Characterization of two-phase flows using fractal analysis of local temperature fluctuations

Abstract

Abstract--This work deals with the characterization of two-phase flows based on fractal techniques in order to develop objective flow regime indicators. Fractal analysis has been used previously for studying turbulent flows and it is a natural way of describing highly irregular fluctuations in two-phase flows. The fractal dimension of measured time series have been evaluated by Higuchi's method. It is shown that the error of the linear fit of the fractal dimension is a sensitive indicator of the changes in the flow regime, while the fractal dimension value itself is less suitable for flow regime identification. The developed method has been applied to the evaluation of two-phase flow experiments at the SIDAS boiling loop at Delft

Gas-liquid two phase flow pattern evolution characteristics based on detrended fluctuation analysis

“…For time series X i , i=l, 2,…, N, the average is X . Firstly, computing the integrated and detrended time series y(k), k=1, …,N, (4) y(k) is divided into N/n sub sequences with each interval length n. The local trend y n (k) comes from each interval with least square method, and the rootmean-square fluctuation of this series is calculated by:…”

“…They also studied the fractal dimension distribution of the microelectrode time series when the liquid flow rate was fixed and the gas flow rate was changing. Kozma et al calculated the fractal dimension by using local temperature fluctuating time series in two phase flow, and observed that the fractal dimension that changes with different flow pattern could be used to distinguish the flow patterns [4]. Cai et al calculated the fractal dimension using the correlation dimension to distinguish the flow patterns in vertical rectangle pipe, and indicated that the gas-liquid flow in vertical rectangle pipe possess chaotic features [5].…”

Nonlinear forecast of heat transfer coefficient signal in fluidized bed evaporator

“…Recently, nonlinear points have been introduced to vaporliquid (V-L) pool boiling system (Sadasivan et al, 1995;Chai and Shoji, 2001;Shoji and Takagi, 2001;Chai and Shoji, 2002a,b;Mosdorf and Shoji, 2004;Shoji, 2004) and V-L flow boiling system (Rizwan-unddin and Dorning, 1988;Clausse and Lahey, 1991;Delmastro and Clausse, 1994;Kozma et al, 1996;Narayanan et al, 1997;Lee and Pan, 1999;Cammarata et al, 2000;Zboray et al, 2004;Mosdorf et al, 2005) to analyze the parameter oscillation and disclose the boiling mechanisms. The nonlinear analysis as well as nonlinear prediction, much like CFD simulation software, is a good analysis tool to increase the mechanism understanding and improve modeling or predicting of the multiphase flow.…”

Characterization of flow regimes in fluidized beds by information entropy analysis of pressure fluctuations

“…Several measurement methods were developed to characterize and classify flow regimes, such as voidage fluctuations, temperature fluctuations, X‐ray (or γ‐ray) tomography, electrical capacitance tomography (ECT), and vibration and pressure fluctuations . Among these, the pressure fluctuation measurement has been most commonly used because the pressure fluctuation signals contain rich information detailing the gas‐solid interaction.…”