Aggregated studies of graphene nanoparticles is important for the effective utilization of their striking thermophysical properties and extensive industrial applications. This investigation is one such computational study to explore the flow of graphene oxide nanofluids with temperature dependant viscosity between two concentric cylinders. Buongiorno model is used to develop the flow of graphene nanofluids including the impacts of Soret and Dufour effects and the effects of nanoparticle characteristics such as thermophoresis and Brownian motion. The modelled equations are transformed and are numerically solved using linearization method together with Chebyshev’s spectral collocation method under convective conditions. The impacts of embedded parameters on temperature, concentration and skin friction profiles of the chosen nanofluid and their consequent impacts on the predominant cause for the generated entropy are studied. From the tabulated values of Nusselt number and Sherwood number, it is observed that convective heat transfer can be enhanced by thermal Biot number whereas Soret number enhances diffusive mass transfer and variable viscosity parameter preferably reduces the skin friction. A comparison table is presented and it shows that the values obtained from the present method are in good agreement with existing literature. Also, the obtained results are depicted and interpreted in detail. Furthermore, entropy generation is analysed and its irreversibilty is calculated.
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