Optimization of the Bubble Departure and Liftoff Boiling Model Using Taguchi Method

Abstract

The bubble departure and liftoff boiling model has been studied using design of experiments technique and three-dimensional computational fluid dynamics (CFD) simulations. Wall heat fluxes were calculated to determine the influence of wall temperature on the flow boiling curve, which were compared with those generated from the experimental data and the numerical model based on the integration of flow induced and subcooling suppression factors. A Taguchi based design of experiments technique was used to analyze the statistical significance of three different parameters namely, the bulk flow velocity, the operating pressure and the wall heat flux. A regression equation was constructed to represent the wall temperature, and this was tested for accuracy with the help of 64 randomly generated test cases from the experiments and the numerical model. The results showed that the numerical model had a mean absolute error of 3.35% and regression coefficient of 0.89, with the experimental data. The boiling curves from CFD fitted well with the numerical model results in comparison to the experimental data. The regression equation obtained from the Taguchi technique made accurate predictions of the wall temperature with an average error of 2.57% and 0.15% compared to the experimental and the numerical model results, respectively.