Computational Modelling Group

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 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'.

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.

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.

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.

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.

Benchmarking the GOPHER orthologue prediction algorithm.

Richard Edwards, Shaun Maguire

Generation of Orthologous Proteins from High-throughput Evolutionary Relationships (GOPHER) is an orthologue prediction algorithm. This experiment aims to benchmark this algorithm.

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.

BRECcIA - Building REsearch Capacity for sustainable water and food security In sub-saharan Africa

The BRECcIA project is aimed at developing research and researchers to understand water and food security challenges in sub-Saharan Africa

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, Thorsten Wittemeier, Kieran Selvon, Alvaro Perez-Diaz, David Lusher, Ashley Setter, Emanuele Zappia, Hossam Ragheb, Ryan Pepper, Stephen Gow, Jan Kamenik, Paul Chambers, Robert Entwistle, Rory Brown, Joshua Greenhalgh, James Harrison, Jonathon Waters, Ioannis Begleris, Craig Rafter

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

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

Challenging Topological Prejudice - Automated Airframe Layout Design

Andras Sobester (Investigator), Paul Chambers

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

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

Characterisation of the Genomic Landscape in Splenic Marginal Zone Lymphoma

Sarah Ennis, Jane Gibson, Jon Strefford (Investigators), Carolina Jaramillo Oquendo, Helen Parker

This project aims to expand the catalogue of mutated genes in splenic marginal zone lymphoma (SMZL) and construct a detailed characterisation of the genetic landscape of this disease. Using next generation sequencing, we aim to identify somatic mutations in over 100 samples, and enrich clinical data with this information to improve patient treatment and prognosis.

Colonising Polynesia; Uncertain sailing craft route modelling

Thomas Dickson (Investigator), David Sear

Through developing a novel methodology of modelling sailing craft routing it is possible to investigate archaeological problems as well as applications to modern yacht racing and autonomous sailing technology. This research uses iridis to provide accurate and fast analysis of shortest path routes for sailing craft in order to provide insight and improve safety of operation.

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.

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.

Data Science and HPC

Are Data science and HPC really different fields or are people just repackaging old ideas with new words.

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.

Designer 3D Magnetic Mesostructures

Hans Fangohr (Investigator), Matteo Franchin, Andreas Knittel

A new electrodeposition self-assembly method allows for the growth of well defined mesostructures. This project's aim is to use this method in order to fabricate supraconducting and ferromagnetic mesostructures. Numerical methods based on well-established models are used in order to characterise the grown structures.

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.

Directing magnetic skyrmion traffic flow with nanoscale patterning.

Hans Fangohr (Investigator), Mark Vousden

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

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.

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.

Feasibility Study of the Impacts of Proposed Tidal Array Installations in Channel Islands

Luke Blunden (Investigator), William Batten

Open source hydrodynamic modelling software TELEMAC is being used to see whether putting a large number of tidal turbines in the sea near a headland-associated sandbank will affect the feature's long term equilibrium.

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.

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?”

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.

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.

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.

Hunting for Walking Technicolor at the LHC

Alexander Belyaev (Investigator), Azaria Coupe

Now that the LHC experiment at CERN has observed the Higgs boson, the final piece of the particle physics theory called the Standard Model, the focus of theoretical and experimental physicists shifts to what could possibly be discovered next. Phenomenologists, such as myself, straddle this line between theory and experiment, comparing the many theories of physics Beyond the Standard Model to whatever the LHC discovers, even drawing conclusions from what it doesn’t discover. I focus on a theory called Walking Technicolor (WTC), what the LHC would see if it were correct, and what the lack of discovery so far means for the fate of WTC.

Identification of Gene-Modules Associated to a Predisposition of Post-Traumatic Stress Disorder

Christopher Woelk (Investigator), Michael Breen

The predisposing genetic factors associated to Post-Traumatic Stress Disorder (PTSD) are altogether unknown. Since not all trauma-survivors later develop the PTSD, it has been hypothesized that transcript differentiation prior–to-trauma exposure could be associated to the risk and resilience of PTSD. We apply a systems-level approach to investigate changes in transcript abundance (gene expression profiles) in whole blood of U.S. Marines sampled prior-to-deployment to the battlefield and followed through-out a seven month deployment to obtain disorder related outcomes.

Identification of novel Crustacean Pathogen Receptor Proteins

Richard Edwards, Chris Hauton, Timothy Elliott (Investigators), Oyindamola Lawal, Lloyd Mushambadzi

We are mining EST libraries (sequence fragments of expressed genes) for novel proteins that might play a role in the immune response of crustaceans.

