Modeling Complex Flow and Heat Transfer in Engine Oil Suspended with Gr/MgO/Cu Nanoparticles Using Fractal-Fractional Derivatives

Articles in Press

Document Type : Research Paper

Authors
Gohar Ali 1
Dolat Khan 2
Zeeshan Ali 3
1 Department of Mathematics, City University of Science & Information Technology, Peshawar, KPK, Pakistan
2 Department of Mathematics, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India
3 Department of Information Management, National Yunlin University of Science and Technology: Douliu, Yunlin, Taiwan
10.22055/jacm.2026.48653.5397
Abstract
Industrial applications of diathermal oils have sparked significant interest in recent years, driving innovation in thermal management. This study revolutionizes the field by developing a new fractal-fractional model for analyzing the thermal enactment of three nanoparticles (graphene, magnesium oxide, copper nanoparticles) in channel flows. We create a robust industrial fluid by homogeneously dispersing the dust particles in engine oil. Model the separate momentum equations for the engine oil base fluid velocity and dust particle velocity profiles, yielding exact solutions for both velocity profiles and temperature profiles. The mentioned physical phenomena are expressed through a mathematical model using a fractal fractional derivative based on a power law kernel. The problem has been solved using classical and fractal Laplace transform methods. On solving these problems, it has been possible to calculate the heat transfer rates, shear stresses, and skin friction coefficients. This research work shows a 9.98% improvement in the heat transfer coefficient of engine oil, which proves it to be a good lubricant. Fractal fractional derivatives give a clear insight into memory effects. The proposed model surpasses traditional models based on fractional derivatives, offering improved results. The valuable aspect of this research study lies in its applicability to give a paradigm shift to industries. It will be helpful in designing efficient thermal management systems. The proposed fractal fractional model has a clear edge in terms of memory effect performance. It has been applicable in modeling complicated dynamics of fluids. It could be used for hydraulic fracturing processes. The improved lubrication system for mechanical, advanced cooling system for electronics, and advanced thermal management for aeronautical engineering are applications of this study. The temperature distribution graph peaks for the Eo-MgO-Cu-Gr nanofluid, surpassing the graphs of all other examined combinations.
Keywords
Dust particles
Shape effects
Tri-hybrid nanoparticles
Fractal fractional model
Base fluid engine oil
Subjects

Publisher’s Note Shahid Chamran University of Ahvaz remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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