Entropy-optimized radiating water/FCNTs nanofluid boundary-layer flow with convective condition
Energy Physics Laboratory, Physics Department, Exact Science Faculty, University of Constantine 1, 25000, Constantine, Algeria
2 Department of Information Technology, Fanshawe College, London, ON, Canada
3 Faculty of Military Science, Stellenbosch University, Private Bag X2, Saldanha, South Africa
Accepted: 13 June 2020
Published online: 6 August 2020
The inherent irreversibility in boundary-layer flow of a radiating water/functionalized carbon nanotubes nanofluid over a convectively heated moving wedge and a horizontal/vertical plates is examined. The water-based nanofluid contains two types of carbon nanotubes, namely SWCNTs and MWCNTs. Using a suitable similarity transformation, the model partial differential equations are reduced to ordinary differential equations along with the corresponding boundary conditions. Solutions are obtained for the nanofluid velocity and temperature profiles analytically via optimal homotopy asymptotic method and numerically via shooting method with Runge–Kutta–Fehlberg integration scheme. Entropy generation analysis is conducted based on second law of thermodynamic, and the Bejan number is determined. Results are presented in graphical and tabular forms in order to scrutinize the effects of various geometrical, dynamical and thermophysical parameters on velocity, temperature, skin friction, Nusselt number, entropy generation rate and Bejan number. Generally, it is found that the entropy production can be minimized by reducing the convection through boundaries, moving the obstacle at the same velocity and direction as the flow (λoptimal = 1) and controlling the penetration of viscous dissipation, while increasing nanoparticles rate and thermal radiation has influence to increase the entropy generation. In addition, horizontal plate corresponding to the wedge angle value m = 0 is the optimum geometry to reduce entropy production.
© Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2020