Identification of phage DNA, common insertion sites and their effect on genes within S.pneumoniae

Richard Edwards, Amy Dean

This study seeks to find if there are any common insertion sites across different strains of S.pneumoniae and discover genes that undergo frequent mutation due to phages and if these mutations can be linked to virulence of the strains.

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.

Interactome-wide prediction of short linear protein interaction motifs in humans

Richard Edwards (Investigator)

Short Linear Motifs (SLiMs) are important in many protein-protein interactions. In previous work, we have developed a computational tool, SLiMFinder, which places the interpretation of evidence for motifs within a statistical framework with high specificity, and subsequently enhanced sensitivity through application of conservation-based sequence masking. We are now applying these tools to a comprehensive set of human protein-protein interactions in order to predict novel human SLiMs in silico.

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.

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.

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).

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.

Life assessment methods for industrial steam turbine blade to disc interfaces

Katherine Soady (Investigator)

This is an EngD project sponsored by E.ON New Build and Technology Ltd. which aims to develop the methods currently implemented in life assessment of industrial steam turbine blade to disc interfaces to take account of the surface treatment process (shot peening) which is applied to component before service and after repair.

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.

Mass Spec identification of proteins utilising EST libraries

Richard Edwards, Maria Debora Iglesias-Rodriguez (Investigators), Bethan Jones

Expressed Sequence Tag (EST) data presents a particular challenge for the identification of proteins using mass spectrometry (MS): it is often redundant (multiple copies of the same gene), consists primarily of short fragments of coding sequence, contains many sequencing errors and is generally poorly annotated. We are developing computational pipelines to maximise robust protein identifications from EST data despite these challenges.

Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction

Mahesan Niranjan, Andrew Collins, Reuben Pengelly (Investigators)

This iPhD project uses a Gaussian Bayesian Networks framework through Machine learning methods to predict which genes are involved in the development of different diseases.

Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction

Mahesan Niranjan, Andrew Collins, Reuben Pengelly (Investigators)

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

Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction

Andrew Collins, Mahesan Niranjan, Reuben Pengelly (Investigators), Alejandra Vergara Lope

This iPhD project uses a Gaussian Bayesian Networks approaches framework through machine learning approach to predict which genes are involved in the development of different diseases.

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?

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 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 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.

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).

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 biological membranes

Jonathan Essex (Investigator), Mario Orsi

Biological membranes are complex and fascinating systems, characterised by proteins floating in a sea of lipids. Biomembranes, besides being the fundamental structures employed by nature to encapsulate cells, play crucial roles in many phenomena indispensable for life, such as growth, energy storage, and in general information transduction via neural activity. In this project, we develop and apply multiscale computational models to simulate biological membranes and obtain molecular-level insights into fundamental structures and phenomena.

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 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 (Investigator), 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.

nano-CMOS

Mark Zwolinski (Investigator), Michael Merrett

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

NGCM-0054 - Automatic Code Generation for Computational Science

Hans Fangohr (Investigator), Gary Downing

Automatically generate code to solve partial differential equations specified symbolically.

Nmag - computational micromagnetics

Hans Fangohr, Thomas Fischbacher (Investigators), Matteo Franchin, Andreas Knittel, Maximilian Albert, Dmitri Chernyshenko, Massoud Najafi, Richard Boardman

Nmag is a micromagnetic simulation package based on the general purpose multi-physics library nsim. It is developed by the group of Hans Fangohr and Thomas Fischbacher in the School of Engineering Sciences at the University of Southampton and released under the GNU GPL.

Nmag finite difference

Hans Fangohr (Investigator), Dmitri Chernyshenko, Matteo Franchin, Massoud Najafi

The goal of this project is to extends the finite element based micromagnetic simulation tool Nmag by the finite difference based extension Nmagfd and so to get an simulation tool where the user can easily switch between the used discretization method.

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.

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.

Numerical investigation of the true sources of jet noise

Anurag Agarwal (Investigator), Samuel Sinayoko

Aircraft noise severely impacts the quality of life of people living close to airports. Noise generation by aircrafts is especially large during take-off. Jet noise is the dominant noise source during take-off. It is produced by the high speed flow generated by the engine. However, the actual source of sound remains unknown. A deeper understanding of the sources of jet noise is need to be able to reduce the noise. The aim of this project is to implement a innovative method that would allow to identify the sources of jet noise.

OpenDreamKit

Hans Fangohr (Investigator), Marijan Beg

OpenDreamKit is a [Horizon 2020](https://ec.europa.eu/programmes/horizon2020/) European Research Infrastructure project (#676541) providing 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.

