Modelling and Analysis of Peristaltic Flows of Nanofluids and Hybrid Nanofluids for Heat Transfer Applications
This thesis presents a comprehensive investigation into the peristaltic flow of nanofluids through different channel configurations, focusing on the behaviour of non-Newtonian nanofluids and their thermal and mechanical characteristics. The primary objective is to analyse the associated entropy generation, heat transfer properties, and the influence of physical parameters on the flow behaviour. Mathematical models and numerical methods are employed to study the flow behaviour and derive relevant results. The analysis takes into account various physical phenomena, including Hall current, mixed convection, Ohmic heating, heat generation/annihilation, viscous dissipation, Lorentz force, thermal radiation, and concentration behaviour. The rheological characteristics of nanofluids are determined using appropriate models, and the mathematical models are simplified using long wavelength and low Reynolds number approximations. The results so obtained shed light on the impact of different physical parameters on temperature profiles, entropy generation, velocity, pressure gradient, concentration, and heat transfer rates. It is observed that the growth of nanoparticle volume fraction in nanofluids leads to reductions in temperature, entropy generation, velocity, and pressure gradient. Additionally, enhanced Hall and Brinkman parameters have a diminishing effect on entropy generation and temperature, while the enhanced permeability parameter reduces velocity and pressure gradients significantly. The effects of thermal radiation, thermal conductivity, and Hartmann number on temperature profiles and entropy generation are also analysed. The practical implications of this research extend to various fields, including materials science, chemical engineering, and biomedical engineering. Better understanding of nanofluid behaviour during peristaltic flow can contribute to the design of more efficient and safe drug delivery systems. Moreover, the findings provide insights into heat and mass transfer processes, paving the way for advancements in diverse industrial applications includingbut not limited to energy generation, chemical processing, materials engineering, and environmental technologies.
History
Supervisor(s)
Ruslan Davidchack; Aldo RonaDate of award
2024-03-05Author affiliation
School of Computing and Mathematical SciencesAwarding institution
University of LeicesterQualification level
- Doctoral
Qualification name
- PhD