Significance of Hybrid Nanoparticles and Lorentz Force on the Flow of Water as Base Fluid: The Case of Modified Buongiorno's Model

Abstract The aim of this current analysis is to explore the properties of the hybrid nanoparticles subjected to non‐Newtonian fluid flow over a linearly stretched surface. For the improvement of thermal transport, Tewari and Das model is altered with modify Buongiorno's model. By imposing appropriate similarity transformations on (PDEs), nonlinear ordinary differential equations are achieved. Applying the current similarity synthesis, the PDE model is translated into ODEs and the modified equations are overcome by a well‐known shooting technique. The resulting set of nonlinear ordinary differential equations is eliminated mathematically by utilizing the Runge‐Kutta 4th order method in MATLAB software. The velocity profile goes down with the uplifting values of Hartmann number but it is clearly observed that the results of hybrid nanoparticle's is more effective than mono nanoparticles. To valid the given model, a comparison table is made with the data present in already published papers. Across a comprehensive range of magnetic field intensities, inverse Darcy numbers, and viscoelastic characteristics, the hybrid nanofluid exhibits a moderately enhanced skin friction factor, a slightly diminished heat transfer performance by the Nusselt number, and a marginally improved mass transfer efficiency by the Sherwood number. This work can find applications in the field of metal cooling, paper production etc.

Authors

Institutions

Publication Details

Journal
Advanced Theory and Simulations
Published
2025-05-29
DOI
https://doi.org/10.1002/adts.202500039
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

Significance of Hybrid Nanoparticles and Lorentz Force on the Flow of Water as Base Fluid: The Case of Modified Buongiorno's Model

Se‐Jin Yook, Nehad Ali Shah, Rana Muhammad Zulqarnain, Ghulam Asghar et al.
Advanced Theory and Simulations
Nanofluid Flow and Heat Transfer
article

Significance of Hybrid Nanoparticles and Lorentz Force on the Flow of Water as Base Fluid: The Case of Modified Buongiorno's Model

Se‐Jin Yook, Nehad Ali Shah, Rana Muhammad Zulqarnain, Ghulam Asghar, Sohaib Abdal
article en

Abstract

Abstract The aim of this current analysis is to explore the properties of the hybrid nanoparticles subjected to non‐Newtonian fluid flow over a linearly stretched surface. For the improvement of thermal transport, Tewari and Das model is altered with modify Buongiorno's model. By imposing appropriate similarity transformations on (PDEs), nonlinear ordinary differential equations are achieved. Applying the current similarity synthesis, the PDE model is translated into ODEs and the modified equations are overcome by a well‐known shooting technique. The resulting set of nonlinear ordinary differential equations is eliminated mathematically by utilizing the Runge‐Kutta 4th order method in MATLAB software. The velocity profile goes down with the uplifting values of Hartmann number but it is clearly observed that the results of hybrid nanoparticle's is more effective than mono nanoparticles. To valid the given model, a comparison table is made with the data present in already published papers. Across a comprehensive range of magnetic field intensities, inverse Darcy numbers, and viscoelastic characteristics, the hybrid nanofluid exhibits a moderately enhanced skin friction factor, a slightly diminished heat transfer performance by the Nusselt number, and a marginally improved mass transfer efficiency by the Sherwood number. This work can find applications in the field of metal cooling, paper production etc.

Advanced Theory and SimulationsVol. 8(10)
Sejong University (KR), Khwaja Fareed University of Engineering and Information Technology (PK), Hanyang University (KR), Saveetha University (IN), Anyang University (KR)
Hanyang University
Openalex Percentile: Top 89%
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.