Projects
Please note that the PhD projects listed are examples of projects offered to current CDT students and as such are not generally available to prospective students.
Fig. 1. Showcasing Wetropolis at the Global Flood Partnership meeting, Sept. 2022, Leeds. Organised by Mark Trigg et al. See also: https://www.youtube.com/watch?v=rNgEqWdafKk The Wetropolis flood demonstrator visualises extreme flooding events and inspired a flood-mitigation cost-effectiveness tool. While Wetropolis’ weather is straightforward, the resultant probability distribution of flooding events in the city is a complex spatial-temporal…
Water-Energy Nexus in Air Entrained Pressurised Pipelines and Air Control/Removal Strategies
The water sector is facing crucial challenges because of climate change and population growth, compromising serviceability. The demand for water and energy is expected to respectively increase by 55 and 80 per cent by 2050. Special considerations of the water-energy nexus are required in the design and operation of water systems. The conveyance capacity of…
The future of the jet stream and role for extreme European weather
Most winter weather extremes in the UK and Europe are driven by the North Atlantic jet stream – a belt of strong winds encircling the globe several kilometres above Earth’s surface. For example, the “Beast from the East” that brought severe wintry weather to the UK in February 2018 was associated with a disrupted jet…
Surrogate-based optimisation for fluid dynamic (FSI) systems” in the theme “underpinning methods in fluid dynamics
This project aims to develop cutting edge numerical methods for optimisation of design and control in fluid-structure interaction systems, with application to understanding of C. elegans locomotion through optimising its biomechanical parameters such as the muscle force distribution. Reconstruction of C. elegans locomotion based upon its centreline data from laboratory
Rock vapor dynamics in the envelopes of young exoplanets
We now know that while most stars host planets, their planetary systems are quite unlike our own and their formation histories were likely different to that of the Earth. A key difference is that most planets were already able to capture a significant hydrogen envelope long before they grew to their final sizes (a few…
Real-time control and validation of a novel rogue wave-energy device
In August 2013, preliminary tests were undertaken in which a working proof-of-principle was established of the novel wave-energy device, in a 1.2m by 0.2m x 0.2m tank, with a wavemaker, a wave-activated buoy moving in the vertical, and by using deconstructed Faraday/shaking lights to create a linear direct-drive generator. The experiments were built and set-up…
Rapid haemodynamic analysis of native and prosthetic heart valves using physics-informed machine learning
The project aims to create rapid and scalable deep learning-based simulation techniques for fluid-structure interaction analysis of native and prosthetic aortic valves. Such tools can enable prediction of the haemodynamic behaviour before and after implants, which is governed by complex interaction of the blood flow and valves themselves. FSI analyses, such as in Fig 1,…
Predictive modelling of nucleate boiling in impacting droplets for high heat flux spray cooling applications
This project seeks to overcome current obstacles to predictive modelling of nucleate boiling in droplets impacting on realistic non-uniform heated surfaces. The key development will be a novel coupling of a mesoscopic lattice Boltzmann method, capable of capturing the incipience of boiling without artificial seed bubbles, together with OpenFOAM-based Navier-Stokes simulations of macroscopic droplet dynamics….
