137
Views
3
CrossRef citations to date
0
Altmetric
Research Article

Magnetic convection nanofluid confined in a cavity with chamfers containing cylinder obstacles with a heat source/sink

ORCID Icon & ORCID Icon
Received 15 Oct 2021, Accepted 30 May 2022, Published online: 15 Jun 2022
 

Abstract

The current research introduces a numerical treatment of MHD laminar convection flow within chamfers cavity containing adiabatic obstacle. Both the flow domain and the magnetic field are inclined with miscellaneous angles and the impacts of the heat absorption (generation) are conducted. The mathematical model of the considered problem is formulated and the finite element (FE) approach is developed to simulate the governing system. The prime outcomes detected that the growth of the chamfers ratio decreases the heat transfer rate within the cavity whereas increasing the aspect ratio affects the isotherms distributions which result in enhancing the average Nusselt numbers. Moreover, the presence of the magnetic field or the nanoparticles leads to slow fluid movement. An enhancement in the heat transfer with a relative of percentage of 16.6 is achieved with nanofluid of ϕ=6% compare to the case of pure fluid at Ha = 100. Also, the highest percentage of the relative Nusselt number is about 258%, concluded in the absence of magnetic field with Ra varies from 103 to 106.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 552.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.