
Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104825 - 104825
Published: April 1, 2025
Language: Английский
Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104825 - 104825
Published: April 1, 2025
Language: Английский
Numerical Heat Transfer Part B Fundamentals, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 29
Published: May 1, 2024
Language: Английский
Citations
33Case Studies in Thermal Engineering, Journal Year: 2024, Volume and Issue: 60, P. 104624 - 104624
Published: May 31, 2024
Quadratic thermal radiation is a fundamental term within the field of radiative heat transfer, which pertains to interaction radiation. It encompasses quadratic correlation between temperature and qualities. Although linear more prevalent in numerous everyday applications, non-linear important some situations, particularly where precise representation transfer required. The phenomenon assumes crucial function contexts that need enhanced accuracy modeling transfer. In view this, present investigation carried out examine hybrid nanofluid flow across cylinder under influence quadratic, nonlinear activation energy. governing system differential equations transformed into ordinary via similarity transformations. current study presents results utilizing shooting Runge-Kutta Fehlberg 45 numerical scheme. outcomes show curvature constraint will improve all three profiles while solid fraction decreases velocity raises other two profiles. shows less distribution, followed by cases. rate distribution improves 0.60% for case, 0.52% case 0.656% from nanofluid. Further, mass 0.068% improvement provide useful insights may be used enhance efficiency various including but not limited mechanics fluids, chemical technology, administration.
Language: Английский
Citations
28International Communications in Heat and Mass Transfer, Journal Year: 2024, Volume and Issue: 155, P. 107573 - 107573
Published: May 13, 2024
Language: Английский
Citations
18Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 105, P. 437 - 448
Published: Aug. 6, 2024
The industrial significance of stability analysis for dual solutions and heat transfer sets the stage this research. Focusing on Maxwell ternary nanofluid flow, study aims to enhance thermal conductivity by delving into viscous dissipation velocity slip effects a stretching/shrinking sheet. Employing mathematical model, refined with nondimensional transformations MATLAB's BVP4C solver, research identifies examines influence key parameters fluid dynamics transfer. Results showcase progressive improvement in convective skin friction from mono (NF) binary hybrid (HNF), culminating (THNF). These improvements are significantly associated suction/injection parameter (S), whereas (σ) elastic (K) but negatively affect efficiency at elevated levels. robustness upper branch underscores reliability these findings. Remarkably, λ=−1.25 nanoparticle volume fraction 0.04, nanofluids achieve 2.9% leap over HNF, which itself surpasses NF 0.46%. findings hold potential significant advancements sectors such as electronics, manufacturing, energy, biomedical, environmental engineering, aerospace, automotive, aiming elevating efficiency.
Language: Английский
Citations
17Journal of Radiation Research and Applied Sciences, Journal Year: 2025, Volume and Issue: 18(1), P. 101315 - 101315
Published: Feb. 5, 2025
Language: Английский
Citations
8Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 116, P. 427 - 438
Published: Jan. 5, 2025
Language: Английский
Citations
4International Journal of Thermofluids, Journal Year: 2025, Volume and Issue: unknown, P. 101075 - 101075
Published: Jan. 1, 2025
Language: Английский
Citations
4Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 117, P. 403 - 417
Published: Jan. 18, 2025
Language: Английский
Citations
4Chinese Journal of Physics, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Language: Английский
Citations
2Case Studies in Thermal Engineering, Journal Year: 2024, Volume and Issue: 56, P. 104248 - 104248
Published: March 13, 2024
The thermal case study is conducted by using artificial intelligence to examine the heat transfer traits in Williamson fluid flow with source and slip effects. field interacts externally applied magnetic velocity additionally considered at surface. formulated terms of energy momentum equations. All inputs (Prandtl number, field, slip, Weissenberg number) are represented a 4 × 72 matrix samples Nusselt number 1 matrix. randomly divided into three stages: 70%(50) for training, 15%(11) each validation testing. neurons set ten. To train neural networking model, Levenberg-Marquardt algorithm employed. best performance noticed 5.9676e-08. This indicates that network was successfully trained predict NN magnetized For generation parameters, magnitude temperature higher non-magnetic field. Further, admits declining trend while it shows inciting values Prandtl number.
Language: Английский
Citations
14