HEFAT2007 5 th International Conference on Heat Transfer, Fluid Mechanics, and Thermodynamics Sun City, South Africa Paper number: VE1 OPTICAL MEASUREMENT TECHNIQUE FOR PREDICTING TIME-FRACTIONS IN TWO-PHASE FLOW Van Rooyen E., Christians M., Liebenberg L., and Meyer J.P. ∗ ∗ author for correspondence Department of Mechanical and Aeronautical Engineering, University of Pretoria, Pretoria, 0002, South Africa E-mail: jmeyer@up.ac.za ABSTRACT The paper presents a signal analysis method used for condensing refrigerants and validated with air-water flow. The method was developed because of a lack of easily usable, accurate and objective flow pattern discrimination methods. Intermittent flow was investigated for improve- ments in heat transfer and pressure drop models based on a probabilistic time-fractional map. The frequency domain was identified as main candidate for discrimination of sub- regimes present in intermittent flow. The time-frequency sig- nal analysis method was applied to pressure measurements and other flow pattern detection devices. Development of an objective visual method for discrimination of flow patterns and determining probabilistic time-fractions are presented here with time-fractional results. INTRODUCTION Probabilistic time-fractional data have been presented by Ni˜ no et al. [1]. In their study of multi port flows in micro channels they evaluated video images of the flow for a set amount of time. Statistically, a sample population of images was taken for analysis at a range of mass fluxes and vapour qualities. The video analysis classified the flow in every tube according to the prevailing flow regime. Another method used for flow pattern research developed by Revellin et al. [2] involves lasers emitting light through a tube and a light sensitive diode to pick up the light inten- sity. The fast sampling rates of this method make it accurate for velocity calculations and can also be used for frequency analysis of the light intensity. The method is accurate and computationally cost effective. As proven by Hervieu et al. [3] the time-frequency do- main analysis of the signal from an inductive sensor can be used as an objective indicator of flow regime. Klein et al. [4] used time-frequency analysis in the intermittent regime to prove the existance of sub-regimes. In these cases an induc- tive sensor was used on air-water flows and in both cases the method proved successful in identifying flow regimes. Most recently work done at the UIUC involved the devel- opment of a time-fractional probabilistic flow map by Jassim [5]. This was done by capturing video images of the entire flow regime map and analysing it with software developed for flow pattern recognition. The flow pattern recognition method is advanced and it transforms each image with a filter after which the compositional flow patterns appear distinctly. The results of the work done by Jassim [5] was a heat trans- fer, pressure drop and void fraction prediction method based on time-fractions. Thus, several methods of signal analysis and measure- ment techniques have been defined in the recent past for in- vestigation of flow patterns (Keska et al. [6]). These methods bring a greater level of objectivity to flow pattern discrimi- nation. The basic premise of time-frequency representation is to divide the signal into smaller parts and to analyse each part separately in the frequency domain. This is done with time- frequency analysis by short time Fourier transforms STFT (or spectral analysis). A time-frequency distribution is a transform that maps a one-dimensional signal into a two- dimensional time-frequency map that describes how the fre- quency content changes with time. Another method of presenting time and frequency data is the wavelet transform. In wavelet transforms a single mother function is scaled in amplitude and length along the original signal to map a time-scale domain. The scales can then be converted to pseudo-frequencies (Matlab [7]). Knowing the flow regime means knowing what mechanisms are responsible for heat transfer and pressure drop. The Thome et al. [8] map defines the flow regime and transitions based on mass flux and vapour quality.