All Projects

A composite likelihood approach to genome-wide data analyses.

Andrew Collins (Investigator), Jane Gibson, Ioannis Politopoulos

We describe composite likelihood-based analysis of a genome-wide breast cancer case-control sample by determining genome regions of fixed size on a linkage disequilibrium map which delimit comparable levels of linkage disequilibrium. Analysis of findings suggests further validation in more samples from other cohorts as well as the exploitation of novel computationally-intensive methods such as next-generation sequencing.

A Fast Multipole Method for the Bessel potential

Marc Molinari, Simon Cox (Investigators), Neil O'Brien

The fast multipole method (FMM) proposed by Greengard and Rokhlin provides a method by which the O(N-squared) many-body problem can be reduced to O(N) complexity. In this project, a multipole method is developed to calculate the energy of a system of vortices in a high temperature superconductor, where the many-body interactions give rise to rich and complex physics. The method developed here is suitable for systems where the interactions are governed by a Bessel potential rather than the usual logarithmic potentials occurring in gravitational and electrostatic problems. We derive and apply vectorised forms of the Gegenbauer addition formulae in order to achieve the O(N) scaling associated with fast multipole methods.

A Fortran Based Mesh Viewer

Gabriel Amine-Eddine (Investigator)

During my final year as an undergraduate, I developed a fully functional software program for visualising geometry, grid and grid quality for a custom developed CFD software tool. It has and now in use in conjunction with the HARTREE CFD code by some of the other fellow postgrads working in my supervisors team.

A habitat suitability model for predicting coral reef distributions in the Galápagos Islands

Terence Dawson (Investigator)

As part of a wider project developing a conservation strategy for the marine environment of the Galapagos Islands, this research used multi-variate modelling techniques to develop a habitat suitability prediction model for coral reefs.

A step toward establishing minimum requirement for CFD modelling of dispersion from floating roof tanks

Zheng-Tong Xie, Ian Castro (Investigators)

It is of great importance to estimate an emission flux (due to leaking from an oil tank) from near field wake, which requires a better understanding of vortex shedding from the tank, in particularly in how the low frequency motion behaves. Large-eddy simulation approaches embedded in up-to-date CFD package will be used for this purpose. This project has a strong link with Concawe and U Surrey.

Adding social ties to the Schelling model

Seth Bullock, Sally Brailsford (Investigators), Elisabeth zu-Erbach-Schoenberg

The Schelling model is an abstract model for segregation in
a spatially arranged population. We extended the traditional model by the addition of a dynamic social network. The social network influences the spatial dynamics of agents moving on the grid by changing the agents’ evaluation of their neighbourhood. In turn, the spatial arrangement influences the change of the social network.

Advanced modelling for two-phase reacting flow

Edward Richardson (Investigator)

Engine designers want computer programs to help them invent ways to use less fuel and produce less pollution. This research aims to provide an accurate and practical model for the injection and combustion of liquid fuel blends.

Aerofoil noise

Richard Sandberg (Investigator)

High-performance computing is used to identify noise sources on aerofoils.

Amorphous Computation, Random Graphs and Complex Biological Networks

Seth Bullock (Investigator)

This interdisciplinary research collaboration arose within the Simple Models of Complex Networks research cluster funded by the EPSRC www.epsrca.ac.uk through the Novel Computation Initiative. Here, leading groups from the Universities of Leeds, Sheffield, Nottingham, Southampton, Royal Holloway and King’s College and industrial partners BT are brought together for the first time to develop novel amorphous computation methods based on the theory of random graphs.

An investigation in to the effects of information provision on driver learning

Ben Waterson, Hans Fangohr (Investigators), James Snowdon

This work aims to better understand and model the role of individual learning and experience on driver route choice. We intend to demonstrate that vehicle-driver agent based models stand alone in being able to capture the complex reciprocal interactions between drivers and their environment, and allow us to incorporate the effects of prior knowledge from previous trips and advice from official information sources and social networks.