Cargando…

Modeling of entropy optimization for hybrid nanofluid MHD flow through a porous annulus involving variation of Bejan number

We numerically investigate the non-Darcy magnetohydrodynamic hybrid nanoparticle migration through a permeable tank using control volume finite element method through entropy generation. The roles of various amounts of Permeability, Lorentz and Rayleigh (Ra) number are investigated upon the various...

Descripción completa

Detalles Bibliográficos
Autores principales: Shah, Zahir, Sheikholeslami, M., Kumam, Poom, Ikramullah, Shafee, Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393077/
https://www.ncbi.nlm.nih.gov/pubmed/32732958
http://dx.doi.org/10.1038/s41598-020-69458-1
Descripción
Sumario:We numerically investigate the non-Darcy magnetohydrodynamic hybrid nanoparticle migration through a permeable tank using control volume finite element method through entropy generation. The roles of various amounts of Permeability, Lorentz and Rayleigh (Ra) number are investigated upon the various aspects of the hybrid nanofluid flow through contour and 3-D plots. Through curve fitting technique, analytical expressions for Nu(ave) and Bejan number as functions of Ra, Ha and Da are obtained. It is found that the strength of the vortexes decline and temperature of the inner wall augments with the higher magnetic field, while temperature drops with increasing buoyancy forces and medium permeability. The irreversibility terms associated with the generation of the thermal energy and applied magnetic field (S(gen,th), S(gen,M)) enhance while the other terms (S(gen,f), S(gen,p)) drop with the rising values of the magnetic field strength. These quantities show exactly opposite behavior with augmenting Da. The Bejan number drops while Nu(ave) augments with the rising buoyancy forces. The agreement with the previous published results confirms the accuracy of the employed computational model.