Gönül, A.Okbaz, A.Kayacı, NurullahSelim Dalkılıç, A.2022-05-112022-05-1120221359-4311https://doi.org/10.1016/j.applthermaleng.2021.117738https://hdl.handle.net/20.500.11776/6629In this study, delta winglet-type vortex generators, widely used in conventional macro channels and proven to be effective, are used in microchannels to increase their heat transfer capacities. The effects of vortex generators on heat transfer and pressure loss characteristics are studied numerically for different angles of attack, vortex generator arrangement type, the transverse and longitudinal distance between vortex generators, vortex generator length and height, and different Reynolds numbers. The thermal and hydraulic characteristics are presented as the Nusselt number, the friction factor, and the performance evaluation criteria number (PEC) that takes into account the heat transfer enhancement and the corresponding increase in pressure loss. The variation of Nu/Nu0, f/f0, and PEC are found to be in the range of 1.03–1.87, 1.04–1.8, and 0.92–1.62, respectively. A multi-objective optimization study are performed with the response surface methodology analysis to see how different parameters affect heat transfer and pressure loss and to determine the most optimum design. Besides, local sensitivity analysis study is carried out through the RSM, and water inlet velocity for heat transfer enhancement is found to be the most effective parameter. Among the geometric parameters, vortex generator height is determined as the most effective factor. Finally, practical Nusselt number and friction factor correlations taking many parameters into account are proposed to be able to compare the results of other researchers, and for engineers designing microchannel cooling systems. © 2021 Elsevier Ltden10.1016/j.applthermaleng.2021.117738info:eu-repo/semantics/closedAccessGenetic algorithmHeat transfer enhancementMicrochannelMulti-objective optimizationVortex generatorAngle of attackCooling systemsDelta wing aircraftFrictionGenetic algorithmsHeat transfer coefficientsHeat transfer performanceMultiobjective optimizationNanofluidicsNusselt numberReynolds numberSensitivity analysisVortex flowVorticityDelta wingletsFlow optimizationHeat Transfer enhancementHeat transfer lossLoss characteristicsMulti-objectives optimizationPerformance evaluation criteriaPressure lossTransfer capacitiesVortex generatorsMicrochannelsArticle2012-s2.0-85118854784Q1