Boundary Layer Flow of Dusty Ferrofluid: A Comparative Analysis of Stagnation Flow Influence

Authors

  • Cik Siti Hajar Abdulah Institute of Engineering Mathematics, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia.
  • ROHANA BINTI ABDUL HAMID Institute of Engineering Mathematics, Universiti Malaysia Perlis (UniMAP), 02600 Arau, Perlis, Malaysia.
  • ROSLINDA BINTI MOHD NAZAR Department of Mathematical Sciences, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

DOI:

https://doi.org/10.58915/amci.v13i4.1468

Abstract

This research examines the characteristics of the boundary layer in the occurrence of dust particles within the ferrofluid boundary layer, aiming to understand the impact of stagnation flow or without stagnation flow in such systems. For this purpose, ferroparticles, namely magnetite (Fe3O4), are taken into consideration with kerosene and water as base fluids. The governing partial differential equations of the problem under consideration are converted into ordinary differential equations (ODEs) through the utilization of similarity transformations. Here, the equations obtained are then numerically solved utilizing MATLAB's built-in bvp4c solver. Moreover, the parameters’ effects, namely the dust particle loading, volume fraction of ferroparticles, and Eckert number to the flow with and without stagnation flow are computed and shown through tables and graphs. The findings indicate that the skin friction coefficient values for the stagnation-point flow are higher than those without stagnation-point flow. The Eckert number increases temperature profiles for both flows but more prominent in the flow without stagnation-point.

Keywords:

Boundary layer, dusty ferrofluid, magnetohydrodynamics, moving surface, stagnation-point

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Published

2024-11-07

How to Cite

Cik Siti Hajar Abdulah, ROHANA BINTI ABDUL HAMID, & ROSLINDA BINTI MOHD NAZAR. (2024). Boundary Layer Flow of Dusty Ferrofluid: A Comparative Analysis of Stagnation Flow Influence. Applied Mathematics and Computational Intelligence (AMCI), 13(4), 1–13. https://doi.org/10.58915/amci.v13i4.1468

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