Analysis and optimization of the curved trapezoidal winglet geometry in a high-efficiency compact heat exchanger

Abstract

The present work is undertaken to optimize the geometry of the curved trapezoidal winglet mounted over each cooling tube to enhance the overall performance of the heat exchanger. Before conducting the optimization study, the most critical geometric entities have been identified, and this has helped in significantly reducing the computational overheads. It has been found that the three most critical design parameters are the arc radius (R), the angle subtended (θ) and the winglet's leading-edge height (h1), and the same are chosen for optimization. To plan the experiment, we make use of the Latin hypercube sampling (LHS) scheme. The system responses viz. the Colburn factor (j) and the friction factor (f) ‒ for different combinations of the independent variables ‒ are computed using the numerical simulations together with the conjugate heat transfer approach. To get the best outcome from computations, both fluid and solid domains have been discretized using hexahedra. We make use of the Reynolds-averaged Navier-Stokes (RANS) approach ‒ with SST k–ω (a 2-equation) turbulence model as a closure to RANS ‒ for evaluating the dependent variables. The artificial neural network (ANN) is trained using the data from the DoE table to build the metamodel necessary for conducting the multiobjective optimization. The genetic algorithm (GA) is employed to generate the optimized data sets. The study reveals that the optimized HE variants outperform the baseline model not only at the on-design condition but also at the off-design conditions. The resulting Pareto front points reveal very interesting results, and these data would facilitate the designers to make choices over a wide range of the VG geometry of the heat exchanger.