Significance of heat transfer for second-grade fuzzy hybrid nanofluid flow over a stretching/shrinking Riga wedge

AIMS Mathematics

article

Imran Siddique¹  Yasir Khan²  Muhammad Nadeem¹  Jan Awrejcewicz³  Muhammad Bilal⁴ 

[1] Department of Mathematics, University of Management and Technology;Department of Mathematics, University of Hafr Al Batin;Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology;Department of Mathematics, The University of Chenab

关键词: hybrid nanofluid;    second-grade fluid;    stagnation point flow;    stretching/shrinking Riga wedge;    TFN;   

DOI  :  10.3934/math.2023014

学科分类：地球科学(综合)

来源: AIMS Press

【 摘 要 】

This investigation presents the fuzzy nanoparticle volume fraction on heat transfer of second-grade hybrid $ {\text{A}}{{\text{l}}_{\text{2}}}{{\text{O}}_{\text{3}}}{\text{ + Cu/EO}} $ nanofluid over a stretching/shrinking Riga wedge under the contribution of heat source, stagnation point, and nonlinear thermal radiation. Also, this inquiry includes flow simulations using modified Hartmann number, boundary wall slip and heat convective boundary condition. Engine oil is used as the host fluid and two distinct nanomaterials ($ {\text{Cu}} $ and $ {\text{A}}{{\text{l}}_{\text{2}}}{{\text{O}}_{\text{3}}} $) are used as nanoparticles. The associated nonlinear governing PDEs are intended to be reduced into ODEs using suitable transformations. After that 'bvp4c, ' a MATLAB technique is used to compute the solution of said problem. For validation, the current findings are consistent with those previously published. The temperature of the hybrid nanofluid rises significantly more quickly than the temperature of the second-grade fluid, for larger values of the wedge angle parameter, the volume percentage of nanomaterials. For improvements to the wedge angle and Hartmann parameter, the skin friction factor improves. Also, for the comparison of nanofluids and hybrid nanofluids through membership function (MF), the nanoparticle volume fraction is taken as a triangular fuzzy number (TFN) in this work. Membership function and $ \sigma {\text{ - cut}} $ are controlled TFN which ranges from 0 to 1. According to the fuzzy analysis, the hybrid nanofluid gives a more heat transfer rate as compared to nanofluids. Heat transfer and boundary layer flow at wedges have recently received a lot of attention due to several metallurgical and engineering physical applications such as continuous casting, metal extrusion, wire drawing, plastic, hot rolling, crystal growing, fibreglass and paper manufacturing.

【 授权许可】

CC BY