; the unstable and oscillating characteristics of churn flow behaved as the entropy between that of bubble flow and slug flow，and the entropy closed to that of bubble at larger scales. The multiscale entropy analysis of two-phase flow is helpful for understanding the dynamic characteristics of flow pattern transition，and the rate of multiscale entropy is a new indicator of flow pattern identification.