A model-based study on heat transfer and irreversibility in squeezing bioconvective-Casson hybrid nanofluid with variable conductivity: Sensitivity analysis
Year: 2025
Type: article
Abstract: The current research focuses on optimizing heat transfer and analyzing entropy generation in the unsteady bioconvective flow of a Casson hybrid nanofluid within a squeezing channel, incorporating variable thermal conductivity. The research integrates magnetohydrodynamics, thermal radiation, thermophoretic particle deposition, and a heat source/sink in a porous medium to develop a novel framework for hybrid nanofluid modeling. The primary objective is to enhance thermal management for biomedical and industrial applications using a hybrid nanofluid comprising uranium dioxide and copper nanoparticles suspended in a blood-based fluid. A comparative analysis of two thermal conductivity models, the Hamilton-Crosser (HC) and Yamada–Ota (YO) models, is conducted to evaluate their effectiveness in enhancing heat transfer. The governing nonlinear partial differential equations are transformed into ordinary differential equations using similarity transformations and solved via the semi-analytical homotopy analysis method (HAM). The results highlight the YO model’s superior thermal performance compared to the HC model. Response surface methodology (RSM) highlights the parametric influences, offering actionable insights for designing energy-efficient systems. Thermal energy transmission is highly sensitive to the Eckert number and nanoparticle concentration, while entropy generation increases with higher magnetic parameters and Eckert numbers and decreases with improved conductivity and the Casson parameter. This comprehensive integration of diverse physical effects offers valuable insights into optimizing heat transfer and entropy management, paving the way for innovative applications in biomedical systems and energy-efficient industrial processes.
Source: Chinese Journal of Physics
Authors: Seetalsmita Samal, Surender Ontela
Institution: National Institute of Technology Kurukshetra
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,000
OpenAlex ID: W4408916171