Abstract
Electrical impedance of a two-phase mixture is a function of void fraction and phase distribution. The difference in the specific electrical conductance and permittivity of the two phases is exploited to measure electrical impedance for obtaining void fraction and flow regime characteristics. An electrical impedance meter is constructed for the measurement of void fraction in microchannel two-phase flow. The experiments are conducted in air–water two-phase flow under adiabatic conditions. A transparent acrylic test section of hydraulic diameter 780μm is used in the experimental investigation. The impedance void meter is calibrated against the void fraction calculated using analysis of images obtained with a high-speed camera. Based on these measurements, a methodology utilizing the statistical characteristics of the void fraction signals is employed for identification of microchannel flow regimes. A self-organizing neural network is used for classification of the flow regimes.
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