Computational Modelling Group

Transdisciplinary tags

Categories within this topic include Complex Systems (128), Computational Social Science (4), Computer Science (39), Crowdsourcing (1), Data Science (4), Demand Response (1), Design (11), Digital Economy (2), Digital Humanities (3), e-Research (7), Economics (8), Education (2), HPC (49), IfLS (6), Medicine (4), NGCM (35), Quantitative Biology (9), Scientific Computing (83), Software Engineering (25), Visualisation (14)

All Projects

A Connected Island: how the Iron Curtain affected Archaeologists in Central Europe

Iza Romanowska

Using citation network analysis this project aims to investigate the effects that the Cold War had on researchers on both sides of the Iron Curtain.

A Mathematical Analysis of the Driving Force of Perivascular Drainage in the Brain

Giles Richardson, Roxana-Octavia Carare (Investigators), Alexandra Diem

The observation that solute drainage in the brain occurs in the reverse direction of the blood flow has for a long time been puzzling for researchers. We developed a simple analytical model that can explain this reverse drainage of solutes and has potential implications for the development of treatment for Alzheimer's Disease.

A novel approach to analysing fixed points in complex systems

James Dyke (Investigator), Iain Weaver

This work aims to contribute to our understanding of the relationship between complexity and stability. By describing an abstract coupled life-environment model, we are able to employ novel analytical, and computational techniques to shed light on the properties of such a system.

A novel method for monitoring air pollution from satellites at very high resolution

Joanna Nield, Jason Noble, Edward Milton (Investigators), Robin Wilson

Developing methods to monitor the clarity of the atmosphere from satellites at 100,000 times the resolution of previous methods. This can then be used to monitor air pollution, correct satellite images and provide data for climate studies. Simulation is used to model the effects of atmospheric pollution on light passing through the atmosphere, and to test the method under 'synthetic atmospheres'.

A spatially-explicit agent-based model of jaguar population dynamics

Jason Noble, Patrick Doncaster (Investigators), Angela Watkins

A single species spatially-explicit agent-based model has been developed that illustrates the role of simulation modelling, integrated with an adapted least-cost modelling approach and real-world geographical data, in exploring jaguar population dynamics.

Ab initio simulations of chemical reactions on platinum nanoparticles

Chris-Kriton Skylaris (Investigator), Álvaro Ruiz-Serrano, Peter Cherry

•Use first principles calculations to study the relationship between shape and size of nanoparticle and the oxygen adsorption energy.

• Investigate the effect of high oxygen coverage on the catalytic activity of the nanoparticles.

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.

Advanced simulation tools for prediction of flash-back in hydrogen-rich gas turbine combustion

Edward Richardson (Investigator), James Bailey

The project involves the numerical simulation of hydrogen-rich flows using Direct Numerical Simulation (DNS) and Large Eddy simulations. Hydrogen rich fuels offer the opportunity to reduce the carbon intensity of energy supply. Hydrogen-rich fuels and other low-carbon energy sources are expect to become increasingly important in this regard. Hydrogen is more reactive and diffusive than conventional hydrocarbon fuels requiring advanced computational methods to optimise the use of these fuels in gas turbines.

Aerofoil noise

Richard Sandberg (Investigator)

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

Agent-Based Modelling of High Frequency Traders

Frank McGroarty, Enrico Gerding (Investigators), Alvaro Perez-Diaz

Agent-Based Modelling of High Frequency Traders

Agent-based simulations of jaguar movements through conservation corridors

Jason Noble, Patrick Doncaster (Investigators), Angela Watkins

We present an agent-based model of jaguars (Panthera onca),
scaled for fragmented habitat in Belize where proposals already exist for creating a jaguar corridor. We use a least cost approach to simulate movement paths through alternative possible landscapes.

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 Evolutionary Economic Approach to the Household?

Jason Hilton

The household is a fundamental societal unit. In a huge array of contexts, our understanding of social behaviour relies on an interpretation of how decision are taken at the household level.This work aims to model individual decision-making and interactions between individuals explicitly within the framework of agent-based modelling, following the work of Potts (2000). Potts describes how economic problems can better be dealt with by considering how agents with incomplete, evolving preferences in the form of decision rules interact on a network, and how they cooperate and form ties to produce combinatorial technologies. Following the work of Gary Becker, he then considers how this ostensibly economic framework might hypothetically describe partnership search and household formation and dissolution.

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.

An Investigation into the Cascade Effect of Mergers on the Global Financial Markets

Seth Bullock, Antonella Ianni (Investigators), Camillia Zedan

An investigation into the external effects that horizontal mergers have on the interconnected global markets.

Antimicrobial Peptide and E. coli Membrane Interactions

Syma Khalid (Investigator), Thomas Piggot, Nils Berglund

Antimicrobial peptides (AMPs) are known to disrupt the membranes of bacterial cells such as E. coli. I work on investigating the nature of these interactions using molecular dynamics (MD) simulations.

Application of RNA-Seq for gene fusion identification in blood cancers

William Tapper (Investigator), Marcin Knut

Gene fusions are often the cause of different blood cancers. As such, accurate identification of them provides information on the underlying cause of a cancer, ensuring appropriate choice of treatment. However, due to shortcomings of the currently applied methods for gene fusion identification, some of them escape undetected. We are employing RNA-Seq, a cutting-edge method for sequencing RNA, the messenger of genetic information, to investigate gene fusions.

Associative learning in ecosystems: Network level adaptation as an emergent propery of local selection

Richard Watson, James Dyke (Investigators), Daniel Power

Ecosystems may exhibit collective adaptive properties that arise from natural selection operating on their component species. These properties include the ability of the ecosystem to return to specific configurations of species, in a manner highly analogous to mechanisms of associative learning in neural networks.

Atlantic ocean meridional heat transport at 26oN: Impact on subtropical ocean heat content variability

Robert Marsh (Investigator), Maike Sonnewald

Local climate is significantly affected by changes in the oceanic heat content on a range of timescales. This variability is driven by heat fluxes from both the atmosphere and the ocean. In the Atlantic the meridional overturning circulation is the main contributor to the oceanic meridional heat transport for latitudes south of about 50◦ N. The RAPID project has been successfully monitoring the Atlantic meridional overturning at 26◦ N since 2004. This study demonstrates how this data can be used to estimate the basin-wide ocean heat content in the upper 800 m between 26◦ N to 36◦ N. Traditionally the atmosphere is seen to dominate the ocean heat content variability. However, previous studies have looked at smaller areas in the Gulf Stream region, finding that the ocean dominates deseasoned fluctuations of ocean heat content, while studies of the whole North Atlantic region suggest that the atmosphere may be dominant. In our study we use a box-model to investigate fluctuations of the ocean heat content in the subtropical North Atlantic between 26◦ N and 36◦ N. The box-model approach is validated using 19 years of high resolution GCM data. We find that in both the GCM and RAPID based data the ocean heat transport dominates the deseasoned heat content variability, while the atmosphere’s impact on the heat content evolution stabilizes after 6 months. We demonstrate that the utility of the RAPID data goes beyond monitoring the overturning circulation at 26◦ N, and that it can be used to better understand the causes of ocean heat content variability in the North Atlantic. We illustrate this for a recent decrease in ocean heat content which was observed in the North Atlantic in 2009 and 2010. Our results suggest that most of this ocean heat content reduction can be explained by a reduction of the meridional ocean heat transport during this period.

Automated Algorithmic Trading with Intelligent Execution

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

In this project, we introduce the first fully automated trading system for real-world stock trading that uses time-adaptive execution algorithm to minimise market impact while increasing profitability com- pared to benchmark strategies.

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.

Automatic Image Retrieval with Soft Biometrics for Surveillance

Mark Nixon, John Carter (Investigators), Daniel Martinho-Corbishley

We're investigating ways to automatically describe and identify pedestrians from surveillance footage using human understandable, soft biometric labels. Our goal is to enable surveillance operators to search for pedestrians in a video network using soft biometric descriptions, and to automatically retrieve these descriptions from CCTV images.

B-meson coupling with relativistic heavy quarks

Jonathan Flynn (Investigator), Ben Samways, Dirk Broemmel, Patrick Fritzsch

We non-perturbatively compute the coupling between B* and B pi meson states relying on relativistic heavy quarks and domain wall light fermions. The coupling is of importance for an effective description of hadronic heavy meson decays.

Bayesian Agents as Models for the Disclosure Behaviour of Pregnant Drinkers

Seth Bullock, Jakub Bijak (Investigators), Jonathan Gray

Examining the feasibility of signalling games, played by Bayesian decision theoretic agents as a model for the disclosure of drinking behaviour by pregnant women to their midwives.

Bioclimatic Architecture

Seth Bullock (Investigator), Nicholas Hill

This was a review report on bioclimatic architecture and how such architecture may be designed by agent-based models inspired by the building behaviour of insects.

BioSimGrid

Jonathan Essex, Hans Fangohr (Investigators), Richard Boardman, Syma Khalid, Steven Johnston

The aim of the BioSimGrid project is to make the results of large-scale computer simulations of biomolecules more accessible to the biological community. Such simulations of the motions of proteins are a key component in understanding how the structure of a protein is related to its dynamic function.

Body Forces in Particle Suspensions in Turbulence

Gabriel Amine-Eddine (Investigator), John Shrimpton

The behaviour of multiphase flows is of primary importance in many engineering applications. In the past, experimental observations have provided many researchers with the ability to understand and probe the phenomena and physical processes occurring in such flows. With advancements in modern day computational power, we now have the ability to gain an even greater wealth of knowledge, from what used to be a physical experiment, is now a virtual simulation.

Amine-Eddine, G.H. (2015) Body forces in particle suspensions in turbulence. University of Southampton, Faculty of Engineering and the Environment, Doctoral Thesis , 283pp.

