Two-Phase Flow Regime Identification Based on Cross-Entropy and Information Extension Methods for Computerized Tomography

Computerized tomography (CT) is applied to multiphase flow measurements in recent years. A new approach based on the cross-entropy and information extension methods is proposed for two-phase flow regime identification in this paper. Two minimum cross-entropy methods, namely, maximum a posteriori and simultaneous multiplicative algebraic reconstruction technique (ART), are presented. This paper discusses the selection of parameters and prior smoothing operator. An information extension method is proposed based on the geometrical model of the CT system to reduce ill condition and modify the edge shape of reconstruction. Both simulation and experiments were carried out for typical flow regimes, indicating that the proposed method can reduce the computation time and improve the resolution of the reconstructed images compared with the ART method.