Predicting Friction of Total Joint Replacement Bearings
Total joint replacements and the associated orthopaedic technologies are a significant contributor to the needs of a healthy nation and are expected to grow in importance worldwide over the next decade. To reduce this increasing economic burden implants need to be designed so that they function optimally within the body over many millions of load…
Physics-informed deep learning and field experiments for dynamic reactive fluids (carbon, nutrients and water flow) in agricultural soils
Artificial Intelligence have attracted considerable attention from researchers in environmental fluid dynamics over the last decade, especially Artificial Neural Networks (ANN) which can provide a flexible mathematical structure capable of identifying complex nonlinear relationships between input and output data sets. However, traditionally, ANNs have been trained using input and output datasets with simple loss functions,…
Physics informed machine learning applied to geothermal energy
Decarbonising space heating is a central focus of the UK’s goal to attain net zero emissions by 2050. One promising source of zero-carbon heat is geothermal energy derived from water-stored energy in abandoned mines, that is particularly applicable in areas such as Leeds with a large number of abandoned mining works. This project seeks to…
Numerical Simulation of Polymer-Particle Adsorption and Flocculation Dynamics for Nuclear Waste Separations
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…
Nonlinear interactions between fluid flows inside and outside of sea ice
Arctic sea ice influences the Earth’s radiation budget through its relatively large albedo, and thus plays an important role in the Earth’s climate system. Hence, predicting changes in the ice cover is crucial to the study of Earth’s climate. The ice-ocean interactions have a controlling effect on the evolution of the ice cover, and the…
Mixed precision, approximate computing, and data compression for computational fluid dynamics
Figure 1: (a) NVIDIA A100 (source: https://www.nvidia.com/en-gb/data-center/a100/). (b) Turbulent flow simulations using GPUs and LBM-based CFD Computer hardware is changing noticeably at the fundamental, computer arithmetic level in the last decade. Graphical processing units (GPUs) and some CPUs increasingly started introducing 16-and 8-bit hardware for computing mathematical operations, which work in parallel with classical 32-and…
Methods for Observing Atmospheric Turbulence with Uncrewed Aerial Systems (UAS)
The planetary boundary layer (the first 1–2 km above the surface) is the most dynamic and turbulent layer of Earth’s atmosphere, contributing the greatest uncertainty to weather forecasting. However, the current global meteorological observing system severely lacks coverage above the ground—inhibiting predictability. New measurement technologies in the form of un-crewed aerial vehicles or ‘drones’ are…
Machine learning (ML)-based intelligent CFD simulation for interactive design exploration of built environments
Understanding the effect of airflow in indoor environments is of great interest due to its close relationship to occupant’s safety, thermal comfort, energy and infection risk. In hospitals, airflow can distribute pathogens and can pose a significant health hazard. Indoor airflow patterns can be very complicated, and computer simulations are an invaluable tool for understanding…
Large-scale Airflow Mapping with Un-crewed Aerial Systems (UAS)
Several industries require airflow characterisation around large objects for safety and engineering purposes, such as construction/architecture, aviation, wind energy, and air quality. Despite CFD advances, physical experimentation must often occur. Large-scale characterisation (wind turbines, airports, urban areas) relies on either laboratory analogues (cost scales exponentially with complexity) or fixed observations (laborious to install and only…
Laminar Drag Reduction and Anti-fouling Behaviour of Biomimetic Nanostructured Surfaces
Surface of most natural plant leaves, animal skins and insect bodies are covered by ordered micro- and nanoscale structures with various morphologies. Understanding the performance of these functional surfaces and their synthetic mimics in dynamic flow conditions yet remains an open challenging question as it lies at the interface of multiple scientific disciplines. This project…
Investigating the effects of climate change on High Speed Rail using CFD
High speed rail is a sustainable mode of transport that has the potential to help meet global ‘net zero’ targets. However, although train movement is energy efficient and emits low emissions, the resulting deterioration and replacement of the supporting railway track granular materials is carbon intensive (160% greater than operations). This is becoming increasingly important…
Interaction of topography with rotation, convection and magnetic fields
Understanding convection is important in a range of geophysical problems. For example, in the interior of the Earth in the fluid outer core or in the Earth’s atmosphere convection is responsible for a range of turbulent phenomena (including the driving of large-scale flows). Often the convection is on large scales, so the effects of rotation…
Image-based modelling of placental blood flow with a focus on fetal growth restriction
The placenta is the interface between mother and fetus and undergoes vascular changes and differentiation to maintain effective blood flow circulation to ensure a healthy pregnancy. Gas and nutrient exchange occur within the placental capillaries. Impaired placental blood flow can result in fetal growth restriction (FGR), where the baby does not meet its growth potential,…
How sustainable is geothermal in the UK: getting a measure of fluid and heat flow in Yorkshire’s aquifers
This project combines mathematical/computational modelling with geological and geophysical parameters to explore fluid and heat flow capacities of potential future geothermal reservoirs within UK aquifers. Using Yorkshire’s aquifers as a focus, the project will examine the relationship between the micro-scale material properties of aquifer rocks and the likely fluid and heat output, recharge and sustainability…
