A numerical frame work of magnetically driven Powell-Eyring nanofluid using single phase model

  • Wasim Jamshed
  • , Mohamed R. Eid
  • , Kottakkaran Sooppy Nisar
  • , Nor Ain Azeany Mohd Nasir
  • , Abhilash Edacherian
  • , C. Ahamed Saleel
  • , V. Vijayakumar

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

The current investigation aims to examine heat transfer as well as entropy generation analysis of Powell-Eyring nanofluid moving over a linearly expandable non-uniform medium. The nanofluid is investigated in terms of heat transport properties subjected to a convectively heated slippery surface. The effect of a magnetic field, porous medium, radiative flux, nanoparticle shapes, viscous dissipative flow, heat source, and Joule heating are also included in this analysis. The modeled equations regarding flow phenomenon are presented in the form of partial-differential equations (PDEs). Keller-box technique is utilized to detect the numerical solutions of modeled equations transformed into ordinary-differential equations (ODEs) via suitable similarity conversions. Two different nanofluids, Copper-methanol (Cu-MeOH) as well as Graphene oxide-methanol (GO-MeOH) have been taken for our study. Substantial results in terms of sundry variables against heat, frictional force, Nusselt number, and entropy production are elaborate graphically. This work’s noteworthy conclusion is that the thermal conductivity in Powell-Eyring phenomena steadily increases in contrast to classical liquid. The system’s entropy escalates in the case of volume fraction of nanoparticles, material parameters, and thermal radiation. The shape factor is more significant and it has a very clear effect on entropy rate in the case of GO-MeOH nanofluid than Cu-MeOH nanofluid.

Original languageEnglish
Article number16500
JournalScientific Reports
Volume11
Issue number1
DOIs
StatePublished - Dec 2021

Fingerprint

Dive into the research topics of 'A numerical frame work of magnetically driven Powell-Eyring nanofluid using single phase model'. Together they form a unique fingerprint.

Cite this