Computational Modelling Group

Automated Trading with Performance Weighted Random Forests and Seasonality

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

This project proposes an expert system that uses novel machine learning techniques to predict the price return over these seasonal events, and then uses these predictions to develop a profitable trading strategy.

Care Life Cycle

Seth Bullock, Sally Brailsford, Jason Noble, Jakub Bijak (Investigators), Elisabeth zu-Erbach-Schoenberg, Jason Hilton, Jonathan Gray

This research programme brings together teams of researchers from social sciences, management science and complexity science to develop a suite of models representing the socio-economic and demographic processes and organisations implicated in the UK’s health and social care provision. Integral to the project is working with our partners in the public sector and communicating the results of these models to policymakers allowing them to effectively plan for the future.

Centre for Doctoral Training in Next Generation Computational Modelling

Hans Fangohr, Ian Hawke, Peter Horak (Investigators), Susanne Ufermann Fangohr, Thorsten Wittemeier, Kieran Selvon, Alvaro Perez-Diaz, David Lusher, Ashley Setter, Emanuele Zappia, Hossam Ragheb, Ryan Pepper, Stephen Gow, Jan Kamenik, Paul Chambers, Robert Entwistle, Rory Brown, Joshua Greenhalgh, James Harrison, Jonathon Waters, Ioannis Begleris, Craig Rafter

The £10million Centre for Doctoral Training was launched in November 2013 and is jointly funded by EPSRC, the University of Southampton, and its partners.

The NGCM brings together world-class simulation modelling research activities from across the University of Southampton and hosts a 4-year doctoral training programme that is the first of its kind in the UK.

Challenging Topological Prejudice - Automated Airframe Layout Design

Andras Sobester (Investigator), Paul Chambers

Aircraft preliminary design scopes are drastically narrowed by topological prejudice. Modern aircraft have settled on the same 'tube plus wing and cruciform tail' type topology that has been adopted through their ancestry, with no scientific evidence that this layout is optimal. This research project poses the question:

“Given a topologically flexible aircraft geometry that is free of prejudice or bias, would a sophisticated multi-disciplinary optimization process yield a conventional layout?”

Complexity in Modelling Electric Marine Propulsive Devices

Suleiman Sharkh, Neil Bressloff, Hans Fangohr (Investigators), Aleksander Dubas

This project involves the simulation of turbulent flow around a marine rim-driven thruster and the complex interaction of flow features involved through computational fluid dynamics. Following this, the optimisation of design parameters using computational fluid dynamics to calculate the objective function is performed and surrogate modelling utilised to estimate optimum design configuration.

Continuously Tunable Optical Buffer

Peter Horak (Investigator)

The project aims to design, fabricate and test a novel integrated all-optical buffer device that is based on MEMS technology and provides a continuously tunable delay for optical pulses over a broad wavelength region. Such a device could play a crucial role in future packet-switched optical networks, photonic integrated circuits and coherent light based applications such as optically steered phase array antennas, LIDAR and optical coherence tomography.

This EPSRC funded project is a collaboration between the Optoelectronics Research Centre, Southampton, and University College London.

Coronary Artery Stent Design for Challenging Disease

Neil Bressloff (Investigator), Georgios Ragkousis

In this work, a method has been setup to (i) reconstruct diseased patient specific coronary artery segments; (ii) use the new supercomputer to run many simulations of this complex problem and (iii) assess the degree of stent malapposition. The aim now is to devise a stent delivery system that can mitigate this problem

Deep Optimisation

Jamie Caldwell

The project will develop the implementation and application of a new optimisation technique. 'Deep optimisation' combines deep learning techniques in neural networks with distributed optimisation methods to create a dynamically re-scalable optimisation process. This project will develop this technique to better-understand its capabilities and limitations and develop GPU implementations. The protein structure prediction problem will be used as the main test application.

Fluid Dynamics Optimisation of Rim-Drive Thrusters and Ducted Hydrokinetic Generators

Aleksander Dubas, Suleiman Sharkh (Investigators)

This is a Knowledge Transfer Partnership project is a collaboration between the University of Southampton and TSL Technology Ltd. to develop computational fluid dynamics software design tools for modelling and optimising the design of propeller thrusters and water turbine generators.

Fluid Loads and Motions of Damaged Ships

Dominic Hudson, Ming-yi Tan (Investigators), Christian Wood, James Underwood, Adam Sobey

An area of research currently of interest in the marine industry is the effect of damage on ship structures. Research into the behaviour of damaged ships began in the mid nineties as a result of Ro-Ro disasters (e.g. Estonia in 1994). Due to the way the Estonia sank early research mainly focused on transient behaviour immediately after the damage takes place, the prediction of capsize, and of large lateral motions. Further research efforts, headed by the UK MoD, began following an incident where HMS Nottingham ran aground tearing a 50m hole from bow to bridge, flooding five compartments and almost causing the ship to sink just off Lord Howe Island in 2002. This project intends to answer the following questions:
“For a given amount of underwater damage (e.g. collision or torpedo/mine hit), what will be the progressive damage spread if the ship travels at ‘x’ knots? OR for a given amount of underwater damage, what is the maximum speed at which the ship can travel without causing additional damage?”

