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• W4313254691 abstract "A droplet impingement on solid surfaces plays a critical role in various spray and heat transfer applications. The main objective of this study is to investigate how to enhance the cooling performance of the single droplet impingement process on the heated hole-patterned surfaces by finding desired conditions using optimization techniques. The cooling effectiveness and total contact area at the maximum droplet spread were chosen for objective functions to be maximized. To estimate the optimal values of the unknown variables efficiently, the improved Gaussian-behaved particle swarm optimization (GQPSO) algorithm with a modified local attractor using Gaussian distributed random numbers was newly proposed and applied to the single droplet impingement problem. To verify the improved search performance of the proposed GQPSO approach, the optimization results were compared with the standard particle swarm optimization (PSO) and original GQPSO methods with the same conditions. By comparing the estimated maximum values of given objective functions, calculation times and numbers of penalty particles, we verified that the proposed GQPSO approach could search for more optimal solutions quickly and efficiently due to its improved local fine-tuning capability with the modified local attractor." @default.
• W4313254691 created "2023-01-06" @default.
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• W4313254691 date "2023-01-01" @default.
• W4313254691 modified "2023-10-18" @default.
• W4313254691 title "Cooling performance enhancement study of single droplet impingement on heated hole-patterned surfaces using improved GQPSO algorithm" @default.
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• W4313254691 doi "https://doi.org/10.1016/j.csite.2022.102679" @default.
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