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Multi-Objective Optimization of Geometrical Parameters of Corrugated-Undulated Heat Transfer Surfaces Using CFD, Artificial Neural Networks and Genetic Algorithms

[+] Author Affiliations
Limin Wang, Chenglong Ji, Lei Deng, Defu Che

Xi’an Jiaotong University, Xi’an, China

Xun Chen, Yiping Chen

Hunan Electric Power Corporation Research Institute, Changsha, China

Paper No. POWER2016-59489, pp. V001T11A010; 11 pages
  • ASME 2016 Power Conference collocated with the ASME 2016 10th International Conference on Energy Sustainability and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology
  • ASME 2016 Power Conference
  • Charlotte, North Carolina, USA, June 26–30, 2016
  • Conference Sponsors: Power Division, Advanced Energy Systems Division, Solar Energy Division, Nuclear Engineering Division
  • ISBN: 978-0-7918-5021-3
  • Copyright © 2016 by ASME


A three dimensional numerical simulation was performed to study the effect of the pitch (PU) and height (HU) of undulated plate (U-plate) and the height (Hc) of the corrugated plate (C-plate) on the heat transfer and fluid flow characteristics in the corrugated-undulated (CU) heat transfer surfaces. The mass, momentum and energy equations were solved using finite volume method by considering the steady state, turbulent and incompressible fluid flow. The numerical results showed a good agreement with the experimental data in reference. The average Nusselt number and friction factor were investigated in CU heat transfer surfaces with different geometrical parameters. To achieve a maximum heat transfer enhancement and a minimum pressure drop, the optimal values of these parameters were calculated using the Pareto optimal strategy. For this purpose, computational fluid dynamics analysis, multi-objective genetic algorithm and artificial neural networks were combined together and used in the optimization process. Finally, the optimal values of these geometrical parameters were presented.

Copyright © 2016 by ASME



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