Multi-objective heat transfer optimization of 2D helical micro-fins using NSGA-II

A numerical simulation of helical micro-fins is implemented in ANSYS Fluent 15. The model is scripted to automatically set up and execute given three input parameters: fin height, helix angle, and number of starts. The simulation results reasonably predict experimental pressure drop and heat transfer for multiple micro-fin geometries. A multi-objective parameter optimization is implemented based on the NSGA-II algorithm to estimate the optimal trade-off (Pareto front) between Nusselt number and friction factor of a micro-fin tube for 0.0006 < e/D < 0.045, 10 < N-s < 70, at Reynolds number of 49,013. The resulting Pareto front is analyzed and compared with several experimental data points. From the optimal results, a distinct difference in flow characteristics was identified between geometries above and below a helix angle of approximately 45 degrees. How the Pareto front can be used to choose micro-fin geometries for different performance evaluation criterion scenarios is demonstrated. Optimal results from various existing correlations are also compared to the optimization results. (C) 2018 The Authors. Published by Elsevier Ltd.