Mathematical simulation of radiative nanofluid flow and heat transfer past a stretching surface: A parametric study DOI
Sidra Jubair,

Sajida Raz Bhutto,

Ioan‐Lucian Popa

et al.

Journal of Radiation Research and Applied Sciences, Journal Year: 2025, Volume and Issue: 18(3), P. 101620 - 101620

Published: May 22, 2025

Language: Английский

Entropy optimization in non-newtonian prandtl-eyring fluid using ANN over a curved riga surface DOI
Muhammad Bilal, Muhammad Farooq, M. Benghanem

et al.

International Journal of Thermal Sciences, Journal Year: 2025, Volume and Issue: 212, P. 109765 - 109765

Published: Feb. 10, 2025

Language: Английский

Citations

3

Unsteady thermal convective transport of nanofluids with couple stress through a circular microchannel under the time-periodic pressure gradient and electromagnetohydrodynamic DOI
Jiali Zhang, Guangpu Zhao, Umer Farooq

et al.

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: 69, P. 105984 - 105984

Published: March 15, 2025

Language: Английский

Citations

0

ANN-Based Prediction and RSM Optimization of Radiative Heat Transfer in Couple Stress Nanofluids with Thermodiffusion Effects DOI Open Access
Reima Daher Alsemiry, Sameh E. Ahmed, Mohamed R. Eid

et al.

Processes, Journal Year: 2025, Volume and Issue: 13(4), P. 1055 - 1055

Published: April 1, 2025

This research investigates the impact of second-order slip conditions, Stefan flow, and convective boundary constraints on stagnation-point flow couple stress nanofluids over a solid sphere. The nanofluid density is expressed as nonlinear function temperature, while diffusion-thermo effect, chemical reaction, thermal radiation are incorporated through linear models. governing equations transformed using appropriate non-similar transformations solved numerically via finite difference method (FDM). Key physical parameters, including heat transfer rate, analyzed in relation to Dufour number, velocity, parameters an artificial neural network (ANN) framework. Furthermore, response surface methodology (RSM) employed optimize skin friction, transfer, mass by considering influence radiation, slip, reaction rate. Results indicate that velocity enhances behavior reducing temperature concentration distributions. Additionally, increase number leads higher profiles, ultimately lowering overall ANN-based predictive model exhibits high accuracy with minimal errors, offering robust tool for analyzing optimizing transport characteristics nanofluids.

Language: Английский

Citations

0

Arrhenius Activation Energy and Binary Chemical Reaction Model in Low Magnetic Field Nanofluid Flow System DOI

M. Nagapavani,

K. Thanesh Kumar, Abhayveer Singh

et al.

Asia-Pacific Journal of Chemical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 10, 2025

ABSTRACT Researchers have significantly explored the fluid motion over rotating surfaces for their significant uses in many technical and manufacturing processes, including centrifugal compressors, gas steam turbines, viscometers, pumps, fans, spin‐coating, computer storage systems. A low‐oscillating magnetic field plays a crucial role heat transport efficiency, nanoparticle manipulation, enhancement of stability rheology. In view this, present study explores consequence on three‐dimensional unsteady stream nanofluid past slowly revolving disk with quadratic thermal radiation, variable conductivity, suction, activation energy. The generalized Fouriers Ficks law is also considered to analyze mass transport. governing partial differential equations are transformed into dimensionless ordinary suitable similarity variables. finite difference technique utilized solve resulting (ODEs) numerically. impact various factors concentration, velocity, temperature profiles shown visually. For unsteadiness parameter, skin friction increases by approximately 5.29%. As suction parameter values rise, velocity decreases. profile rise conductivity parameter's value. radiation intensifies profile. concentration reduces as relaxation time increases.

Language: Английский

Citations

0

Deep Learning-driven analysis using artificial neural networks of hydrodynamic and radiative behavior of SAE oil-based hybrid nanofluid over stretching surface DOI
Sidra Jubair, Mansourah Aljohani, Wafa F. Alfwzan

et al.

Journal of Radiation Research and Applied Sciences, Journal Year: 2025, Volume and Issue: 18(3), P. 101588 - 101588

Published: May 8, 2025

Language: Английский

Citations

0

Mathematical simulation of radiative nanofluid flow and heat transfer past a stretching surface: A parametric study DOI
Sidra Jubair,

Sajida Raz Bhutto,

Ioan‐Lucian Popa

et al.

Journal of Radiation Research and Applied Sciences, Journal Year: 2025, Volume and Issue: 18(3), P. 101620 - 101620

Published: May 22, 2025

Language: Английский

Citations

0