Generating Optimal Ensembles of Earth System Models

Simon Cox (Investigator), Elizabeth Hart, Andras Sobester

GENIE is an Earth system model of intermediate complexity. As with other climate models, the tuning of its parameters is essential for providing reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem. The aim of the tuning exercise is to find the optimal values for the free parameters that produce and euqilibrium model end state with the closest fit to equivalent observational data.

Measuring biomolecules - improvements to the spectroscopic ruler

Pavlos Lagoudakis, Tom Brown (Investigators), Jan Junis Rindermann, James Richardson

The spectroscopic ruler is a technique to measure the geometry of biomolecules on the nm scale by labeling them with pairs of fluorescent markers and measuring distance dependent non-radiative energy transfer between them. The remaining uncertainty in the application of the technique originates from the unknown orientation between the optical dipole moments of the fluorescent markers, especially when the molecule undergoes thermal fluctuations in physiological conditions. Recently we introduced a simulation based method for the interpretation of the fluorescence decay dynamics of the markers that allows us to retrieve both the average orientation and the extent of directional fluctuations of the involved dipole moments.

Modelling Macro-Nutrient Release & Fate Resulting from Sediment Resuspension in Shelf Seas

Chris Wood

This study involves adapting a previously-published model to take into account the effect resuspension events (both natural and anthropogenic) may have on nutrient dynamics at the sediment-water interface, and hence produce better estimates for the total nutrient budgets for shelf seas.

Multi-objective design optimisation of coronary stents

Neil Bressloff, Georges Limbert (Investigators), Sanjay Pant

Stents are tubular type scaffolds that are deployed (using an inflatable balloon on a catheter), most commonly to recover the shape of narrowed (diseased) arterial segments. Despite the widespread clinical use of stents in cardiovascular intervention, the presence of such devices can cause adverse responses leading to fatality or to the need for further treatment. The most common unwanted responses of inflammation are in-stent restenosis and thrombosis. Such adverse biological responses in a stented artery are influenced by many factors, including the design of the stent. This project aims at using multi-objective optimisation techniques to find an optimum family of coronary stents which are more resistant to the processes of in-stent restenosis (IR) and stent thrombosis (ST).

OCCASION: Overcoming Capacity Constraints - A Simulation Integrated with Optimisation for Nodes

Tolga Bektas (Investigator)

OCCASION is a collaboration between TRG and the Schools of Mathematics and Management. The project's objective is to identify and investigate innovative methods of increasing the capacity of nodes (i.e. junctions and stations) on the railway network, without substantial investment in additional infrastructure. To this end, a state-of-the-art review of recent and ongoing work in this area will be conducted, followed by the development of tools to (i) assess existing levels of capacity utilisation at nodes, and (ii) investigate options for re-routeing and re-scheduling trains, with a view to reducing capacity utilisation levels. These tools will be used in combination to develop solutions delivering reduced levels of capacity utilisation, and thus increases in capacity and/or service reliability. Incremental changes to existing railway technologies (e.g. improved points) and operating practice (e.g. relaxations of the Rules of the Plan) will be investigated, as will concepts from other modes (e.g. road and air transport) and sectors (e.g. production scheduling).

Optimisation of Acoustic Systems for Perceived Sound Quality

Jordan Cheer (Investigator), Daniel Wallace

Acoustic systems have traditionally been optimised on the basis of minimising an objective acoustic measure, such as sound pressure level. The project investigates the use of subjective measures of sound quality, such as "loudness", "harshness" etc. in optimisation algorithms.

Porous Media and Hydrothermal Circulation in Weakened Ocean Crust

Formation of oceanic crust is an interplay between magma and the cooling hydrothermal system above that its own heat drives. To understand this system we must understand where and how water circulates through the crust.

Ocean crust is riddled with faults and other permeable pathways along which water preferentially flows. We seek to use basic numerical models of circulation in porous media to understand how much of an influence on crust formation these anomalous features have, compared to the bulk, unfractured crust.

Quantum Computation for Signal Detection in Multiple-Input Multiple-Output Communication Systems

Lajos Hanzo (Investigator), Panagiotis Botsinis

Optimal, classic optimization processes in communication systems, such as signal detection, introduce an extremely high computational complexity in the system. Quantum computation offers the optimal equivalent algorithms in the quantum domain, with at least a quadratic degradation in complexity. Since quantum computers have still not been physically realized though, the quantum algorithms' simulation's complexity is higher than that of the optimal classic equivalents. Use of Iridis is essential in facilitating their simulation.

