Multi-objective optimization of geometrical parameters of corrugated-undulated heat transfer surfaces

To achieve a maximum heat transfer capability and a minimum pumping power for corrugated undulated (CU) heat transfer surfaces, a multi-objectives genetic algorithm was used to obtain the optimal values of the pitch and height of undulated plate (U-plate) and the height of the corrugated plate (C-plate) by using the Pareto optimal strategy. For this purpose, computational fluid dynamics (CFD) simulation, support vector machine (SVM) and the fast non-dominated sorting genetic algorithm were combined together and used for the optimization process. Three dimensional numerical simulations were performed to investigate the effect of geometrical parameters on the thermos-hydraulic performance of CU heat transfer surface. The maximum deviation for the Nusselt number and friction factor between the simulation and the published data were 8.81% and 13.1% respectively when the Reynolds number ranged from 1500 to 10,000. The flow and temperature profile in the CU passage were analyzed. Intensive secondary flows occurred in the C-plate channel and the U-plate channel due to the drag effect between the main flows in the two channels. And the effects of Reynolds number and structure parameters were studied. The change of U-plate height rather than that of U-plate pitch would have a dominant effect on the disturbance influence of U-plate. Besides, two SVM models were trained by the CFD results to predict the Nusselt number and friction factor of flow in CU passages with different geometrical and operational parameters. The comparison between the SVM predictions and the CFD results showed that the SVM models could predict the numerical data with a good accuracy. In addition, two evaluation criteria were proposed from perspectives of the manufacturers and the users, respectively. Finally, a set of optimized solutions were obtained. The optimal values of pumping power ratio and heat transfer area ratio between different CU passages and the standard one were in the range of 0.8-3.1 and 0.5-1.2, respectively. The manufacturers and the users can select the best design points according to their considerations. (C) 2016 Elsevier Ltd. All rights reserved.