City Research Online

Abstract

Fluids of complex rheology (polymer solutions, nanofluids, biological specimens and so on) are utilised in consumer products, heavy industry as well as biomedical applications driving the technological advancements. They find uses in crude oil recovery, pharmaceuticals, micro-electromechanical systems, lubrication, and thermal management systems to name a few. Despite this, the behaviour of such fluids as a response to various physical conditions and external stimuli is yet to be elucidated convincingly. In the present study, novel heat transfer liquids are sought for immersive-cooling applications of electric vehicle (EV) battery thermal management systems (BTMS). The application limits the families of base solvents to dielectric compounds that can be utilised to design the coolants. Niche requirements such as this demand computational modelling and simulation methods suitable for the design and property predictions of the engineered fluids. The computational research in this field must be able to link the chemistry of the complex liquids to the anticipated heat transfer effectiveness performance in BTMS. Molecular dynamics (MD) simulations founded on statistical and Newtonian mechanics can provide insights into the relationship between the chemical structure and rheological behaviour of the non-Newtonian fluids. Additionally, a bottom-up approach of modelling the liquids based on MD can complement experimental studies. The current MD research on this front is severely scattered.

The research begins with the systematic study of oil-based polymer solutions that are compounds of interest in heat transfer applications. Atomistic MD studies are performed to obtain the structural, transport and rheological properties of the compounds. The addition of the polymer chain in oil shows the early onset of shear-thinning which helps maintain stable vortices, which in turn enhance heat transfer by disrupting the thermal boundary layer. At the same time, the thermal conductivity of the resultant solution increases with the addition of polymer. Satisfactory models based on the comparison of properties with atomistic MD simulations are used as building blocks for mesoscale many-body dissipative particle dynamics (mDPD) modelling. The coarse-grained (CG) mDPD simulations are capable of modelling the rheological behaviour of polymers solutions at spatial-temporal scales relevant to engineering.
The CG modelling framework is able to reproduce the structural characteristics observed at atomistic scale MD. The modelling strategy is able to showcase the non-Newtonian behaviour of oligomers and dilute polymer solutions, demonstrating the sensitivity of the model. Also, the mDPD model is able to distinguish the viscoelastic behaviour of polymers of different chemistries in a solution. Thus, the framework can bridge the information obtained at atomistic levels with the macroscale non-Newtonian behaviour.

An additional objective of the research is to investigate how the presence of the nanoparticles in such polymer solutions impacts the performance of the fluids as heat transfer media. Atomistic scale MD simulations of nanoparticles of different chemistries and shapes dispersed in the polymer solutions are performed. The investigation clearly shows higher thermal conductivities with the addition of nanoparticles. Subsequently, it is found that heat transfer coefficients of nanofluids in the presence of polymer chains are higher than in their absence.
The structural analysis indicates how the underlying interactions of polymer and nanoparticles shrinks the thermal boundary layer, thus assisting heat transfer in laminar flow. The research concludes with an understanding of the capabilities of different nanofluids that can be used for immersive-cooling applications, and a potential to extend the mDPD models to include nanofluids.

Publication Type:	Thesis (Doctoral)
Subjects:	Q Science > QC Physics T Technology > T Technology (General) T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments:	School of Science & Technology > Engineering School of Science & Technology > School of Science & Technology Doctoral Theses Doctoral Theses

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