Can the principle of Maximum Entropy Production be used to predict the steady states of a Rayleigh-Bernard convective system?

Kevin Oliver, Iain Weaver, James Dyke (Investigators)

The principle of Maximum Entropy Production (MEP) has been successfully used to reproduce the steady states of a range of non-equilibrium systems. Here we investigate MEP and maximum heat flux extremum principles directly via the simulation of a Rayleigh-Bérnard convective system implemented as a lattice gas model.

Can we calculate the pKa of new drugs, based on their structure alone?

Chris-Kriton Skylaris (Investigator), Chris Pittock, Jacek Dziedzic

The pKa of an active compound in a pharmaceutical drug affects how it is absorbed and distributed around the human body. While there are various computational methods to predict pKa using only molecular structure data, these tend to be specialised to only one class of drug - we aim to generate a more generalised prediction method using quantum mechanics.

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.

Cellular Automata Modelling of Membrane Formation and Protocell Evolution

Seth Bullock (Investigator), Stuart Bartlett

We simulated the meso-level behaviour of lipid-like particles in a range of chemical and physical environments. Self-organised protocellular structures can be shown to emerge spontaneously in systems with random, homogeneous initial conditions. Introducing an additional 'toxic' particle species and an associated set of synthesis reactions produced a new set of ecological behaviours compared to the original model of Ono and Ikegami.

Census 2022: Transforming Small Area Socio-Economic Indicators through Big Data

Patrick James, Ben Anderson (Investigators)

One of only 20 to be funded under the ESRC’s new ‘Transformative Social Science’ programme, this project will explore the feasibility of estimating small area (neighbourhood) census-like statistics from transactional ‘big data’ including large scale fine grained temporal energy monitoring data held by the Energy & Climate Change Division (FEE).

Centre for Doctoral Training in Next Generation Computational Modelling

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

Chaotic Analysis of Partial Discharge

Paul Lewin (Investigator), Lyuboslav Petrov

The deterministic character of PD pulses predicted by theory has been shown to be existent for certain PD events. Finding characteristic patterns in phase space enables field-data PD detection with high reliability.

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.

Computational Fluid Dynamics of Compressor Blades Within a Gas Turbine Engine (HiPSTAR)

Richard Sandberg (Investigator), John Leggett

As modern engines become more and more efficient, the importance of understanding the finer details of the physics involved grows, if further gains are to be achieved. In such harsh enviroments, such as within a gas turbine engine, there are few means of studying them physicaly and we are left with little choice but to use super computers to model the flow.

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.

Controlling Ant-Based Construction

Seth Bullock (Investigator), Lenka Pitonakova

This paper investigates dynamics of ant nest building and shows that algorithms capable of generating ant-like structures can also be used to create nests, shapes of which are imposed from outside of the system.

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

Cosmological evolution of supermassive black holes in the centres of galaxies

Anna Kapinska (Investigator)

Radio galaxies and quasars are among the largest and most powerful single objects known and are believed to have had a significant impact on the evolving Universe and its large-scale structure. Their jets inject a significant amount of energy into the surrounding medium, hence they can provide useful information in the study of the density and evolution of the intergalactic and intracluster medium. The jet activity is also believed to regulate the growth of massive galaxies via the AGN feedback. In this project, through the use of numerical simulations, I explore the intrinsic and extrinsic physical properties of the population of Fanaroff-Riley II (FR II) objects, i.e. their kinetic luminosities, lifetimes, and central densities of their environments. This allows one to investigate evolution of these radio sources across cosmic time, and to discuss the significance of the impact of these sources on the evolving Universe.

Coupled multi-scale simulation of high Reynolds number airfoil flows

Neil Sandham, Nicola De Tullio (Investigators), David Lusher

Application of multi-scale nested direct numerical simulations to high Reynolds number aerofoil flows.

CRISIS – Complexity Research Initiative for Systemic InstabilitieS

Frank McGroarty (Investigator), Bob De Caux

A new approach to modelling and understanding financial system and macroeconomic risk and instability

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.

Design of Unmanned Air Vehicles

James Scanlan (Investigator), Robert Entwistle

Using computational modelling of a 3D airspace simulation environment to meet the safety and collision-avoidance requirements of the certification authorities.

Developing mathematical tools to identify the genes underlying disease

Andrew Collins (Investigator), Alejandra Vergara Lope

This PhD project uses a Monte Carlo molecular simulation processes approach to predict which genes are involved in the development of different diseases.

Developing programming skills with Minecraft and Python

Hans Fangohr (Investigator), Alvaro Perez-Diaz

PythonTool is a Minecraft mod created for this project which allows interactive execution of Python scripts which interact with the game in real time. It intends to make teaching programming to children or non-expert users easier and more appealing.

Development of a novel Navier-Stokes solver (HiPSTAR)

Richard Sandberg (Investigator)

Development of a highly efficient Navier-Stokes solver for HPC.

Development of wide-ranging functionality in ONETEP

Chris-Kriton Skylaris (Investigator), Jacek Dziedzic

ONETEP is at the cutting edge of developments in first principles calculations. However, while the fundamental difficulties of performing accurate first-principles calculations with linear-scaling cost have been solved, only a small core of functionality is currently available in ONETEP which prevents its wide application. In this collaborative project between three Universities, the original developers of ONETEP will lead an ambitious workplan whereby the functionality of the code will be rapidly and significantly enriched.

Differences between sexual genetic algorithms and a compositional cooperative co-evolutionary algorithm

Richard Watson (Investigator), Daniel Power

Different algorithms are representative of different genetic processes. This work explores how algorithms representing sexual recombination can solve certain problems that hill climbers cannot.

DIPLOS - Dispersion of Localised Releases in a Street Network

Trevor Thomas, Ian Castro (Investigators)

The security threat level from international terrorism, introduced by the UK Security Service, has been classified as either "severe" or "critical" for much of its six-year history, and currently remains as "substantial" (source: MI5 website). Part of the risk posed by terrorist threats involves potential releases of air-borne chemical, biological, radiological or nuclear (CBRN) material into highly populated urbanised areas. Smoke from industrial accidents within or in the vicinity of urban areas also pose risks to health and can cause widespread disruption to businesses, public services and residents. The Buncefield depot fire of 2005 resulted in the evacuation of hundreds of homes and closure of more than 200 schools and public buildings for two days; consequences would have been much more severe if prevailing meteorological conditions had promoted mixing or entrainment of the smoke plume into the urban canopy. In both these scenarios it is crucial to be able to model, quickly and reliably, dispersion from localised sources through an urban street network in the short range, where the threat to human health is greatest. However, this is precisely where current operational models are least reliable because our understanding and ability to model short-range dispersion processes is limited. The contribution that DIPLOS will make is:

1. to fill in the gaps in fundamental knowledge and understanding of key dispersion processes,
2. to enable these processes to be parametrized for use in operational models,
3. to implement them into an operational model, evaluate the improvement and apply the model to a case study in central London

Most of the existing research on urban dispersion has focused on air quality aspects, with sources being extensive and distributed in space. Scientifically, this research is novel in focusing on localized releases within urban areas, and on dispersion processes at short range. Through a combination of fundamental studies using wind tunnel experiments and high resolution supercomputer simulations, extensive data analysis and development of theoretical and numerical models, DIPLOS will contribute to addressing this difficult and important problem from both a scientific research and a practical, operational perspective.

Dipole moment and theoretical spectroscopy: a computational approach

Chris-Kriton Skylaris (Investigator), Valerio Vitale

The present project represents a first step towards the implementation of a new technique to calculate the whole vibrational spectra of molecules in a formally exact way, which fully takes into account anharmonicity and conformational transitions, at a finite temperature, both in gas phase and in solution in a single ab initio molecular dynamics simulation.

Direct Numerical Simulations of transsonic turbine tip gap flow

Richard Sandberg (Investigator)

Direct Numerical Simulations are conducted of the transsonic flow through the tip gap at real engine conditions.

Directing magnetic skyrmion traffic flow with nanoscale patterning.

Hans Fangohr, Ondrej Hovorka (Investigators), Mark Vousden

Skyrmions in magnetic nanostructures may lead to new data storage technologies. Appropriate simulation methodologies are developed and applied.

Dispersion of Small Inertial Particles in Characteristic Atmospheric Boundary Layer Flows

John Shrimpton, Zheng-Tong Xie (Investigators), Thorsten Wittemeier

This project aims at improving the near-field accuracy of short term predictions of the dispersion of particulate matter in the atmospheric boundary layer. For this purpose a variety of LES and DNS modelling approaches is used.

Do the adaptive dynamics of host-parasite systems catalyse or constrain sympatric speciation?

Richard Watson (Investigator), Daniel Power

Coevolutionary dynamics affect both parties evolutionary trajectories. When might these affect speciation? This project uses a simulation model to explore the issue.

Dual resolution simulations of lipid membrane systems

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 this mechanism, drugs could be designed to easily cross the membrane, or target particular embedded proteins to improve their efficacy. A reliable and robust computational method to asses a molecules permeability would be invaluable in the field of drug design, we seek to perfect such a method.

Dynamag: computational magnonics

Hans Fangohr, Atul Bhaskar (Investigators), Matteo Franchin, Andreas Knittel

Analytical treatment of long range magneto-dipole interactions is a bottle-neck of magnonics and more generally of the theory of spin waves in non-uniform media. This project develops a theoretical framework for analysis of magnonic phenomena in magnetic nano-structures, including isolated nano-elements, arrays of those, and extended magnonic crystals. The DYNAMAG project is funded by the EU FP7 and the DST of India.

