Numerical simulation of melting heat transport mechanism of Cross nanofluid with multiple features of infinite shear rate over a Falkner‐Skan wedge surface

Author:

Darvesh Adil1ORCID,Santisteban Luis Jaime Collantes2ORCID,Khan Shahzeb3,Maiz Fethi Mohamed4,AL Garalleh Hakim5ORCID,Sánchez‐Chero Manuel6

Affiliation:

1. Department of Mathematics and Statistics Hazara University Mansehra Pakistan

2. Department of Mathematics Universidad Nacional Pedro Ruiz Gallo Lambayeque Perú

3. School of Mathematics and Statistics Central South University Changsha Hunan China

4. Faculty of Science, Physics Department King Khalid University Abha Saudi Arabia

5. Department of Mathematical Science College of Engineering University of Business and Technology Jeddah Saudi Arabia

6. Facultad de Ingeniería de Industrias Alimentarias y Biotecnología Universidad Nacional de Frontera Sullana Perú

Abstract

AbstractThe wedge geometry is a cornerstone in thermal transport mechanism, sepcially in scenarios involving fluid flow over surfaces. The current study emphasizes the melting heat transport mechanism in a Graphene oxide nanofluid over a Falkner‐Skan wedge geometry in the presence of multiple features of infinite shear rate accompanied with variable thermal transport characteristics and activation energy. Additionally, Cross model incorporated in the sytem, which predicts accurate behavior of intricate flow for better thermal simulation. The flow is governed by framed set of partial differential equations based on Naver stokes relations. A highly nonlinear system is altered in simplified non dimensional form using similarity variables. Numerical simulations are performed by an efficient MATLAB (bvp4c) solver scheme and the results of emerging parameters are compiled via different pictorial and tabular representations. The higher values of velocity ratio and melting heat parameter boost up the heat transfer rate over the Falkner‐Skan wedge geometry, whereas Brownian motion of nanofluid molecules arises by thermophoresis which declines the concentration profile. Numeric growth in the values of Schmidt number reduce the mass diffusivity, which declines the fluid temperature distribution. Likewise, Increasing value of Prandtl number causes reduction in thermal conductivity and produces temperature fall. It is worth noting that, this computational assessment is crucial in thermal processes because the results derived from this analysis enable the optimization of designs for better performance, efficiency, and control in practical applications.

Funder

King Khalid University

Publisher

Wiley

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