Signal-to-noise ratio and ANOVA approach to analyze tetra-hybrid radiative nanofluid flow under horizontal magnetic field

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Authors: Vishwanatha R. Banakar, R. Naveen Kumar, Ioannis E. Sarris, A. B. Sathisha
Cited by: 3

Abstract

The thermal efficiency of tetra-hybrid nanofluids exposed to a horizontal magnetic field over a stretched revolving disk has significant potential for enhanced cooling and energy-related applications. Such fluids, formed by dispersing multiple nanoparticles within a base fluid, offer enhanced heat transfer suitable for turbine blade cooling, compact electromagnetic heat exchangers, and biomedical thermal control systems. In this study, the three-dimensional flow of a tetra-hybrid nanofluid over a rotating stretchable disk is analyzed by accounting for the combined influence of a horizontal magnetic field, porous medium, thermal radiation, and internal heat sink/source under convective boundary conditions. The governing equations are transformed into ordinary differential equations (ODEs) and solved numerically using the Runge–Kutta–Fehlberg–Fourth–Fifth (RKF-45) method. To maximize the heat transfer rate, the Taguchi-based statistical method, combined with signal-to-noise ratio analysis and analysis of variance (ANOVA), is employed. The results reveal that increasing magnetic field strength and porosity significantly suppress both tangential and radial velocities due to enhanced resistive forces. Quantitatively, the optimization predicts a maximum Nusselt number of 10.4844123215026. The ANOVA results show that the rotational parameter dominates heat transfer enhancement with a contribution of 86.86%, while the Biot number has a minimal influence of only 0.30%. These findings provide useful design guidance for controlling thermal performance in magnetically regulated cooling systems and high-efficiency thermal management devices.

Fields of Study & Subjects

Nanofluid Flow and Heat Transfer Heat Transfer Mechanisms Fluid Dynamics and Vibration Analysis

Publication details

Journal / source
International Journal of Computational Materials Science and Engineering
Publisher
World Scientific Pub Co Pte Ltd
Publication date
19 February 2026
Language
EN