Investigation on different scenarios of two-phase flow measurement using Orifice and Coriolis flow meters: Experimental and modeling approaches

Abstract

In this study, various methods for multiphase flow metering were introduced. These techniques include measurement of gas-liquid average density by a Coriolis flow meter and determining the gas volume fraction by discharge coefficient of an orifice plate. Application of Orifice plate and Coriolis flow meters were investigated for gas-liquid flow metering. The principle of using these instruments as single-phase flow meters, for measurement of the two-phase flow was not focused in previous studies. In the second part, gas volume fraction was predicted by a soft sensor. Variation of Coriolis meter factor with gas volume fraction and Reynolds number was studied. Moreover, changes of pressure drop and discharge coefficient of Orifice with Reynolds number was investigated. On the other hand, 250 data sets were collected to develop a soft sensor using 2-layer and 3-layer neural networks optimized by genetic algorithm and Least Square Support Vector Machine. Increasing Reynolds number led to decrease in Coriolis meter factor. Among various computational intelligence methods, 3-layer neural network was the best, with mean square error and mean absolute percent error of 0.91% and 3%, respectively and computation time of 0.0001 s.