Modified magnetic flow of Williamson nanofluid over a stretching sheet with Newtonian heating

In systems where heat transfer and flow dynamics are crucial, the Williamson nanofluid model is a useful tool for studying non-Newtonian fluids. Numerous industrial applications, such as energy systems, manufacturing processes, and thermal management systems, depend on non-Newtonian fluid flows. In conjunction to this, this paper aims to investigate numerically the boundary layer flow of a Williamson nanofluid across a stretching sheet under modified magnetic influence and Newtonian heating (NH). Thus, the goal of the study is to investigate how the velocity and temperature profiles are affected by several characteristics, such as the concentration of nanoparticles, the strength of the magnetic field, the Williamson fluid properties, and thermal boundary conditions. To solve the nonlinear ordinary differential equations resulting from the application of similarity variables to the governing partial differential equations, the Runge–Kutta–Fehlberg (RKF45) method is utilized. To comprehend their impact on the fluid's behaviour and heat distribution, the analysis assesses several pertinent physical characteristics. The findings show that while magnetic effect reduces velocity, raising the Williamson parameter improves thermal performance. It is anticipated that these discoveries will advance our knowledge of non-Newtonian nanofluid flows and offer guidance for improving engineering systems that employ them.

Authors

Institutions

Publication Details

Journal
Data Analytics and Applied Mathematics (DAAM)
Published
2025-09-30
DOI
https://doi.org/10.15282/daam.v6i2.13064
Primary Topic
Nanofluid Flow and Heat Transfer
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modified magnetic flow of Williamson nanofluid over a stretching sheet with Newtonian heating

Imran Ullah, Abdul Rahman Mohd Kasim, Nur Syamilah Arifin, Ahmad Khudzairi Khalid et al.
Data Analytics and Applied Mathematics (DAAM)
Nanofluid Flow and Heat Transfer
article

Modified magnetic flow of Williamson nanofluid over a stretching sheet with Newtonian heating

Imran Ullah, Abdul Rahman Mohd Kasim, Nur Syamilah Arifin, Ahmad Khudzairi Khalid, Nur Intan Syafinaz Ahmad, Wan Munirah Wan Mohamad, Abdul Fatah Zainuddin
article en

Abstract

In systems where heat transfer and flow dynamics are crucial, the Williamson nanofluid model is a useful tool for studying non-Newtonian fluids. Numerous industrial applications, such as energy systems, manufacturing processes, and thermal management systems, depend on non-Newtonian fluid flows. In conjunction to this, this paper aims to investigate numerically the boundary layer flow of a Williamson nanofluid across a stretching sheet under modified magnetic influence and Newtonian heating (NH). Thus, the goal of the study is to investigate how the velocity and temperature profiles are affected by several characteristics, such as the concentration of nanoparticles, the strength of the magnetic field, the Williamson fluid properties, and thermal boundary conditions. To solve the nonlinear ordinary differential equations resulting from the application of similarity variables to the governing partial differential equations, the Runge–Kutta–Fehlberg (RKF45) method is utilized. To comprehend their impact on the fluid's behaviour and heat distribution, the analysis assesses several pertinent physical characteristics. The findings show that while magnetic effect reduces velocity, raising the Williamson parameter improves thermal performance. It is anticipated that these discoveries will advance our knowledge of non-Newtonian nanofluid flows and offer guidance for improving engineering systems that employ them.

Data Analytics and Applied Mathematics (DAAM)
Universiti Malaysia Pahang Al-Sultan Abdullah (MY), Hospital Tuanku Ja’afar (MY), Malaysia Theological Seminary (MY), Universiti Teknologi MARA (MY), National University of Sciences and Technology (PK)
Universiti Teknologi MARA
Openalex Percentile: Top 69%
Nanofluid Flow and Heat Transfer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.