June 19, 2024
Gholam Hossein Roshani

Gholam Hossein Roshani

Academic rank: Associate professor
Education: Ph.D in Nuclear Engineering
Faculty: Faculty ofٍٍ Electrical Engineering


Volume fraction determination of the annular three-phase flow of gas-oil-water using adaptive neuro-fuzzy inference system
Type Article
Annular;Adaptive neuro-fuzzy inference system; Three-phase
Researchers Gholam Hossein Roshani، A. Karami، Ehsan Nazemi، Farzin shama


The use of adaptive neuro-fuzzy inference system (ANFIS) has been reported for predicting the volume fractions in a gas–oil–water multiphase system. In fact, the volume fractions in the annular three-phase flow are measured based on a dual energy metering system consisting of 152Eu and 137Cs and one NaI detector using ANFIS. Since the summation of volume fractions is constant, therefore ANFIS must predict only two volume fractions. In this study, three ANFIS networks are applied. The first is utilized to predict the gas and water volume fractions. The next one is applied to predict the gas and oil, and the last one is used to predict the water and oil volume fractions. In the next step, ANFIS networks must be trained based on numerically obtained data from MCNP-X code. Then, the average testing errors of these three networks are computed and compared. The network with the least error has been selected as the best predictor model.