Dynamics of interacting magnetic nanoparticles

Thomas Fischbacher (Investigator), Maximilian Albert

The project aims at extending the micromagnetic simulation framework 'nmag' developed at the University of Southampton to enable it to handle dynamic geometries. The extended framework will then be used to study systems such as interacting magnetic nanoparticles.

Dynamics simulations for quantum feedback to steer a single-particle harmonic oscillator in non-classical states

Hendrik Ulbricht (Investigator), Ashley Setter

This PhD project is about using digital electronics to implement a parametric feedback loop to modulate the intensity of an optical trapping laser in order to stabilise/cool the centre of mass motion of a nanoparticle. It is then intended we use digital parametric feedback to drive the motion of the particle, which is essentially a quantum harmonic oscillator, into non-classical quantum states such as squeezed and number states.

Early warning signals in climate data

Kevin Oliver, James Dyke (Investigators), Maike Sonnewald

Paleoclimatic records reveal that the Earth’s climate system has undergone sharp transitions between
states. Much work has recently been devoted to assessing how likely the current climate is to undergo such a sharp transition. This is motivated by the severe socioeconomic consequences such dramatic changes would entail. Thus, predicting iminent transitions would be very valuable. This review provides an overview of two promising techniques which could potentially be used to assess the stability of components of the climate system. These techniques are degenerate fingerprinting and detrended fluctuation analysis (DFA). It is found that degenerate fingerprinting is more widely used, but that DFA could be more suitable. DFA allows for memory in the time-series, and can give better results with less data. However, the DFA technique is best suited for systems close to the transitions, and relies on calibration with the degenerate fingerprinting technique further from the transition. Applying these techniques to forecast transitions is unfortunately impeded by lack of suitable data. Using data from several sources could overcome this. Thus, the techniques could be very valuable if the use of unevenly spaced data from several sources does
not lead to serious loss off accuracy. However, the techniques are still very useful when assessing underlying dynamics in model output and paleooceanographic time-series.

Eddy-resol​ving Simulation​s for Turbomachi​nery Applicatio​ns

Richard Sandberg (Investigator), Li-Wei Chen

Traditionally, the design of turbomachinery components has been exclusively accomplished with steady CFD, with Reynolds Averaged Navier-Stokes (RANS) models being the predominant choice. With computing power continuously increasing, high-fidelity numerical simulations of turbomachinery components are now becoming a valuable research tool for validating the design process and continued development of design tool.
In the current project, Direct Numerical Simulations (DNS) and other eddy-resolving approaches will be performed of turbomachinery components to establish benchmark data for design tools, and to investigate physical mechanisms that cannot be captured by traditional CFD approaches.

Evolving Behaviour-Dependent Strategies in Agent Negotiations

Enrico Gerding, Markus Brede (Investigators), Darius Pepe Falahat

We use genetic algorithms to evolve trading strategies for iterative bilateral negotiations between buyers and sellers. In contrast to previous work we evolve purely reactive strategies that base decisions on memories of behaviour in previous negotiation rounds. A paper was written on this research and was published in the proceedings for the European Conference on Artificial Life 2013.

Evolving Resilience to Leverage Based Crashes

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

This project analyses the maturation, initiation and evolution of crashes in the financial markets using an agent-based model.

Excitable Boys: An Exploration of the Role of Social Groups in the Self-radicalisation Process Using Agent-based Modelling.

Jason Noble (Investigator), Lewys Brace

This work built upon the seminal work of Sageman (2008), and his hypothesis that the self-radicalisation phenomenon that we are currently witnessing across Europe and the United States stems from self-organising ‘bunches of guys’. More specifically, there was a focus on how individuals can influence one another through social links; and how this can lead to behaviour, similar to deindividuation, arising through their interactions. Complexity theory and agent-based modelling were used in order to explore the interactions that are believed to lie at the heart of this psycho-social phenomenon, and justification is given for this approach. The model presented demonstrated that social bonds can lead to a greater number of individuals ‘rebelling’ against the status quo.

Fidelity optimisation in an atomic quantum computer

Timothy Freegarde (Investigator), Jack Saywell

Development of optimised composite pulses for atomic quantum computers with the aim of reducing systematic errors in information processing caused by variations in laser intensity and environment.

First Principles Simulation of Glycine Adsorption to Amorphous Silica

Chris-Kriton Skylaris (Investigator), Benjamin Lowe

Understanding the molecular interactions between silica and biomolecules is an important in the fields of Bionanotechnology, Biomimetic Material Science and Prebiotic Chemistry. DFT calculations were performed based on a literature study to better understand the interaction between silica and glycine.

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?”

Fluid Structure Interactions of Yacht Sails

Stephen Turnock (Investigator), Daniele Trimarchi

The research is the main subject of the PhD topic. It regards the application of fluid structure interaction techniques to the domain of yacht sails simulation

Fracturing of small social networks

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

A connected social network is a very important factor for the success of groups and organisations. We investigate which factors make a group more resistant to the effects of disagreements which commonly happen in small social networks.

FUE: Foragers in Unpredictable Environments

Iza Romanowska

An Agent-based model developed to investigate human dependencies on orally transmitted knowledge under constantly changing environmental conditions.

Generic Operational Simulation of Civil Unmanned Air Vehicle Operations

Hans Fangohr, James Scanlan (Investigators)

This project creates a generic operational simulation of Unmanned Air Vehicle Operations. UAVs can be valued for their mission-suitability and compared against various configurations.

Graphical Simulation of Archaeological Environments

Graeme Earl (Investigator)

This project defines an emerging area of interest in physically accurate rendering within the Archaeological Computing Research Group. Sub-projects include analysis of Roman spaces at herculaneum, Neolithic buildings at Catalhoyuk and simulation of a range of artefacts.

Hadronic structure on the computer

Jonathan Flynn (Investigator), Dirk Broemmel, Thomas Rae, Ben Samways

In experiments at the Large Hadron Collider (LHC) at CERN, Geneva, the interactions that occur between the colliding particles (protons in this case) can be factorised into a simple scattering between two constituent particles, called quarks, followed by a hadronisation process, which describes the dynamics of forming the bound proton states. Quarks are particles within the proton that bind to form composite particles (hadrons) such as a proton. The scattering process can be computed relatively easily, but hadronisation is intrinsically non-perturbative and hard to calculate. Lattice QCD (computer simulation of QCD on a discrete space-time lattice) provides our only known first-principles and systematically-improvable method to address problems like hadronisation. This project uses Iridis to extract parton distribution amplitudes which are experimentally inaccessible, but needed to describe the quark structure of hadrons.

High-resolution shock-capturing (HRSC) methods for elastic matter in general relativity

Carsten Gundlach, Ian Hawke, Stephanie Erickson (Investigators)

We are designing HRSC methods for numerical simulation of elastic matter coupled to general relativity and later magnetic fields, with the ultimate aim of simulating old neutron stars, which have elastic crusts.

How far can we stretch the MARTINI?

Syma Khalid (Investigator), Ric Gillams

To date, coarse-grained lipid models have generally been parameterised to ensure the correct prediction of structural properties of membranes, such as the area per lipid and the bilayer thickness. The work described here explores the extent to which coarse-grained models are able to predict correctly bulk properties of lipids (phase behaviour) as well as the mechanical properties, such as lateral pressure profiles and stored elastic stress in bilayers. Such an evaluation is crucial for understanding the predictive capabilities of coarse-grained models.

How sensitive is ocean model utility to resolution?

Kevin Oliver (Investigator), Maike Sonnewald

One of the most intriguing problems in recent ocean modeling research is the impact of varying model resolution on model accuracy. Increasing model resolution one includes more of the important processes. However, the increase in accuracy with resolution is unlikely to be linear. Thus, as computational cost increases with resolution, a critical assessment of achieved benefits is prudent. Here we analyse a suite of realistic and compatible global ocean model runs from coarse (1o, ORCA1), eddy-permitting (1/4o, ORCA025) and eddy resolving (1/12o, ORCA12) resolutions. Comparisons of steric height variability (varSH) highlight changes in ocean density structure, revealing impacts on mechanisms such as downwelling and eddy energy dissipation. We assess vertical variability using the covariace of the deep and shallow varSH. Together with assessing isopycnal movements, we demonstrate the influence of deep baroclinic modes and regions where the barotropic flow sheds eddies. Significant changes in the deepwater formation and dispersion both in the Arctic and Antarctic are found between resolutions. The varSH increased from ORCA1 to ORCA025 and ORCA12, particularily in the Southern Ocean and Western Boundary Currents. However, there is no significant covariance between the surface and deep in ORCA1, while ORCA025 and ORCA12 show significant covariance, implying an important missing energy pathway in ORCA1. Comparing ORCA025 and ORCA12 we see significant differences in eddy energy dissipation. We assess the impact of varying model resolution on the mean flow, discussing implications to dissipation pathways on model accuracy, with reference to stochastic parameterisation schemes.

Hybrid quantum and classical free energy methods in computational drug optimisation

Jonathan Essex, Chris-Kriton Skylaris (Investigators), Christopher Cave-Ayland

This work is based around the application of thermodynamics and quantum mechanics to the field of computational drug design and optimisation. Through the application of these theories the calculation of the physical properties of drug-like molecules is possible and hence some predictive power for their pharmaceutical activity in vivo can be obtained.

Hybrid RANS/LES methods

Richard Sandberg (Investigator), Markus Weinmann

Novel hybrid RANS/LES methods are developed for more accurate and efficient simulation of flow over complex geometries.

Image Based Modelling of Fluid Flow through Lymph Nodes

Tiina Roose, Bharathram Ganapathisubramani, Geraldine Clough (Investigators), Laura Cooper

In this project we are using images of mouse lymph nodes to investigate the fluid transport pathways through it. The images of the nodes are taken using selective plane illumination microscopy, and synchrotron micro computed tomography. The fluid flow is modelled using Darcy's law in COMSOL Multiphysics and the models are run on the Iridis cluster.