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?

Predicting Relative Protein Abundance via Sequence-Based Information

Gregory Parkes (Investigator), Mahesan Niranjan

Understanding the complex interactions between transcriptome and proteome is essential in uncovering cellular mechanisms both in health and disease contexts. The limited correlations between corresponding transcript and protein abundance suggest that regulatory processes tightly govern information flow surrounding transcription and translation, and beyond.

In this study we adopt an approach which expands the feature scope that models the human proteome: we develop machine learning models that incorporate sequence-derived features (SDFs), sometimes in conjunction with corresponding mRNA levels. We develop a large resource of sequence-derived features which cover a significant proportion of the H. sapiens proteome, demonstrate which of these features are significant in prediction on multiple cell lines, and suggest insights into which biological processes can be explained using these features.

We reveal that (a) SDFs are significantly better at protein abundance prediction across multiple cell lines both in steady-state and dynamic contexts, (b) that SDFs can cover the domain of translation with relative efficiency but struggle with cell-line specific pathways and (c) provide a resource which can be plugged into many subsequent protein-centric analyses.

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.

Real-time CFD for helicopter flight simulation

Kenji Takeda (Investigator), James Kenny

Project aims to show how real-time computational fluid dynamics (CFD) could be used to improve the realism of helicopter flight simulators.

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.

Reversal of ferromagnetic nanotubes

Hans Fangohr (Investigator), David Cortes

We are analysing the feasibility of reversing a nano scaled magnetic tube by applying weak pulses of currents through the nano-tube inner core

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.

Selection pressure for language and theory-of-mind in monkeys

Jason Noble (Investigator)

To what extent are the alarm calls of putty-nosed monkeys likely to be a good model for human language evolution? Simulation is used to classify evolutionary trajectories as either plausible or implausible, and to put lower bounds on the cognitive complexity required to perform particular behaviours.

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).

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 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 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.

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 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.

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.

Statistical model of the knee

Mark Taylor (Investigator), Francis Galloway, Prasanth Nair

Development of methods for large scale computational testing of a tibial tray incorporating inter-patient variability.

Structured low-rank approximation

Ivan Markovsky

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

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.

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.

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 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 effect of roughness upon turbulent supersonic flows

Neil Sandham (Investigator), Christopher Tyson

Understanding the interaction between surface roughness and supersonic air flows are crucial in the design of high speed vehicles, including space re-entry vehicles. Numerical simulations of these flows has been conducted in order to examine and understand how the surface roughness interacts with high speed flows in terms of drag prediction and heat transfer to the wall surface.

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.

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.

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).

Understanding Stochastic Processes in Interacting Spin Models

Oliver Laslett

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

Using Molecular Dynamics to Understand the Antibacterial Mechanisms of Daptomycin & Chlorhexidine to Target the Bacterial Membrane

This project aims to use molecular dynamics techniques to understand how antimicrobial peptides, daptomycin and chlorhexidine, disrupt both gram positive and negative cell membranes on an atomic level.

Using Molecular Dynamics to Understand the Antibacterial Mechanisms of Daptomycin & Chlorhexidine to Target the Bacterial Membrane

This project aims to use molecular dynamics techniques to understand how antimicrobial peptides, daptomycin and chlorhexidine, disrupt both gram positive and negative cell membranes on an atomic level.

Using Molecular Dynamics to Understand the Antibacterial Mechanisms of Daptomycin & Chlorhexidine to Target the Bacterial Membrane

Syma Khalid (Investigator), Eilish McBurnie

This project aims to use molecular dynamics techniques to understand how antimicrobial peptides, daptomycin and chlorhexidine, disrupt both gram positive and negative cell membranes on an atomic level.

Vortex Dynamics in High-Tc superconductors

Hans Fangohr (Investigator)

The dynamics of vortices in high temperature superconductors exhibits the complex and rich physics we expect from many body systems with competing interactions. Molecular Dynamics, Langevin Dynamics and Monte Carlo Computer simulations are carried out to understand this system in more detail.

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.

µ-VIS Computed Tomography Centre

Ian Sinclair, Richard Boardman, Dmitry Grinev, Philipp Thurner, Simon Cox, Jeremy Frey, Mark Spearing, Kenji Takeda (Investigators)

A dedicated centre for computed tomography (CT) at Southampton, providing complete support for 3D imaging science, serving Engineering, Biomedical, Environmental and Archaeological Sciences. The centre encompasses five complementary scanning systems supporting resolutions down to 200nm and imaging volumes in excess of one metre: from a matchstick to a tree trunk, from an ant's wing to a gas turbine blade.