Computational Modelling Group

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'.

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.

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.

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.

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.

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.

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) 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.

Optical Characterisation of Black Silicon for Photovoltaics Using the Finite Element Method

Jack Tyson (Investigator)

Here we present a novel method of simulating the reflectance spectra of black silicon solar cells using the finite element method. Designed in COMSOL Multiphysics is a new set of algorithm-controlled-geometries rendering a vast array of different structural permutations of silicon nanowires. Our model focused on the variation of this geometry within customisable predefined conditions in large output quantities, collated and averaged to reliably determine the reflectance of an entire black silicon solar cell.

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.

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.

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.

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 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!

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.