Scalability of Energy Efficient Routing Algorithms in Wireless Sensor Networks

Geoff Merrett (Investigator), Davide Zilli

This project compares two broad classes of routing algorithms for Wireless Sensor Networks, message flooding and single path, by means of a simulation model. In particular, we want to understand how the two scale in terms of energy efficiency on large networks of sensors.

Simulation of biological systems at long length and distance scales

Jonathan Essex (Investigator), Kieran Selvon

This project aims to shed light on cell membrane mechanisms which are difficult to probe experimentally, in particular drug permiation across the cell membrane. If one had a full understanding of the mechanism, drugs could be designed to target particular embedded proteins to improve their efficacy, the viability of nano based medicines and materials could also be assessed, testing for toxicity etc.

Spatially Embedded Complex Systems Engineering

Seth Bullock (Investigator)

SECSE brought together an interdisciplinary team of scientists working on an ambitious three-and-a-half year project titled. The research cluster spanned neuroscience, artificial intelligence, geography, and complex systems in an attempt to understand the role of spatial organization and spatial processes in complex networks within the domains of neural control, geo-information systems and distributed IT systems such as those implicated in air-traffic control.

Structured low-rank approximation

Ivan Markovsky

Today's state-of-the-art methods for data processing are model based. We propose a fundamentally new approach that does not depend on an explicit model representation and can be used for model-free data processing. From a theoretical point of view, the prime advantage of the newly proposed paradigm is conceptual unification of existing methods. From a practical point of view, the proposed paradigm opens new possibilities for development of computational methods for data processing.

Sustainable domain-specific software generation tools for extremely parallel particle-based simulations

Chris-Kriton Skylaris (Investigator)

A range of particle based methods (PBM) are currently used to simulate materials in chemistry, engineering, physics and biophysics. The 4 types of PBM considered directly in the proposed are molecular dynamics (MD), the ONETEP quantum mechanics-based program, discrete element modelling (DEM), and smoothed particle hydrodynamics (SPH).
The overall research objective is to develop a sustainable tool that will deliver, in the future, cutting edge research applicable to applications ranging from dam engineering to atomistic drug design.

The hydrogen abstraction phase of the CYP-cyclohexene reaction, using large-scale DFT

Chris-Kriton Skylaris (Investigator), Chris Pittock, Karl Wilkinson

Studying the hydrogen-abstraction reaction between cyclohexene and the active site of cytochrome P450. This starts a series of reactions that eventually oxidise the small molecule to become either an epoxide or an alcohol.

Understanding the finer detail of this reaction can assist towards a model that will predict the breakdown of drugs in the human body.

The ONETEP project

Chris-Kriton Skylaris (Investigator), Stephen Fox, Chris Pittock, Álvaro Ruiz-Serrano, Jacek Dziedzic

Program for large-scale quantum mechanical simulations of matter from first principles quantum mechanics. Based on theory and algorithms we have developed for linear-scaling density functional theory calculations on parallel computers.

The Perks of Complexity Reduction

Lajos Hanzo (Investigator), Chao Xu

Reliable high-speed modems facilitate ubiquitous communications in our daily lives amongst people and/or machines. The communication technologies we need for the future have to have a high reliability and a low cost. My research aims for reducing the complexity of state-of-the-art communication systems, so that they can communicate in real time at an increased throughput. Naturally having access to parallel computers such as Iridis gives my research a competitive advantage over other researchers, relying on slower simulations.

The use of channel wings for slow speed UAV flight

Andy Keane (Investigator), Juraj Mihalik

In this project, advanced computational modeling and robust design optimization tools are used to observe the possibility of use of the Custer channel wings for slow speed UAV flights.

Today's Computation Enabling Tomorrow's Seamless Communication

Lajos Hanzo (Investigator), Varghese Thomas

Radio Over Fibre (ROF) is a communication technique that aims to gainfully amalgamate the benefits of optical and wireless communication, while keeping the system cost low. This technique would support the next generation of wireless services.

Validation of a spatial-temporal soil water movement and plant water uptake model

Tiina Roose, Sevil Payvandi (Investigators), James Heppell

We develop a model that estimates the water saturation level within the soil at different depths, and the uptake of water by the root system. Data from Smethurst et al (2012) is used to validate our model and obtain a fully calibrated system for plant water uptake. When compared quantitatively to other models such as CROPWAT, our model achieves a better fit to the experimental data because of the simpler, first, second and third order terms present in the boundary condition, as opposed to complicated non-linear functions.

Variability in high pressure blade trailing edge geometry and its impact on stage capacity and blade temperature

Andy Keane (Investigator), Jan Kamenik

My project involves the trailing edge (TE) geometry of gas turbine high pressure turbine blades, which is subject to inevitable variability due to the manufacturing processes involved.