Impact of reciprocal feedbacks between evolution and ecology

Richard Watson, Patrick Doncaster, James Dyke (Investigators), Daniel Power

How do organism's activities affect their evolutionary trajectories? This project uses simulation techniques to evaluate the effects of this feedback.

Integrated in silico prediction of protein-protein interaction motifs

Richard Edwards (Investigator), Nicolas Palopoli, Kieren Lythgow

Many vital protein-protein interactions are mediated by Short Linear Motifs (SLiMs) which are short proteins typically 5-15 amino acids long containing only a few positions crucial to function. This project integrates a number of leading computational techniques to predict novel SLiMs and add crucial detail to protein-protein interaction networks.

Integrating Automated Vehicles into the Transport Network

Bani Anvari, Ben Waterson (Investigators), Craig Rafter

Innovative new designs to transportation infrastructure - with a strong evidence base - that will support automated vehicles to maximize sustainability in the transport network.

Integrating least-cost models with agent-based simulations: example hedgehog responses to fragmented landscapes

Jason Noble, Patrick Doncaster (Investigators), Angela Watkins

This study presents a novel analysis of an agent-based model of hedgehog movements integrated with a least-cost model of hedgehog dispersal and validated in landscapes with a varying degree of habitat fragmentation. A comparison of the fitness of individual agents reveals that incorporating a simple rule into
individual agents, to better mimic movement choices by real hedgehogs, dramatically affects the relationship between individual fitness and fragmentation.

Introducting Defects into the Ising Model

Benjamin Lowe

The well-known Ising model, a model of emergent critical phenomenon and phase transitions, was reimplemented and extended to incorporate the study of defects in the lattice.

Investigation into the Interfacial Physics of Field Effect Biosensors

Nicolas Green, Chris-Kriton Skylaris (Investigators), Benjamin Lowe

This interdisciplinary research aims to improve understanding of Field Effect Transistor Biosensors (Bio-FETs) and to work towards a multiscale model which can be used to better understand and predict device response.

Investigations of Lymphatic Fluid Flow

Tiina Roose, Bharathram Ganapathisubramani, Geraldine Clough (Investigators), Laura Cooper

The lymphatic system performs three main roles returns interstitial fluid back into the blood stream to maintain tissue fluid homeostasis. The aim of this project is to increase our understanding of how the lymph flows through the system by creating three dimensional fluid structure interaction models of the secondary lymphatic valves and image based models of lymph nodes.

Is fine-scale turbulence universal?

Richard Sandberg (Investigator), Patrick Bechlars

Complementary numerical simulations and experiments of various canonical flows will try to answer the question whether fine-scale turbulence is universal.

Is the decline in East African lesser flamingo population a natural concequence of soda ake dynamics?

Seth Bullock

An interdisciplinary approach using palaeoenvironmental data analysis and a modelling is being used investigate the dramatic fluctuations in conditions in the East African Rift Valley soda lakes, and how these changes may be impacting the lesser flamingo population.

It takes all sorts: the mathematics of people’s behaviour in financial markets

Valerio Restocchi (Investigator), Frank McGroarty, Enrico Gerding

Agent-based models provide a deeper understanding of financial markets than classic models. We model people's behaviour and use agent-based simulations to study financial markets. By analysing the emerging complex dynamics, we achieve a deeper understanding of market participants' behaviours, which are necessary for a deeper comprehension of financial markets themselves.

Jet noise

Richard Sandberg (Investigator), Neil Sandham

Direct numerical simulations are used to investigate jet noise.

Lagrangian modelling of ecosystem dynamics at the Bermuda Atlantic Time-series Study station

Tom Anderson, Seth Bullock (Investigators), Melissa Saeland

Focus in the marine ecosystem modelling community is starting to shift towards the use of Lagrangian, agent-based models as these are believed to produce more realistic results. The basic assumptions behind these models have not been thoroughly tested, and this project aims to undertake a detailed study of Lagrangian marine ecosystem models, before creating one to investigate the dynamics at the Bermuda Atlantic Time-series Study station (BATS).

Laminar to Turbulent Transition in Hypersonic Flows

Neil Sandham, Heinrich Luedeke

Understanding of laminar to turbulent transition in hypersonic boundary-layer flows is crucial for re-entry vehicle design and optimization. The boundary-layer state directly affects the temperatures on the vehicle surface and its viscous drag. Therefore transition has to be considered to correctly compensate for drag and to properly design the thermal protection system.
For the proposed study, in order to obtain a clear understanding of the transition process, the configuration is kept as simple as possible by varying only a minimum number of parameters affecting transition on a simple test geometry such as a swept ramp at different sweep angles. To investigate the influence of such sweep angles on the transition process in the hypersonic regime, Direct Numerical Simulations (DNS) of the turbulent flow field are carried out on the Iridis cluster.

Large-Scale Quantum Chemistry Simulations of Organic Photovoltaics

Chris-Kriton Skylaris (Investigator), Gabriele Boschetto

The aim of this project is to use first principles quantum mechanical calculations to provide a detailed atomic-level understanding of OPV materials and models of bulk heterojunctions on a far larger scale than possible before by using the ONETEP program for linear-scaling first principles quantum mechanical calculations.

Lattice Holographic Cosmology

Andreas Juttner (Investigator), Matthew Mostert

This project will aim to develop new theoretical field methods and massively parallel computational algorithms to be utilised on both new computational architectures (e.g. Intel Xeon Phi) and existing high performance computers (HPCs).

The ultimate goal is to make predictions for the power spectrum and non-gaussianties of the CMB which would then be falsifiable by comparison to the Planck and WMAP data.

Lattice Holographic Cosmology

This project will aim to develop new theoretical field methods and massively parallel computational algorithms to be utilised on both new computational architectures (e.g. Intel Xeon Phi) and existing high performance computers (HPCs).

Magnetic dynamics under the Landau-Lifshitz-Baryakhtar equation

Hans Fangohr (Investigator), Weiwei Wang

Magnetic dynamics using the Landau-Lifshitz-Baryakhtar (LLBar) equation that the nonlocal damping is included as well as the scalar Gilbert damping.

Magnon-Driven Domain-Wall Dynamics in the presence of Dzyaloshinskii-Moriya Interaction

Hans Fangohr (Investigator), Weiwei Wang

The domain wall motion induced by spin waves (magnons) in the presence of Dzyaloshinskii-Moriya Interaction is studied in this project.

Mathematical modelling of plant nutrient uptake

Tiina Roose (Investigator)

In this project I will describe a model of plant water and nutrient uptake and how to translate this model and experimental data from the single root scale to the root branching structure scale.

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.

Measuring organisation with statistical complexity

Seth Bullock (Investigator), David Arden

What is a organisation and how can we measure it? In particular, can we automate the process of picking out the emergence of pattern and structure in a noisy system over time?

Micromagnetic simulation of Magnetoelectric Multiferroics

Hans Fangohr (Investigator), Rebecca Carey

The focus of this project is towards the understanding of the magnetic and electric couplings in multiferroic materials, in order to create a magnetoelectric micromagnetic model.

Microstructural modeling of skin mechanics

Georges Limbert (Investigator), Emanuele Zappia

Microstructural modeling of skin mechanics to gain a mechanistic insight into the biomechanics of the skin.

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.

Modelling mechanoreceptor reaction to tissue deformation

Mark Taylor (Investigator), Gwen Palmer

This project involved the modelling of a piece of knee joint capsule, which will produce an electrical output when mechanically stimulated. The model is based on expermental work carried out by P. Grigg and A.H. Hoffman (1982).

Modelling micromagnetism at elevated temperature

Hans Fangohr, Kees de Groot, Peter de_Groot (Investigators), Dmitri Chernyshenko


We aim to develop a multiscale multiphysics model of
micromagnetism at elevated temperatures with atomistic simulations for
material parameter. The tool will be used to guide the development of the next generation magnetic data storage technology: heat assisted magnetic recording.

Modelling neuronal activity at the knee joint

Mark Taylor, Tiina Roose (Investigators), Gwen Palmer

The function of the knee joint is reliant on proprioception, which involves the response of nerve endings in the tissues at the joint. This project will be concentrating on the neuronal activity, caused by mechanical stimuli, of the more common receptors found at the knee (Ruffini, Paciniform, Golgi and Nociceptor).

There are three stages to this project:
1. Modelling the behaviour of each individual receptor, with the use of the Hodgkin-Huxley model [1].
2. These models will then be applied to the soft tissues around a knee, where a global deformation of the tissue will result in local stimulation of receptors.
3. The soft tissue models will then be applied to structures in the knee.

[1] - Hodgkin, A.L. and A.F. Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, 1952. 117: p. 500-544.

Modelling of neutron star interactions in X-ray binary systems

Malcolm Coe (Investigator), Rory Brown

Investigating the X-ray production mechanisms of binaries containing neutron stars and the decretion disks of Be stars using Smoothed Particle Hydrodynamics (SPH).

Modelling power output and wake effects in tidal stream turbine arrays

William Batten (Investigator), Matthew Harrison, Luke Blunden

The PhD research is regards the investigation of modelling techniques for simplifying turbine simulation so that models of large arrays can be investigated.

Modelling the Easterlin Effect

Jason Hilton

This project is an attempt to formalise the Easterlin hypothesis in a simulation model and test its plausibility.
The Easterlin Hypothesis, developed by economist Richard Easterlin, purports to describe a mechanism whereby the fertility decisions of a particular cohort of individuals are linked to population level conditions that held sway when they were born The empirical support for the theory is quite strong for the certain periods in the history of the United States, but elsewhere it is circumstantial and patchy. A simulation model may allows us to test under what conditions it may hold and not hold, and also might help inform more general theory building.

