Fluid Dynamics - understanding fluid dynamics to improve our lives

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The addition of small concentrations of high-molecular-weight polymers to particle-laden flows to separate non-settling fine solids from aqueous suspensions is a promising method to instigate settling. This is of invaluable use in nuclear waste processing, where management of multiphase sludge waste is critical to on-going operations which aim to transport aggregated waste to interim storage facilities. It is also of relevance to the minerals industry and in general water treatment applications. This project aims to investigate the underpinning polymer-particle adsorption and subsequent flocculation dynamics using numerical simulation. Nonequilibrium Langevin dynamics and the finitely-extensible nonlinear elastic (FENE) dumbbell model will be used to predict the interaction of polymers with simulated nuclear waste material, modelled as fully-resolved particles. Relevant flow conditions such as shear and isotropic turbulence will be predicted using the high-accuracy technique, direct numerical simulation. Machine learning will also be used to augment the predictive capabilities and to limit the number of high computational cost simulations required. A full mechanistic understanding of the particle-polymer systems will help inform safe industrial practice in ongoing nuclear operations and improve the efficiency of filtration and settling processes.