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Fluids

Title Description Status Research Student Supervisor
Adaptive probabilistic meshless methods for evolutionary systems This project will develop and implement a new class of numerical solvers for evolving systems such as interacting fluid-structure flows. To cope with extreme strain rates and large deformations these new solvers will be adaptive and meshless, and they will also implicitly represent their own solution uncertainty, thus enabling optimal design and uncertainty quantification. This exciting project brings together aspects of continuum mechanics, numerical methods for partial differential equations, and statistical machine learning. In Progress Tadashi Matsumoto (Cohort 2) Tim Sullivan
Computational Modelling of Leidenfrost Fractals The Leidenfrost effect levitates small liquid drops above hot surfaces via a strong evaporative flux and is seen when water droplets skate across a hot pan. Understanding when this occurs is critical for the efficiency of numerous technologies, including the spray-cooling of next-generation electronics that our collaborators at Nokia Bell Labs are developing. Experiments at Bell have recently revealed counter-intuitive contact dynamics that display fractal surface wetting in competition with the nanoscale vapour flow under impacting droplets. This project will use unconventional mathematical modelling combined with computational techniques to gain unprecedented insight into this phenomenon combined with theory-driven targeted experiments at Bell. In Progress Peter Lewin-Jones (Cohort 2) James Sprittles
Fluctuating Hydrodynamics for Liquid Spreading over Heterogeneous Surfaces Understanding the spreading of liquids over heterogeneous solid surfaces is the key to numerous emerging technologies (e.g. 3D ‘metaljet’ printing) and biological systems (retention of rain by leaves). In Progress Jingbang Liu (Cohort 1) James Sprittles
Nonlinear, but under control: a hierarchical modelling approach to manipulating liquid films We are surrounded by situations that depend on a controlled outcome in our day-to-day lives, ranging from controlling the evacuation of crowds, to efficient drug delivery, or cooling systems inside computing centres. Most real-life scenarios rely on complicated models which are too complex to tackle analytically or computationally. Using the framework provided by a beautiful and rich physical problem – controlling nonlinear waves in falling liquid films – the project will provide opportunities to develop analytical and computational multi-physics tools. Acting in tandem for the first time, they become sufficiently powerful to translate robust theoretical strategies into realistic technological solutions. Now Filled TBC (Cohort 3) Radu Cimpeanu, Susana N. Gomes
Scale effects on reactive turbulent mixing Spatial and temporal fluctuations in fluid behaviour control mixing and reaction processes. Observations show that velocity fluctuations are correlated with mixing and reaction rates, and degree of these correlations vary across the scale. These provide compelling evidence that the key statistics of reaction parameters driving the transport processes are scale dependent and functions of the increments of porous media geometrical characteristics. This project aims to develope theoretical and computational frameworks to assimilate data associated with diverse variables collected at a range of scales and combine these to provide predictions of reactive solute dynamics and quantify associated uncertainties across the scales. The candidate will benefit from HetSys CDT training on computational data science and geostatistical methods and will perform research in the field of reactive transport and turbulent mixing processes in porous media in collaboration with partners at Bayer A.G. (Germany). Available TBC Mohad Nezhad, Gary Bending, Tim Sullivan