Numerical study of Carreau fuzzy nanofluid across a stretching cylinder using a modified version of Buongiorno's nanofluid model

• Published in: Alexandria engineering journal 2024-08, Vol.101, p.318-329
• Main Authors: Asaigeethan, P., Vaithiyalingam, K., Loganathan, K., Prabu, K., Abbas, Mohamed, Mishra, Nirmith Kumar
• Format: Article
• Language: English
• Subjects: bvp5c; Carreau nanofluid; Modified Buongiorno’s model; Stretching cylinder; TFNs; TMF
• ISSN: 1110-0168
• DOI: 10.1016/j.aej.2024.05.095

The principal intention of the currently analysis is to investigate the impacts of the naturally convective nanofluid using a model of Carreau fluid with engine oil (CnH2n+2)as the base fluid and Manganese Zinc Ferrite (MnZnFe2O4)as the nanoparticle, the fluid flowing through a stretched cylinder in a fuzzy ambient. It examines the impact of assorted parameters, Weissenberg number(We), Prandtl numeral(Pr), Schmidt numeral (Sc), and curvature (k)with magnetic field(B) and nanoparticle parameter, in order to manipulate an analogous conversion, the regulating equations of velocity, energy, and concentration profiles permute from a set of partial differential equations stand to ordinary differential equations. The present analysis focuses on the no slip assumption, which gives rise to a nonlinear Dirichlet boundary condition in axial velocity. The bvp5c approach was utilized to solve the resulting series of equations by the MATLAB. This is a highly effective approach with minimal computing expenditure. The volume quantity of nanoparticles in MnZnFe2O4 is considered an uncertain parameter respect to TFNs (triangular fuzzy numbers) ranging [0, 0.5, 0.1]. Triangular membership function (TMF) is used to study the uncertainty variability while α − cut controls the TFNs. Fuzzy linear regression analysis makes use of TFNs to determine the middle (crisp), left, and right values of the fuzzy velocity profile. In comparison to the crisp velocity profile (mid value), the study's result and the fuzzy velocity profile have the maximum rate of flow. Tables and graphs are used to illustrate the outputs.