Shape effects of TEG mounted ventilated cavities with alumina-water nanofluids on the performance features by using artificial neural networks

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dc.contributor.authorSelimefendigil F.
dc.contributor.authorÖztop H.F.
dc.contributor.authorAfrand M.
dc.date.accessioned2024-07-22T08:04:14Z
dc.date.available2024-07-22T08:04:14Z
dc.date.issued2022
dc.description.abstractShape effects of TEG mounted vented cavities on the performance characteristic during alumina-water nanofluid convection are numerically assessed by using finite element method. Rectangular, triangular, L-shaped and Ushaped cavities are used. The interface temperatures of hot and cold side are varied by changing the cavity shape, opening ratio (OR) and Reynolds number (Re). The highest hot side temperature is obtained with L-shaped cavity followed by U, T and R-shaped cavities. When using T, L and U shaped cavities, the rise of the power are calculated as 38%, 78% and 76% at Re=1000 when compered to rectangular cavity. The power rises with higher OR while increment amounts are 83.9%, 63.5%, 42% and 87.8% for R, T, L and U cavities a Re=1000. When nanofluid is used at the highest loading, 11%, 10.3%, 9% and 8.5% rise of power are achieved for R, T, L and U shaped cavities while the amount is than 5% when different sizes of particles are considered. Neural network modeling with 10 neurons in the hidden layer provides accurate power outputs for all shaped cavities. © 2022
dc.identifier.DOI-ID10.1016/j.enganabound.2022.04.005
dc.identifier.issn09557997
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/12611
dc.language.isoEnglish
dc.publisherElsevier Ltd
dc.subjectAlumina
dc.subjectAluminum oxide
dc.subjectFinite element method
dc.subjectMultilayer neural networks
dc.subjectReynolds number
dc.subjectAlumina-water nanofluid
dc.subjectCavity shape
dc.subjectFEM, nanofluid, ANN
dc.subjectL-shaped
dc.subjectNanofluids
dc.subjectOpening ratio
dc.subjectPower
dc.subjectShape effect
dc.subjectThermoelectric conversion
dc.subjectU-shaped
dc.subjectNanofluidics
dc.titleShape effects of TEG mounted ventilated cavities with alumina-water nanofluids on the performance features by using artificial neural networks
dc.typeArticle

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