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Continuum: Projects in progress

Projects in progress

TitleSelect to sort (ascending) Description Research StudentSelect to sort (ascending) Supervisor
Coupling fluid and kinetic codes for laser-driven inertial fusion energy simulations Coupling kinetic solutions of laser-plasma interactions to large-scale fluid simulations will help optimise experiments aimed at achieving thermonuclear fusion driven by lasers. Andrew Angus (Cohort 1) Tony Aber
Investigating the impact of equation of state uncertainties on direct-drive inertial fusion energy simulations Direct-drive inertial fusion energy1 (IFE) requires high-energy lasers to be focussed on a spherical target. The outer material of the target (usually plastic) ablates, driving an implosion of the core deuterium-tritium (DT) fuel. To design efficient future experiments and interpret previous ones an accurate and predictive computational modelling capability is required. This must include a formal understanding of the sources and magnitudes of uncertainty. This project will investigate the uncertainty in direct-drive IFE calculations arising from the equations-of-state used. The primary outcome of the project will be an uncertainty quantification (UQ) framework that could also be applied to other areas of uncertainty, such as opacity, emissivity and thermal transport. Charlotte Rogerson (Cohort 2) Tom Goffrey
Using surrogate models to optimise designs for laser-driven fusion power production Laser-plasma experiments in high-energy density physics (HEDP) and fusion research trigger kinetic scale instabilities whose effects must be included in large-scale fluid simulations. The difference in time and spatial scales between the kinetic and fluid models, along with the cost of the kinetic modelling, have hindered the full inclusion of important kinetic processes in laser-driven fusion simulations. It is critical for the design and interpretation of experiments that this is solved. This project aims to develop a surrogate model for the kinetic processes suitable for including in fluid scale simulations. Ben Gosling (Cohort 3)

Tony Arber, Tom Goffrey and Keith Bennett

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. 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. 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). 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. Oscar Holroyd (Cohort 3) Radu Cimpeanu, Susana N. Gomes
Atomistically-informed continuum interface models for functional composites Functional composites are material candidates for high-energy density applications. Their overall energy density can be enhanced by tailoring constituent dielectric properties, breakdown strength, and interfacial polarisation. Aravinthen Rajkumar (Cohort 1) Lukasz Figiel
Statistics of porous media attributes and mixing processes state variables across scales Typical observations of porous media attributes arise from a variety of techniques which have their own spatial resolution and associated uncertainty. Therefore, key statistics of parameters driving transport processes in porous media vary across scales and a scientific foundation for the characterization of basic transport mechanisms requires understanding of all relevant processes across the relevant length and time scales. In this project, we develop a theoretical and computational framework to assimilate data associated with diverse variables collected at a range of scales and combine these to provide predictions of solute dynamics and associated uncertainties. Alisdair Soppitt (Cohort 2) Mohaddeseh Mousavi-Nezhad
Uncertainty Assessment of Solute Mixing in Heterogenous Porous Media The transport of chemical substances in the subsurface is relevant in many different applications. Matthew Harrison (Cohort 1) Mohaddeseh Mousavi Nezhad