Thermoelectric generation with impinging nano-jets

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dc.contributor.authorSelimefendigil F.
dc.contributor.authorOztop H.F.
dc.contributor.authorSheremet M.A.
dc.date.accessioned2024-07-22T08:06:28Z
dc.date.available2024-07-22T08:06:28Z
dc.date.issued2021
dc.description.abstractIn this study, thermoelectric generation with impinging hot and cold nanofluid jets is considered with computational fluid dynamics by using the finite element method. Highly conductive CNT particles are used in the water jets. Impacts of the Reynolds number of nanojet stream combinations (between (Re1, Re2 ) = (250, 250) to (1000, 1000)), horizontal distance of the jet inlet from the thermoelectric device (between (r1, r2 ) = (−0.25, −0.25) to (1.5, 1.5)), impinging jet inlet to target surfaces (between w2 and 4w2 ) and solid nanoparticle volume fraction (between 0 and 2%) on the interface temperature variations, thermoelectric output power generation and conversion efficiencies are numerically assessed. Higher powers and efficiencies are achieved when the jet stream Reynolds numbers and nanoparticle volume fractions are increased. Generated power and efficiency enhance-ments 81.5% and 23.8% when lowest and highest Reynolds number combinations are compared. However, the power enhancement with nanojets using highly conductive CNT particles is 14% at the highest solid volume fractions as compared to pure water jet. Impacts of horizontal location of jet inlets affect the power generation and conversion efficiency and 43% variation in the generated power is achieved. Lower values of distances between the jet inlets to the target surface resulted in higher power generation while an optimum value for the highest efficiency is obtained at location zh = 2.5ws . There is 18% enhancement in the conversion efficiency when distances at zh = ws and zh = 2.5ws are compared. Finally, polynomial type regression models are obtained for estimation of generated power and conversion efficiencies for water-jets and nanojets considering various values of jet Reynolds numbers. Accurate predictions are obtained with this modeling approach and it is helpful in assisting the high fidelity computational fluid dynamics simulations results. © 2021 by the authors. Li-censee MDPI, Basel, Switzerland.
dc.identifier.DOI-ID10.3390/en14020492
dc.identifier.issn19961073
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/13549
dc.language.isoEnglish
dc.publisherMDPI AG
dc.rightsAll Open Access; Gold Open Access; Green Open Access
dc.subjectComputational fluid dynamics
dc.subjectConversion efficiency
dc.subjectEfficiency
dc.subjectGas dynamics
dc.subjectJets
dc.subjectNanofluidics
dc.subjectNanoparticles
dc.subjectPhase interfaces
dc.subjectPolynomial regression
dc.subjectReynolds number
dc.subjectVolume fraction
dc.subjectWater distribution systems
dc.subjectAccurate prediction
dc.subjectComputational fluid dynamics simulations
dc.subjectInterface temperatures
dc.subjectNanoparticle volume fractions
dc.subjectSolid nanoparticles
dc.subjectSolid volume fraction
dc.subjectThermoelectric devices
dc.subjectThermoelectric generation
dc.subjectThermoelectric energy conversion
dc.titleThermoelectric generation with impinging nano-jets
dc.typeArticle

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