Modelling the morphodynamic evolution of the Ganges-Brahmaputra-Meghna (GBM) Delta over centennial time scales

Stephen Darby (Investigator), Balaji Angamuthu

Around 0.5 Billion people live in deltaic environments where they are threatened by flooding and land loss frequently. Yet, our understanding of the threats posed by land dynamic process remains limited. In this work, we try to address this issue through a land dynamic simulation of the largest and most populated of all the deltas, the GBM Delta, using the CFD software Delft3D for a range of climate change and management scenarios. The results provide new insight into the factors controlling past morphodynamics that, in turn, are helpful when assessing the possible trajectories of future evolution.

Models of Avian Flocking

Edward Butler (Investigator)

This research review project explores current state of avian flock modelling research, exploring how ideas have developed since the earliest theories dating back to the 1930s.

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).

Multi-Scale Modelling of Composite Riser Systems

Adam Sobey (Investigator), Hossam Ragheb

There is an ever increasing interest in exploiting ocean resources at greater depths. At these depths composite materials have a larger separation, in terms of benefits, from traditional steel structures as they offer lower maintenance costs, low weight and high durability. However, there are limited current examples of using composites for these applications meaning that empirical knowledge and specific computational tools are limited. As an example of this lack of knowledge current design guidance gives fatigue safety factors in a range of 15-50. Development of more accurate computational tools will allow an increase in safety and/or reduction of the structure.

A key aspect to increasing the usage of flexible composite risers is the ability to assess the reliability of such structures. Importance Sampling Simulation is becoming the preferred method to assess structures which ideally requires a fast and accurate structural modelling method. Whilst Finite Element Methods can provide an accurate solution to these problems they are slow to run. It is therefore proposed to investigate the use of multiscale modelling to investigate the reliability of such structures. This will involve the development of: a full-scale model to be run in conjunction with fluid mechanics simulations, a higher resolution model to investigate the fatigue hotspot near the seabed and a more local model to simulate the fatigue growth.

Multimode simulation of high power fibre lasers and amplifiers

Peter Horak (Investigator), Ioannis Begleris

This project aims to address the challenge of ever-increasing demand for higher powers from fibre lasers by developing theoretical and numerical methods to simulate laser pulse amplification in large-mode area fibres supporting multiple spatial modes.

Multiscale Modelling of Cellular Calcium Signalling

Hans Fangohr, Jonathan Essex (Investigators), Dan Mason

Calcium ions play a vitally important role in signal transduction and are key to many cellular processes including muscle contraction and cell apoptosis (cell death). This importance has made calcium an active area in biomedical science and mathematical modelling.

Multiscale Modelling of Electrochemical Processes in Neurons

John Chad (Investigator), Stuart George

Using asymptotic expansions to determine how the signalling behaviour of neurons is related to their microstructure.

Multiscale modelling of neutron star oceans

Ian Hawke (Investigator), Alice Harpole

Type I X-ray bursts are explosions which occur on the surface of some
neutron stars. It is believed that the burning begins in a localised spot in the ocean of the
star before spreading across the entire surface. By gaining a better understanding of X-ray
bursts, it is hoped that tighter limits can be determined for other neutron star properties
such as the radius and magnetic field strength.

Multiscale models of magnetic materials at elevated temperatures

Denis Kramer, Ondrej Hovorka (Investigators), Jonathon Waters

This project will develop and apply multi-scale modelling approaches to investigate thermal fluctuation effects in magnetic materials.

Multiscale Relativistic Simulations

Ian Hawke (Investigator), Alex Wright

There has been recent success in experiments, such as LIGO, in detecting the mergers of celestial objects via the gravitational waves they emit. By implementing numerical methods, we aim to speed up the numerical simulations of these events but up to two orders of magnitudes, and study binary inspirals in greater detail and over much larger timespans.

MXL Project

Mark Taylor, Junfen Shi (Investigators)

‘MXL’ is short for “Enhanced patient safety by computational Modelling from clinically available X-rays to minimise the risk of overload and instability for optimised function and Longevity”. This is an international EU-funded project which the Bioengineering Sciences Research Group at Southampton is involved in. For more information, visit http://www.m-x-l.eu

nano-CMOS

Mark Zwolinski (Investigator), Michael Merrett

Modelling random device variations within systems using nano-CMOS technologies.

Network Analysis of Roman Transport Routes in the Imperial Roman Mediterranean

David Potts

This research is designed to explore the nature of the relationships between Portus, Rome, and other selected ports in the Mediterranean and to establish patterns and the changing nature of trading networks derived from the distribution of known Roman artefacts.

New Forest Cicada Project

Alexander Rogers, Geoff Merrett (Investigators), Davide Zilli, Oliver Parson

Rediscover the critically endangered New Forest cicada with crowdsourced smartphone biodiversity monitoring techniques.

Next Generation Space Debris Environment Model

Hugh Lewis (Investigator), Samuel Diserens

Developing a next generational model of the space debris environment. Including inter-disciplinary issues related to space debris, space operations, space situational awareness, space weather, commercialisation, possible conflicts in space and regulation

NGCM-0054 - Automatic Code Generation for Computational Science

Hans Fangohr (Investigator), Gary Downing

Automatically generate code to solve partial differential equations specified symbolically.

Non-Perturbative Renormalisation on the Lattice

Jonathan Flynn (Investigator), Dirk Broemmel, Thomas Rae

In this project we compute renormalisation factors for various physical observables in a non-perturbative lattice framework. Renormalisation hereby arises due to a fundamental scale dependence of the physical processes.

Nonequilibrium Dynamics of Atomic Gases in Optical Lattices

Sophie Marika Reed

Many-body, quantum systems exhibit emergent properties which allows for quantum events to influence properties on macroscopic scales. Such emergent properties are studied using stochastic phase-space techniques.

Nonlinear Optics in Structured Material

Peter Horak, Neil Broderick (Investigators)

Structured materials such as photonic crystals, optical fibres, Bragg gratings etc. are the ideal material for nonlinear optics. Properly engineered materials allows one to control which nonlinear interactions are observed and enhanced whilst other nonlinear interactions can be neglected. This work looks both at fundamental ideas as well as the fabrication of devices for advanced telecommunications.

Numerical Elastic Neutron Stars

Ian Hawke, Ian Jones (Investigators), Andrew Penner

We study the astrophysical effects of the crust on a neutron star using an elasto-hydrodynamic model.

On the applicability of nonlinear timeseries methods for partial discharge analysis

Paul Lewin (Investigator), Lyuboslav Petrov

The governing processes of Partial Discharge (PD)
phenomena trigger aperiodic chains of events resulting in ’ap-
parently’ stochastic data, for which the widely adopted analysis
methodology is of statistical nature. However, it can be shown,
that nonlinear analysis methods can prove more adequate in
detecting certain trends and patterns in complex PD timeseries.
In this work, the application of nonlinear invariants and phase
space methods for PD analysis are discussed and potential pitfalls
are identified. Unsupervised statistical inference techniques based
on the use of surrogate data sets are proposed and employed for
the purpose of testing the applicability of nonlinear algorithms
and methods. The Generalized Hurst Exponent and Lempel Ziv
Complexity are used for finding the location of the system under
test on the spectrum between determinism and stochasticity. The
algorithms are found to have strong classification abilities at
discerning between surrogates and original point series, giving
motivation for further investigations.

OpenDreamKit

Hans Fangohr (Investigator), Marijan Beg

OpenDreamKit is a [Horizon 2020](https://ec.europa.eu/programmes/horizon2020/) European Research Infrastructure project (#676541) that will run for four years, starting from September 2015. It will provide substantial funding to the open source computational mathematics ecosystem, and in particular popular tools such as LinBox, MPIR, SageMath, GAP, Pari/GP, LMFDB, Singular, MathHub, and the IPython/Jupyter interactive computing environment.

Operational Simulation of the Solent Search-and-Rescue environment

James Scanlan, Kenji Takeda, Hans Fangohr (Investigators), Ben Schumann

This project aims to identify useful metrics for a proposed Search-and-Rescue UAV and test it virtually in a realistic environment.

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.

Origins of Evolvability

Richard Watson, Markus Brede (Investigators), William Hurndall

This project examined the putative evolvability of a Lipid World model of fissioning micelles. It was demonstrated that the model lacked evlovability due to poor heritability. Explicit structure for micelles was introduced along with a spatially localised form of catalysis which increased the strength of selection as coupling between potential chemical units of heredity were reduced.

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.

Precision study of critical slowing down in lattice simulations of the CP^{N-1} model

Jonathan Flynn, Andreas Juttner (Investigators), Andrew Lawson

This project involves the study of critical slowing down (CSD): a property that may arise when taking measurements in Monte Carlo simulations. In order to study and quantify this phenomenon we have performed extensive simulations of the CP^{N-1} model. By studying the properties of the Monte Carlo algorithms in this model, we hope to make algorithmic improvements that can then be employed in simulations of physical quantum field theories, such as in lattice quantum chromodynamics (lattice QCD).

Predicting Available Energy in Energy Harvesting Wireless Sensor Networks

Geoff Merrett (Investigator), Davide Zilli

Is it possible to predict how much energy a sun-light or wind powered wireless sensor node can harvest and tune its sensing pattern accordingly?

