The fluid properties strongly affect the performance of radiation-based multiphase flow meter. By changing the
fluid properties (especially density), recalibration is necessary. In this study, a method was presented to
eliminate the dependency of multiphase flow meter on liquid phase density in stratified two phase horizontal
flows. At the first step the position of the scattering detector was optimized in order to achieve highest sensitivity.
Several experiments in optimized position were done. Counts under the full energy peak of transmission
detector and total counts of scattering detector were applied to the Radial Basis Function neural
network and the void fraction percentage was considered as the neural network output. Using this method, the
void fraction was predicted independent of the liquid phase density change in stratified regime of gas–liquid
two-phase flowswithmeanrelativeerrorpercentagelessthan1.2%.
کلید واژگان :
Radial Basis Function Radiation-based MPFM Detector Void fraction Prediction
