Prediction of the Optimized Frictional Pressure Drop in a Two-phase Flow Small-channel with Genetic Algorithm

Research in energy and material efficiencies has never been more important due to the current global policies towards a sustainable future. Compact heat exchangers involving the complexities of two-phase flows, with their decreasing channel size and low environmentally friendly coolant mass requirement, necessitate intensive investigations into the significant wall friction which must be balanced by the heat transfer capability. This paper reports the initial study into the feasibility of using the fast growing optimization tool of genetic algorithm in predicting the minimized frictional pressure drop across a small channel under optimized vapor quality and mass flow rate. Both the single-objective and double-objective optimizations have been completed. The former involves minimizing the frictional pressure drop and the latter involves minimizing the frictional pressure drop as well as the Martinelli-Lockhart parameter. The single objective optimization and double objective optimization scheme applied show promise with similar trends observed as those that have been previously reported.