Prediction of orifice flow flooding rates through generic orifices

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

This presearch concentrates on the modelling of compartment flooding rates following the occurrence of damage in a ship's side shell. Typical state of the art flooding models use Torricelli’s formula to calculate flooding rates using a constant co-efficient of discharge (Cd). Based on Bernoulli’s theorem, turbulence and viscosity effects are not included using a Cd independent of damage shape or size. Previous work indicates that this assumption over-simplifies the problem to an extent where the flooding rates used for calculation are in error. This project will use CFD validated by experiment to calculate flooding rates for a large number of cases from which a 'krigged' response surface will be generated. Validity of the subsequent response surface will be interrogated.

Preventing Alzheimer's Disease: A Multiphysics Simulation Approach

Neil Bressloff, Giles Richardson, Roxana-Octavia Carare (Investigators), Alexandra Diem

Experimental research has identified the causes of many diseases, such as Alzheimer's Disease. However, finding an effective treatment is very cost- and time-intensive and sacrifices many animals and does not guarantee success. In this PhD project, we investigate the driving force of solute drainage in the brain using multiphysics simulations in order to identify possible ways of preventing dementia.

Pushing the Envelope of Planetary Formation and Evolution Simulations

Peter Bartram

A full understanding of the formation and the early evolution of the Solar System and extrasolar planetary systems ranks among natural science's grand challenges, and at present, even the dominant processes responsible for generating the observed planetary architecture remain elusive.

pyQCD

Matthew Spraggs

A basic Python package to perform coarse lattice QCD simulations on desktop and workstation computers.

Quantifying Collective Construction

Seth Bullock (Investigator), Nicholas Hill

This was an initial investigation into how best to develop quantifying and discriminating measures of both the processes and results of collective construction.

Reforging the Wedding Ring: Exploring a Semi-Artificial Model of Population for the United Kingdom with Gaussian process emulators

Jason Hilton

Note: Jakub Bijak from Social Science is the lead author on this project, which is forthcoming in Demographic Research (http://www.demographic-research.org/)
Co-Authors: Eric Silverman, Viet Dung Cao

We extend the „Wedding Ring‟ agent-based model of marriage formation to include some empirical information on the natural population change for the United Kingdom together with behavioural explanations that drive the observed nuptiality trends.

Renormalisation group approach to 1D cellular automata with large updating neighbourhoods

Iain Weaver, Adam Prugel-Bennett (Investigators)

We study self-similarity in one-dimensional probabilistic cellular automata (PCA) by applying a real-space renormalisation technique to PCA with increasingly large updating neighbourhoods. By studying the flow about the critical point of the renormalisation, we may produce estimates of the spatial scaling properties of critical PCA.

Renormalisation of 2D cellular automata with an absorbing state

Adam Prugel-Bennett, Iain Weaver (Investigators)

We describe a real-space renormalisation scheme for non-equilibrium probablistic cellular automata (PCA) models, and apply it to a two-dimensional binary PCA. An exact renormalisation scheme is rare, and therefore we provide a method for computing the stationary probability distribution of states for such models with which to weight the renormalisation, effectively minimising the error in the scale transformation.

Replication of Sayama Group Decision Model

Jason Noble (Investigator), Jonathan Gray

Replication of a model of group decision making from Sayama et al. (2011), with a revised methodology that alters a conclusion from the original paper.

Sample tracking in whole-exome sequencing projects

Andrew Collins, Sarah Ennis (Investigators), Reuben Pengelly

Whole-exome sequencing is entering clinical use for genetic investigations, and it is therefore essential that robust quality control is utilised. As such we designed and validated a tool to allow for unambiguous tying of patient data to a patient, to identify, and thus prevent errors such as the switching of samples during processing.

SAVE: Solent Achieving Value through Efficiency

Patrick James, Ben Anderson (Investigators), Luke Blunden

Analysis of 15 minute electricity consumption and 10 second instantaneous power data from 4,000+ households in the Solent region collected over 3 years of a randomised control trial study.

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.

Self Interest & the Evolutionary Optimisation of Adaptive Trading Agents for Continuous Double Auctions

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

One cannot escape the recent crises in economics and the lack of understanding of financial markets that has been highlighted by them. Improvements to current market models are already being made and a realisation of the power of agent based modelling in such models is evident. In this project we seek to explore an existing model by Cliff of trader behaviour in continuous double auctions. We investigate the strategies that arise in such auctions when trader parameters are evolved with intent to maximise personal profit. Results show different trading strategies to those evolved by Cliff and explanations are given with regards to the self-interest.

Self Organized Network Routing using Quantum Evolutionary Methods

Lajos Hanzo (Investigator), Dimitrios Alanis

Self Organized Networks (SON) may consist of a large number of nodes, which could be fully interconnected. Optimizing its performance satisfying various Quality of Service (QoS) requirements is a quite complex procedure and the optimization problem belongs to the family of the Travelling Salesman Problems (TSP) which has been proven to be NP-hard as the number of nodes increases. In this project, various suboptimal methods are used in order to tackle this multi-objective optimization problem; in particular, the Ant Colony Optimization (ACO) and its quantum inspired counterpart (QACO) are being employed in order to reduce complexity.

Self-Force and Black Hole Inspirals

Sam Dolan (Investigator)

We use IRIDIS to compute the self-force acting on a solar-mass black hole orbiting a supermassive black hole.

Sensitivity of the critical depth to the choice of particle movement rules in Lagrangian models and the consequences for the predicted timing of the spring bloom

Tom Anderson (Investigator), Melissa Saeland

Individual-based (Lagrangian) models lend themselves to the study of the controls of the spring bloom in the ocean, due to their ability to represent both the turbulence and the phytoplankton motion. Here, we use a Lagrangian phytoplankton model to test some of the most prevalent hypotheses (e.g. critical depth and critical turbulence).

Separation of timescales in models of complex networks

Seth Bullock (Investigator), Elisabeth zu-Erbach-Schoenberg, Connor McCabe

In many real-world systems several processes act on the system state. The way these processes interact can have implications for the resulting system state. We investigate how separation of the timescales of two processes influences the system's equilibrium state.

Simulating Household Decision Making in Rural Malawi

James Dyke, Kate Schreckenberg (Investigators), Samantha Dobbie

A scoping exercise to determine whether data collection tools of the social sciences can be used effectively in the construction of empirical ABM. Focus fell upon simulating drought coping strategies of Malawian smallholders. Model implementation enabled inferences to be made concerning the impact of drought and input subsidies upon smallholder food security.

Simulating Human Expansion in the Early Pleistocene

Seth Bullock, Fraser Sturt (Investigators), Iza Romanowska

Using Agent-based modelling to investigate the first human dispersal almost 2 million years ago.

Simulating Multi-Agent Negotiation with Agents that use Incomplete Information

Enrico Gerding (Investigator), Darius Pepe Falahat

An investigation into multi-agent negotiation where the participants have incomplete information about each other. This project consisted of a literature review and creating a simulation model based on the research being reviewed.

Simulating Sleeping Sickness: a two-host agent-based model

Jason Noble, Peter Atkinson (Investigators), Simon Alderton

Sleeping sickness is a vector-borne, parastic disease which affects millions of people across 36 sub-Saharan African countries. Using agent-based models, we aim to gain a greater understanding of the interactions between the tsetse fly vector and both animal and human hosts.

Building an accurate representation will allow the testing of local interventation scenarios including the closing of watering holes, and the selective spraying of cattle with insecticides.

Simulation modelling of habitat permeability for mammalian wildlife

Patrick Doncaster, Jason Noble (Investigators), Angela Watkins

Using and integrating least-cost models and agent-based simulations to explore the way in which mammals interact with, and hence move, through fragmented landscapes.

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.

Simulation of Parking Choice Behaviour

Ben Waterson, Hans Fangohr (Investigators), James Snowdon

Exploring how psychological models of individual parking search behaviours can be combined into an accurate simulation of vehicle flows, allowing for assessment of the impact on searching traffic of different demand/ supply ratios, different driver population characteristics and different charging regimes.

Simulations investigating droplet diameter-charge models, for predicting electrostatically atomized dielectric liquid spray chracteristics

Gabriel Amine-Eddine (Investigator), John Shrimpton

Liquid sprays are atomized using electrostatic methods in many scienti fic, industrial and engineering applications. Due to jet and droplet breakup mechanisms, these spray plumes contain a range of drop diameters with differing droplet charge levels. Using an transient charged spray CFD code, simulations have been performed to investigate charge-diameter relationship models for predicting dynamics of poly-disperse and electrostatically atomized hydrocarbon sprays.

The methodology developed can be readily extended towards high-pressure spray applications, where secondary atomization plays a dominant role within the spray dynamics and subsequent performance of the spray itself.

Amine-Eddine, G. H. and Shrimpton, J. S. (2013), On simulations investigating droplet diameter–charge distributions in electrostatically atomized dielectric liquid sprays. Int. J. Numer. Meth. Fluids, 72: 1051–1075. doi:10.1002/fld.3776

Simulations of Magnetic Skyrmions

Hans Fangohr (Investigator), Ryan Pepper

The manipulation of magnetic skyrmions could prove to be a useful technique for storing data on an unprecedented density scale. In this project we seek to better understand their properties and ways to control them.

Skyrmionic states in confined helimagnetic nanostructures

Hans Fangohr (Investigator), Marijan Beg

An ever increasing need for data storage creates great challenges for the development of high-capacity storage devices that are cheap, fast, reliable, and robust. Because of the fundamental constraints of today's technologies, further progress requires radically different approaches. Magnetic skyrmions are very promising candidates for the development of future low-power, high-capacity, non-volatile data storage devices.

Software Sustainability Institute

Simon Hettrick (Investigator)

A national facility for cultivating world-class research through software

Software helps researchers to enhance their research, and improve the speed and accuracy of their results. The Software Sustainability Institute can help you introduce software into your research or improve the software you already use.

The Institute is based at the universities of Edinburgh, Manchester, Oxford and Southampton, and draws on a team of experts with a breadth of experience in software development, project and programme management, research facilitation, publicity and community engagement.

