A CRITICAL REVIEW ON THE NUMERICAL METHODS OF TWO-PHASE FLOWS

Abstract

The two-phase flow processes play a significant role in the heat transfer processes in the chemical and power industry, including in nuclear power plants. This study is a critical review on the determination of the heat transfer characteristics of pure refrigerants flowing in vertical and horizontal tubes. The authors' previous publications on this issue, including the numerical analyses, are summarized here. The lengths of the vertical and horizontal test sections varied between 0.5 m and 4 m countercurrent flow double-tube heat exchangers with refrigerant flowing in the inner tube and cooling water flowing in the annulus. The measured data are compared to numerical predictions based on the solution of the artificial intelligence methods and CFD analyses for the condensation and evaporation processes in the smooth and enhanced tubes. The theoretical solutions are related to the design of passive containment cooling systems (PCCS) in simplified water boiling reactors (SWBR). A genetic algorithm (GA), various artificial neural network models (ANN) such as multilayer perceptron (MLP), radial basis networks (RBFN), generalized regression neural network (GRNN), and adaptive neuro-fuzzy inference system (ANFIS), and various optimization techniques such as unconstrained nonlinear minimization algorithm-Nelder-Mead method (NM), non-linear least squares error method (NLS), and Fluent CFD program are used in the numerical solution. It is shown that the heat transfer characteristics of laminar and turbulent condensing and evaporating film flows such as heat transfer coefficient and pressure drop can be predicted by means of numerical analyses reasonably well if there is a sufficient amount of reliable experimental data. Regression analysis gave convincing correlations, and the most suitable coefficients of the proposed correlations are depicted as compatible with the large number of experimental data by means of the computational numerical methods. Dependency of the output of the ANNs from various numbers of input values is also shown for condensing and evaporating flows.