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• W2912831312 abstract "Abstract This work is related to numerical investigation and optimization of the attack angle of delta winglet type vortex generators in plain and wavy finned-tube heat exchangers. For this purpose, three-dimensional numerical simulation data and a multi-objective genetic algorithm with Artificial neural network are employed. The heat exchanger models considered in this study are three rows of tubes in staggered arrangement. The angle of attack (α) of delta winglets and Reynolds number varies from 15° to 75° and 500 to 1300, respectively. Results are illustrated by investigating the flow structures and local heat transfer coefficient. Results show that compared to plain fins, wavy fins enhance the heat transfer performance of the heat exchanger due to constant disruption of thermal boundary. Applying delta winglets on the plain and wavy fins further increased the heat transfer by energizing flow in the wake of tubes while friction factor is also increased. To achieve a maximum heat transfer enhancement and a minimum pressure drop, the optimal angle of attack for varying Reynolds numbers are calculated using the Pareto optimal strategy. For this purpose, CFD data, artificial neural network and a multi-objective genetic algorithm are combined. Results show that compared to the corresponding smooth fins, heat transfer per unit volume (Qv) and pumping power per unit volume (Pv) performances of delta winglets in wavy finned-tube heat exchanger has increased up to 12.5% and 7.41%, respectively. Similarly, for plain finned-tube heat exchangers, the maximum increase in Qv is 14.7% while Pv is increased by 6.93%." @default.
• W2912831312 created "2019-02-21" @default.
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• W2912831312 date "2019-03-01" @default.
• W2912831312 modified "2023-10-17" @default.
• W2912831312 title "Thermal-hydraulic performance and optimization of attack angle of delta winglets in plain and wavy finned-tube heat exchangers" @default.
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• W2912831312 doi "https://doi.org/10.1016/j.applthermaleng.2019.01.083" @default.
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