We help people build better software, and we work with researchers, developers, funders and infrastructure providers to identify key issues and best practice in scientific software.

Space Debris and Evolution of of Resilient Space Systems

Hugh Lewis (Investigator), Marian Daogaru

The aim of the project will be to characterise and quantify the possible evolution of space systems in response to future environmental change; in particular, with respect to changes in the space debris environment.

Space debris has been recognised by the international space-faring community as a significant threat to spacecraft operations in Earth orbit. Impacts on spacecraft can result in damage to critical systems, the loss of the mission, and the generation of fragment clouds which may go on to endanger other spacecraft. With the population of objects in near-Earth orbit ever-increasing, future space systems will need to develop greater resilience to the growing space debris threat. Resilience to this threat can be achieved in several ways, through adaptation, redundancy, protection, distribution and restoration, for example.

These resilience measures can be included within space systems design, which is a multi-objective optimisation process, such that the resulting spacecraft or architectural design is well-suited for operation in the space environment, whilst at the same time respecting mass, power, and cost constraints, amongst others. However, rapidly changing priorities in the space sector and changes in the debris population mean that optimal designs will need to evolve through time such that successive generations of spacecraft continue to be, or are better adapted to survive in the space environment. At the same time, better adapted spacecraft represent a possibly beneficial feedback into the space debris environment, meaning that future generations of spacecraft will also be indirectly affected by the designs of previous generations (and vice versa). Consequently, the multi-objective optimisation needs to be integrated with an appropriate space debris model.

The development of this integrated assessment and optimisation approach, and its application to identify future trends in space systems design, will form the basis of the project. Firstly, an appropriate methodology for identifying and representing the key design objectives, including concepts such as resilience, will be developed. Secondly, this methodology will be incorporated within a novel integrated assessment framework that will perform the multi-objective design optimisation through time.

Given the potential complexity of this task, arising from the large parameter space and the uncertainties in the future debris environment predictions, there will be a need for new and state-of-the-art computational modelling and optimisation approaches that enable solutions to be found in a reasonable time-frame. Such approaches could include evolutionary algorithms and particle swarm optimisation techniques. In addition, the project will also benefit from developments in space debris modelling coming from a parallel project.

Spatial Mobility in the Formation of Agent-Based Economic Networks

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

An investigation into the effect of spatial mobility on endogenous economic network formation.

Spatial variability of the atmosphere in southern England

Joanna Nield, Jason Noble, Edward Milton (Investigators), Robin Wilson

No-one really knows how variable key atmospheric parameters such as Aerosol Optical Thickness and Water Vapour content are over relatively small areas. This study aims to find out!

Stability of chiral structures in magnetic nanodisks

Hans Fangohr, Weiwei Wang (Investigators), David Cortes

This project is aimed to study the stability of skyrmionic and helical equilibrium states in magnetic nanodisks, using computational simulations.

Stratified combustion physics and modelling

Edward Richardson (Investigator)

Full-resolution simulation data for turbulent combustion are used to investigate the fundamental impact, and practical modelling, of fuel-air stratification.

Supernova Rates in the Local Universe

Mark Sullivan (Investigator), Christopher Frohmaier

This project will calculate the frequency of exploding stars -- or supernovae -- in the nearby universe. We simulate a 'toy universe' by exploding billions of stars in a computer, and then artificially 'observing' these explosions by replicating a real astronomical sky survey, the Palomar Transient Factory (PTF). The results of this simulation allows us to discover the rate at which supernovae occur in the local universe each year.

Supersonic axisymmetric wakes

Richard Sandberg (Investigator)

Direct numerical simulations are used to shed more light on structure formation and evolution in supersonic wakes.

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.

Tag based transcriptome analysis of gene expression in a promising green algae

Richard Edwards (Investigator), Andreas Johansson

We use SuperSAGE in combination with next-generation sequencing to compare differences in gene expression between selected mutants and the wild type of a green algae. The data in the form of millions of 26 bp tags representing short stretches of expressed genes, will be analysed to find patterns of variation in gene expression under different conditions.

TEDx: Closing the Loop: Entropy Accounting for a Sustainable World

Stuart Bartlett (Investigator)

This is a TEDx talk that I gave on some ideas I've had about the large-scale thermodynamic organisation of life on Earth. While these ideas probably aren't new, I believe they can teach us something about the way in which we think about energy and the 'consumption' of goods and energy.

Test and Rest

Hans Fangohr (Investigator), Evander DaCosta, James Graham, Oliver Laslett

Regression and system testing, automatic execution of testing - establishing best practice.

Testing an interaction game on relationships.

Seth Bullock (Investigator), Anastasia Eleftheriou

The aim of this project is to examine how attractiveness is related to hypothetical risky sexual behaviour. The term `risky sexual behaviour' refers to having multiple sexual partners without the use of a condom. Data will be collected using questionnaires in order to investigate the influence of attractiveness on intentions towards engaging in unprotected sexual intercourse. A primary research question is whether perceived attractiveness of a potential partner affects the reported likelihood of having sex and/or using a condom.

The application and critical assessment of protein-ligand binding affinities

Jonathan Essex (Investigator), Ioannis Haldoupis

A method that can accurately predict the binding affinity of small molecules to a protein target would be imperative to pharmaceutical development due to the time and resources that could be saved. A head-to-head comparison of such methodology, ranging from approximate methods to more rigorous methods, is performed in order to assess their accuracy and utility across a range of targets.

The application of automated pattern metrics to surface moisture influences on modelled dune field development

Robin Wilson, Joanna Nield (Investigators)

Areas of sand dunes (known as dunefields) develop complex patterns over time. These are influenced by both the past and present environmental conditions, including surface moisture, vegetation distribution and human impact. This project develops a method of automated pattern analysis which allow the patterns produced by a large number of sand dune evolution simulations (performed using the DECAL model) to be quantified over time.

The application of next-generation sequencing to unresolved familial disease

Andrew Collins, Sarah Ennis (Investigators), Jane Gibson, Reuben Pengelly

Next-generation sequencing (NGS) allows us to sequence individual patients cost-effectively, allowing us to enter a new era of genomic medicine. The level of genetic detail that we can access through these methods is unprecedented making it suitable for clinical molecular diagnostics.

The Atlantic Meridional Overturning Circulation’s Response to Variable Buoyancy Forcing

Kevin Oliver (Investigator), Edward Butler

An investigation into the impact of periodic variations in surface buoyancy forcing on the mean strength of ocean circulation; in particular, the Atlantic Meridional Overturning Circulation.

The Ca-geospeedometer - A tool for investigating the processes that generate oceanic crust

We quantify the errors inherent in the current methods of geospeedometry, which lets one obtain the cooling rate of a rock, using mineral trace element chemistry. Calcium-in-Olivine geospeedometry is useful for deep ocean crust.

We want to use this proxy to figure out how ocean crust actually accretes, it provides key evidence as to how magma chambers and hydrothermal systems interact to produce new lithosphere. But to do so we first have to determine how reliable the method is and therefore how much can be inferred from results.

The Endogenous Formation of Economic Networks

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

An investigation into endogenous network formation using a simple agent-based approach.

The importance of timescales for the emergence of environmental self-regulation

Iain Weaver, James Dyke (Investigators)

Models which explore the possibilities of emergent self-regulation in the Earth system often assume the timescales associated with changes in various sub-systems to be predetermined. We analyse a classic model of environmental self-regulation, Daisyworld, and interpret the original equations for model temperature, changes in insolation, and self-organisation of the biota as an important separation of timescales.

The Maximum Entropy Production Principle and Natural Convection

Seth Bullock, James Dyke (Investigators), Stuart Bartlett

In this project I wanted to perform some tests of the so-called Maximum Entropy Production Principle (MEPP) in the context of buoyancy-driven convection in a system with negative feedback boundary conditions.

THE NORM MATE TRANSPORTER FROM N. GONORRHEAE: INSIGHTS INTO DRUG & ION BINDING FROM ATOMISTIC MOLECULAR DYNAMICS SIMULATIONS

Syma Khalid (Investigator), Daniel Holdbrook, Thomas Piggot, Yuk Leung

The multidrug and toxic compound extrusion (MATE) transporters extrude a wide variety of substrates out of both mammalian and bacterial cells via the electrochemical gradient of protons and cations across the membrane. Multiple atomistic simulation are performed on a MATE transporter, NorM from Neisseria gonorrheae (NorM_NG) and NorM from Vibrio cholera (NorM_VC). These simulations have allowed us to identify the nature of the drug-protein/ion-protein interactions, and secondly determine how these interactions contribute to the conformational rearrangements of the protein.

The Ocean's Gravitational Potential Energy Budget in a Coupled Climate Model

Kevin Oliver (Investigator), Edward Butler

This study examines, in a unified fashion, the budgets of ocean gravitational potential energy (GPE) and available gravitational potential energy (AGPE) in the control simulation of the coupled atmosphere–ocean general circulation model HadCM3.

The Origins of Communication Revisited

Jason Noble (Investigator), Jordi Arranz

Quinn (2001) sought to demonstrate that communication be- tween simulated agents could be evolved without pre-defined communication channels. Quinn’s work was exciting because it showed the potential for ALife models to look at the real origin of communication; however, the work has never been replicated. In order to test the generality of Quinn’s result we use a similar task but a completely different agent architecture. We find that qualitatively similar behaviours emerge, but it is not clear whether they are genuinely communicative. We extend Quinn’s work by adding perceptual noise and internal state to the agents in order to promote ritualization of the nascent signal. Results were inconclusive; philosophical implications are discussed.

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 Philosophy of Complexity

Greg Fisher

How we think is in large part socially constructed, which means we inheret cognitive ways of framing and making sense of the world around us.

