Numerical analysis of free convection from a spinning cone with variable wall temperature and pressure work effect using MD-BSQLM

The problem of the numerical analysis of natural convection from a spinning cone with variable wall temperature, viscous dissipation and pressure work effect is studied. The numerical method used is based on the spectral analysis. The method used to solve the system of partial differential equations is the multi-domain bivariate spectral quasi-linearization method (MD-BSQLM). The numerical method is compared with other methods in the literature, and the results show that the MD-BSQLM is robust and accurate. The method is also stable for large parameters. The numerical errors do not deteriorate with increasing iterations for different values of all parameters. The numerical error size is of the order of 1 0 − 10 1{0}^{-10} . With the increase in the suction parameter ξ \xi , fluid velocity, spin velocity and temperature profiles decrease.

Entropy generation of tangent hyperbolic nanofluid flow past a stretched permeable cylinder: Variable wall temperature

Numerical computations are presented to scrutinize the entropy analysis in a steady magneto-hydrodynamic non-Newtonian tangent hyperbolic nanofluid regime adjacent to an accelerating stretching cylinder manifested with variable wall temperature. Some of the different water-regular nanofluids involving Cu, Ag, Al2O3, and TiO2 have been addressed. Both the motion governing equations and the equation of entropy generation are formulated in cylindrical coordinates. Similar scaling transformation has been chosen to mutate the governing equations into ordinary differential equations system. Then the resulting ordinary differential equations are solved numerically via the implicit finite difference Keller box. In order to comprehend the flow behavior nearby the cylinder surface, the impacts of such different parameters on entropy generation number, velocity, and temperature distributions have been analyzed in detail. As it is noticed, the temperature distribution represents a decreasing function of mixed convection parameter while an opposite trends are given for nanoparticle volume fraction, curvature, and magnetic field parameters. Additionally, the entropy generation number is an increasing function of the Reynolds number, curvature, and mixed convection parameters, whereas it reduces with magnetic field parameter. The given numerical computations have been validated by a comparison with already published literature, which supports our present developed model.