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    FEM treatments for MHD radiative convective flow of MWCNTs –C2H6O2 nanofluids between inclined hexagonal/hexagonal or hexagonal/cylinder

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    Type
    Article
    Authors
    Ahmed, Sameh E. cc
    Raizah, Zehba A.S.
    Date
    2021-07
    Permanent link to this record
    http://hdl.handle.net/10754/670657
    
    Metadata
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    Abstract
    This paper aims to analyze the second law of the thermodynamic for the non-Newtonian power-law nanofluids flow between inclined polygonal/polygonal or polygonal/cylinder shapes. Multi-wall carbon nanotubes are incorporated in the ethylene glycol as a base fluid to formulate the worked suspension. Electromagnetic forces together with the thermal radiation are taken into account. Unusually, the magnetic field is assumed to be horizontal while the flow domain is inclined and a semi implicit treatment is presented for the magnetic terms. The solution methodology is depending on the Galerkin finite element method (FEM) and the Characteristic-Based Split (CBS) scheme. Various designs for the considered models are considered based on the areas and shapes of the inner polygonal/cylinder. The main outcomes revealed that area of the flow and power-law index N control in the convective and heat transfer process. Also, the fluid friction irreversibility takes its maximum values at high values of the power-law index. Furthermore, ratios of the increase in values of the entropy tools (ST+,SF+,Stot+) due to the variations of γ take their maximum at γ=30 and low values of Ha.
    Citation
    Ahmed, S. E., & Raizah, Z. A. S. (2021). FEM treatments for MHD radiative convective flow of MWCNTs C2H6O2 nanofluids between inclined hexagonal/hexagonal or hexagonal/cylinder. Ain Shams Engineering Journal. doi:10.1016/j.asej.2021.07.003
    Sponsors
    The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through research groups program under Grant Number (R. G. P2/144/42). For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia.
    Publisher
    Elsevier BV
    Journal
    Ain Shams Engineering Journal
    DOI
    10.1016/j.asej.2021.07.003
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/S2090447921003002
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.asej.2021.07.003
    Scopus Count
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