Determination of Void Fraction in Microchannel Flow Boiling Using Computer Vision

Extended Abstract The void fraction is one of the most critical parameters for characterizing two-phase flow boiling in microscale channels. Several important thermal-hydraulic parameters such as two-phase viscosity and two-phase density can be derived from the knowledge of the void fraction. In addition, it is used in numerous models to predict heat transfer, pressure drop and flow patterns in microchannels. The most commonly used definition of void fraction in this context is the cross-sectional void fraction, which is the ratio of the cross-sectional area occupied by the vapor phase to the total cross-sectional area at a given location in the channel [1]. This void fraction is often determined roughly by electrical impedance measurements using the Maxwell-Garnett equations, which relate impedance and void fraction [2], or with high precision by optical studies at specific locations in the microchannel. However, the lack of suitable image processing makes the optical determination of the void fraction very time-consuming, since it must be calculated manually for each frame. In this study, computer vision was applied to realize an automatic and accurate calculation of cross-sectional void fractions perpendicular to the fluid flow direction at different locations in microchannels. The void fractions of each channel location could be linked together to provide a map of the average void fraction of the entire channel. Therefore, two-phase flow boiling experiments were performed with DI water in rectangular stainless-steel microchannels with hydraulic diameters of 430 and 750 µm and lengths of 65 mm. The mass flow rate ranged from 1.5 to 5 g/min and the heat load applied to the