Investigation on intermittent flow characteristics in horizontal pipe by visualization measurement method

Abstract

Accurate measurement and prediction of the intermittent flow characteristics in horizontal pipes is important for constructing multiphase flow models and ensuring pipe flow safety. In this paper, a quantitative image post-processing technique for intermittent flow characteristics based on gray histogram image similarity is proposed, which can realize the measurement of slug frequency. In addition, the technique also has the ability to classify a large number of images, and can quickly find the elongated bubble head, liquid film area and liquid slug area of intermittent flow. On the basis of this technique, combined with image post-processing methods such as gas–liquid interface feature analysis, a set of intermittent flow image processing technique with perfect route is formed. Based on this post-processing technique, the similarity image oscillation trajectories of plug flow and slug flow are obtained. There are differences in the similarity image oscillation trajectories of the two intermittent sub-flow patterns, and the similarity image of the plug flow has an obvious platform period and trailing rising line, which can be used as a basis for the classification of the two intermittent sub-flow patterns. A correlation for predicting the slug frequency of intermittent sub-flow patterns is developed. The accuracy of this slug frequency prediction correlation can be improved by about 10 % compared to not dividing the sub-flow patterns. When the mixture Froude number Fr_m is less than 5.0, the radial position of the elongated bubble head decreases linearly as the Fr_m increases. When the Fr_m is greater than 5.0, the elongated bubble head oscillates near the middle of the pipe. Prediction correlations for the radial position of the elongated bubble head and the slug velocity are established separately, and the maximum error is ± 10 %. The modified mixed Froude number is proposed, and based on this, a new prediction model for the transition from plug flow to slug flow is established.