The Enlightenment saw an important shift towards reductionism and atomistic thinking, which on the one hand helped facilitate many stunning successes in science but on the other, we have applied these principles in domains when we perhaps should not e.g. in economics.

In this project I would like to explore how philosophy can benefit the complexity revolution, and how complexity theory can support philosophy.

The response of the Bergmann glial cell to synaptic activity

Giles Richardson (Investigator), Stuart George

We model the potential changes induced in the Bergmann glial cell by synaptic activity in neighbouring neurons.

The Role of Information in Price Discovery

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

The recent economic crisis has highlighted a continued vulnerability and lack of understanding in the financial markets. In order to overcome this, many believe that current market models must be improved. Recently, a trend towards agent-based modelling has emerged. Viewing the economy as a complex system is beginning to be seen as key to explaining certain market characteristics that were originally considered anomalies.

One of the fundamental assumptions in economics is that of information efficiency: that the price of a stock reflects its worth, that all possible information about a security is publicly known, and that any changes to price take place instantaneously. In reality, however, this is not the case.

This project considers the use of agents in modelling economic systems and demonstrates the effect of information levels on price discovery using a simple market simulation.

The Role of the Biota in the Carpenter Model on Lake Eutrophication

James Dyke (Investigator), Alexandra Diem

The Carpenter model is a useful and simple model to predict the eutrophication of shallow lakes via phosphorus input. This project aimed at resolving the function of the biota, which play a major role in the phosphorus dynamics, but are so far only implicitly modelled, and extending the model to explicitly represent them.

The Social-cognitive Niche: An Exploration of the Co-evolutionary Relationship between Human Mind and language, with a Particular Focus of the Self-organisational properties of the Emergence of Symbolic Representation.

Jason Noble, Glyn Hicks (Investigators), Lewys Brace

This work explored the relationship between the origin and subsequent evolution of the human mind and language; a relationship that is believed to be symbiotic in nature. This piece aimed to achieve two objectives. Firstly, it set out a theoretical framework, using the principles of complexity theory and self-organisation, which attempts to explain this relationship from a holistic perspective.

Secondly, it presented an agent-based model of a vervet monkey social group, which sought to investigate the variables that were perceived to underpin the emergence of symbolic representation within a population of language users.

The belief here was that, by understanding the influence of these variables, one would be able to better understand the genesis of the aforementioned relationship.

The tarsal intersegmental reflex control system in the locust hind leg

David Simpson, Philip Newland (Investigators), Alicia Costalago Meruelo

Locomotion is vital for vertebrates and invertebrates to survive. Despite that feet are responsible for stability and agility in most animals, research on feet movements and their reflexes is scarce.
In this thesis, the tarsal reflex responses of locust will be studied and modelled with ANNs to achieve a deeper comprehension of how stability and agility is accomplished.
The choice of ANNs is linked to the applicability of the method into other fields, such as technological designs or medical treatment.

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.

Towards biologically-inspired active-compliant-wing micro-air-vehicles

Richard Sandberg (Investigator), Sonia Serrano-Galiano

Despite a good knowledge of the physiology of bats and birds, engineering applications with active dynamic wing compliance capability are currently few and far between. Recent advances in development of electroactive materials together with high-fidelity numerical/experimental methods provide a foundation to develop biologically-inspired dynamically-active wings that can achieve "on-demand" aerodynamic performance. However this requires first to develop a thorough understanding of the dynamic coupling between the electro-mechanical structure of the membrane wing and its unsteady aerodynamics. In this collaborative initiative between the University of Southampton and Imperial College London, we are developing an integrated research programme that carries out high-fidelity experiments and computations to achieve a fundamental understanding of the dynamics of aero-electro-mechanical coupling in dynamically-actuated compliant wings. The goal is to utilise our understanding and devise control strategies that use integral actuation schemes to improve aerodynamic performance of membrane wings. The long-term goal of this project is to enable the use of soft robotics technology to build integrally-actuated wings for Micro Air Vehicles (MAV) that mimic the dynamic shape control capabilities of natural flyers.

Towards design patterns for robot swarms

Richard Crowder, Seth Bullock (Investigators), Lenka Pitonakova

Swarm robotics is an inter-disciplinary field that seeks to design the behaviour of robots that can cooperate effectively on tasks like search and retrieval, reconnaissance, construction, etc. In this project, we are aiming towards a theoretical understanding of swarm intelligence and the development of design patterns for effective robot swarms.

Towards Exascale computing in particle physics

Andreas Juttner, Jonathan Flynn (Investigators), James Harrison

Lattice QCD

Traveling and movement during European Late Prehistory

Patricia Murrieta Flores

This project has as main purpose to investigate through spatial analysis and computational modelling the variables and factors that influenced how humans traveled during prehistoric times.
One of the principal objectives will be to clarify the role that certain landscape elements (i.e megalithic monuments) played in terrestrial navigation and territorial definition.

This project is supported by CONACYT (Mexico) as a doctoral research by Patricia Murrieta-Flores under the supervision of Dr. David Wheatley (University of Southampton) and Dr. Leonardo Garcia Sanjuan (University of Seville, Spain). It also counts with the collaboration of Dr. Dimitrij Mlekuz (Gent University, Belgium).

Uncertainty quantification and propagation through complex chains of computational models

Dave Woods (Investigator), Stephen Gow

This project will explore how predictions can be made and assessed through complex chains of computer models.

Understanding Stochastic Processes in Interacting Spin Models

Ondrej Hovorka (Investigator), Oliver Laslett

Applying efficient computational models to compute Langevin dynamics and master equation equilibrium solutions for interacting magnetic spin systems.

Understanding the Role of Recruitment in Robot Foraging

Seth Bullock, Richard Crowder (Investigators), Lenka Pitonakova

It is shown that recruitment among foraging robots is useful when resources are hard to find, but that the extra cost associated with such robots is not returned when there are many locations to gather from or simply when the relative gain from using communication is low.

Using MEP to determine parameter values of ocean and atmosphere diffusivity

Kevin Oliver, James Dyke (Investigators), Maike Sonnewald

Entropy budgets can potentially offer new and valuable insights into the dissipation of energy in the ocean system. Specifically, if one assumes the Earth system maximises the dissipation of energy, one can use this as a guiding principle maximising the internal entropy production. In this study, resultant temperature distributions from a four box ocean-atmosphere-ice model are used to assess to what extent such considerations could ameliorate the need for tuning parameter values associated with oceanic and atmospheric diffusivity. Results from a standard implementation with fixed, empirically determined, parameters were compared to one where the maximum entropy production principle is applied to determine the value of oceanic and atmospheric diffusivity parameters. These methods have been successfully applied to cloud fraction and convection in the atmosphere.

The MEP principle suggested using diffusivity values of 3.3×1014 W K −1 and 3.2×1014 W K −1
for the ocean and atmosphere respectively, where the empirical values were 2.0 × 1014 W K −1
and 1.0 × 1014 W K −1 . The oceanic temperatures of the MEP implementation were 3 and -1oC
away the high and low latitude observed ocean temperatures respectively, while the empirical
implementation was -5 and 3oC away, largely within the observational standard deviation of
8 and 2◦ C respectively. For the atmospheric values, MEP implementation was 3W m−2 away
from the high latitude observed value, while the empirical implementation was 6W m−2 away,
both within the standard deviation of 13.2W m−2 . However, in the low latitudes this reverses,
with the empirical implementation being only -16W m−2 off while the MEP implementation
is -21W m−2 off. However, both figures are outside the range of the standard deviation of
4.2W m−2 . Overall, both methods were found to be very close to oceanic observations. This
confirms that in the model used, the assumption of maximal dissipation of energy is reasonable.

Furthermore, the nature of the landscape of internal entropy production created by the
oceanic and atmospheric diffusivity was found to be fairly smooth, with non-linearities mainly
coming from ice albedo. Assuming the Earth system is in a state of maximal energy dissipa-
tion, applying the MEP principle successfully may depend on such a smooth, easily optimisable
landscape. Thus, the successful application of the MEP principle could be much more difficult
if attempting to aid parametrisation in more detailed ocean models, as these are likely to have
internal entropy production landscapes with local maxima. Nevertheless, results presented
are very promising, and encourage further exploration of to what extent this principle could
be applied to ameliorate the need for tuning parameters in light of lacking information.

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.

Validation of GPS-derived water vapour estimates

Joanna Nield, Jason Noble, Edward Milton (Investigators), Robin Wilson

Measurements from GPS base stations can be processed to provide estimates of the water vapour content in the atmosphere. These are lots of these base stations across the world and they take measurements very frequently, making them perfect data sources for scientific use. However, we need to understand their accuracy - and this project aims to do this.

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.

Vibrational spectroscopy from ab initio molecular dynamics

Hans Fangohr, Chris-Kriton Skylaris (Investigators), Valerio Vitale

In this project I used the Fourier transform of the time correlation function (FTTCF) formalism, that allows to compute the vibrational spectra of molecules both in gas and condensed phase, at finite temperature, in a single ab initio molecular dynamics simulation.

Water molecules in drug development: can we predict drug affinity when water molecules are involved?

Jonathan Essex (Investigator), Hannah Bruce Macdonald, Christopher Cave-Ayland

Water molecules are often found to be involved in drug-protein binding and can influence the effectiveness of a drug. We aim to aid drug design by calculating the energies involved with complexes of drugs, proteins and water molecules to predict the affinities of drug molecules.

Wind direction effects on urban flows

Zheng-Tong Xie, Ian Castro (Investigators), Jean Claus

Numerical simulations of turbulent air flow are conducted on Iridis to investigate the effects of different wind directions on the flow within and above an urban-like canopy.