Hardware agnostic multi-layer abstraction based solver for Computational Fluid Dynamics (CFD)
Computational scientists are typically not expert programmers and thus have to work with easy to use programming languages. However, they have very high-performance requirements due to their experimental setup and large datasets and have to rely on parallel computing machines for tasks like simulation runs. Unfortunately, the increasing specialisation and complexity in computing hardware have…
Fluid dynamics modelling of thrombus formation and endovascular treatment of brain aneurysms
A brain aneurysm is a life-threatening vascular distension routinely treated upon discovery. Common treatments for aneurysms involve a stent or a coil that aims to redirect blood flow away from the aneurysm. This triggers blood clotting and causes the aneurysm to heal and eliminates it from circulation. Clot formation in human blood is complex, and…
Flexible Multi-Disciplinary Design Optimisation of Next Generation Commercial Aircraft Using Open-Source Methods and Tools
The next generation of commercial aircraft must meet exceptionally challenging design requirements including the use of hydrogen and/or electric powered jet engines to deliver on the emissions dedications of current government policies and ensure the long-term sustainability of accessible flight. This project will deliver a flexible multidisciplinary design optimisation framework for a conventional passenger aircraft…
Extreme value theory and Quantitative Poincare recurrence in fluid mixing problems
The importance and relevance of fluid mixing in modern science is clear, both from the range of industrial and environmental situations in which it appears, and from the explosion of research articles connected with mixing by chaotic advection that have appeared in the last thirty years. Similarly well-established is extreme value theory (EVT) – the…
Extreme tidal interactions between stars, planets and black holes
Tides between astrophysical fluid objects are ubiquitous in astrophysics, from planets orbiting their host stars to stars orbiting supermassive black holes in galaxy centres. In many cases the tidal forces can become extreme and comparable to the self-gravitational force holding the celestial body together resulting in its disruption. This can occur when a planet migrates…
Dynamical systems and Machine Learning approach to mixing and dispersion of airborne viruses in indoor environments
Understanding the effect of airflow in enclosed/indoor environments is of great interest due to its close relationship to occupant’s health, thermal comfort, and energy efficiency. Optimally designed ventilation could result in increased comfort and reduced health risk of the occupants. Airflow indoors can distribute pathogen-laden aerosols and can pose a significant health hazard. Furthermore, indoor…
Distribution of microbial pathogens into aerosol and the implications for airborne infection transmission
Airborne transmission of infection relies on microorganisms within the human respiratory system to be released in aerosols that are small enough to remain airborne and to be inhaled by a susceptible person. Current transmission models use a microbial source which includes a size distribution of particles but assumes distribution of microorganisms is uniform by volume….
Developing mathematical models to incorporate microstructural heterogeneities into viscous flow
This project will address fundamental aspects of viscous flow arising from the evolution of a complex microstructure in the material, eventually informing efforts to predict the evolution of the Earth’s ice sheets in a changing climate, and the effects of the Earths’ interior which governs the movement of tectonic plates, each problems of considerable societal…
Design of controlled-release drugs using image-based modelling and machine learning
Controlled-release tablets are manufactured to dissolve slowly and release active ingredients at a predictable rate so they can sustain a small amount of medication into a patient’s system over an extended period. Such systems give physicians better control over the patient’s health. However, designing a micro-structure that guarantees such controlled release is subject to uncertainty…
Coupled flow-growth models for recovery and reduction of energy from wastewater processes
Wastewater treatment processes have high energy costs and are challenging to optimise due to the complex coupled processes occurring. Over 10 billion litres of sewage are produced every day in England and Wales; taking over 6.3 gigawatt–hours of energy to treat (~1% of the average daily electricity consumption). Many of the processes take place within…
Blind estimation of the arterial input function in MRI to model fluid transport in tissues and tumours
Measurement of tissue blood flow (perfusion) and related fluid transport parameters using contrast-enhanced MRI is a valuable technique in the clinic, but these parameters are difficult to quantify without knowing the concentration of the contrast agent in the arterial blood (the arterial input function, AIF). There have been many approaches described to estimate the AIF…
Aerodynamic design and analysis of a hyperloop vehicle
Hyperloop is a newly proposed mode of transportation where vehicles move within a tube held at vacuum-type conditions at speeds of up to 1200km/h. Currently, the most well-known embodiment of Hyperloop is that proposed by Elon Musk in 2013, and presents a step-change in transport engineering, allowing people to move vast distances in short periods…
Accessing the rapidly rotation regime of convection and magnetic field generation in planetary interiors
This project involves the investigation of the mechanisms that lead to reversals of the Earth’s magnetic field. As shown in the figure below, the polarity of the Earth’s field reverses rarely, making modelling difficult. In this project we use the latest advances in “rare event” modelling to construct descriptions of the processes that lead to…