Engine oil enhanced performance with hybrid graphene-SWCNT nanomaterials over a Riga curvy surface
Hybrid graphene nanomaterials and single-wall carbon nanotubes (SWCNTs) saturated in a steady laminar viscous incompressible engine oil over a permeable and stretchable curvy Riga surface are focussed in the present study. The effects of nanoparticle shape factor, nanoparticle volume fraction and th...
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Veröffentlicht in: | Case studies in thermal engineering 2023-05, Vol.45, p.102902, Article 102902 |
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Sprache: | eng |
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Zusammenfassung: | Hybrid graphene nanomaterials and single-wall carbon nanotubes (SWCNTs) saturated in a steady laminar viscous incompressible engine oil over a permeable and stretchable curvy Riga surface are focussed in the present study. The effects of nanoparticle shape factor, nanoparticle volume fraction and thermal radiation towards the non-Newtonian flow are considered. The proposed partial differential governing equations are initially transformed into non-linear ODEs aided with similarity expressions. Subsequently, the numerical MATLAB's bvp4c package is utilized to solve the equations. Then, the parameters' influences on dimensionless velocity and temperature distributions, reduced skin friction coefficient and reduced Nusselt number are presented tabularly and graphically. Hybrid graphene-SWCNTs/engine oil has the least velocity, yet the greatest temperature profile when φ1= 0.04 and φ2= 0.02 are considered. It is also observed that the heat transfer performance enhances as the values of nanoparticle shape factor and thermal radiation increase. The lamina-shape nanomaterials are highly recommended to elevate the heat transfer performance of hybrid graphene-SWCNTs/engine oil for realistic applications. The present hybrid nanofluid flow with consideration of thermal radiation and nanoparticle shape factor allows enhancement in the heat and mass transfer for various engineering, technological and industrial operations especially in the design of submarines, thermal reactors and micro-coolers. |
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ISSN: | 2214-157X 2214-157X |
DOI: | 10.1016/j.csite.2023.102902 |