Convection refers to the heat transfer that occurs between moving fluid and surface at a different temperature. Nowadays, there has been a great deal of interest in the convective boundary layer fluid flow problems. Despite its popularity, the review paper discussing the mathematical model for various fluid types regarding various geometry and boundary conditions has been observed to fall short. This review paper adopts a thematic review based on the mathematical model captured in published fluid flow problems from 2015 until 2020. The articles were analysed using thematic analysis ATLAS.ti 8 software. Using keyword search and filtering criteria from Scopus and Web of Science (WOS) databases, 198 peer-reviewed journal articles were identified. However, after the exclusion and inclusion processes, only 50 articles were reviewed as final articles. The thematic review of these articles has further identified 120 initial codes characterising the mathematical model, grouped into 7 clusters: Viscoelastic, Williamson, Casson, Brinkman, Jeffrey, Nanofluid and hybrid Nanofluid. The report from the code-to-document in ATLAS.ti 8 found that the boundary condition, geometry and method were highlighted in the literature. The outcomes of this study will benefit the future research direction to identify the gap for future studies, specifically in extending the mathematical model for fluid flow problems as well as choosing the suitable geometry and boundary condition.
Present paper utilizes a combination of non-Newtonian fluid model (Jeffrey fluid) with Buongiorno model (nanofluid). The Jeffery fluid, which is regarded as a base fluid, together with suspended nanoparticles are examined over an inclined stretching sheet with the amalgamated impacts of mixed convection and viscous dissipation. The mathematical formulation of this model is done by choosing the appropriate similarity variables for the aim to reduce the complexity of governing partial differential equations. The Runge-Kutta-Fehlberg (RKF45) method is then applied to the resulting of non-linear ODE to generate numerical results for highlighting the impact of emerging parameters towards specified distributions. Both the graphical and tabular representations of vital engineering physical quantities are also shown and deliberated. For the increase of Eckert number, thermophoresis diffusion, and Brownian motion parameters, the elevation of temperature profiles is observed. Besides, the thermophoresis diffusion parameter tends to accelerate the nanoparticle concentration profile while Brownian motion parameter displays the opposite behavior.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.