Data Management

Both experimental measurements and simulation results can produce substantial amounts of data that need to be postprocessed, analysed, and stored for archival or subsequent analysis at a later point. Databases are good at storing relatively small amounts of data with logical connections but often simulation or experimental data sets are very large (of the order of gigabytes (GB) or terabytes (TB)).

Depending on the cost of an experiment of the cost of performing a computer simulation, the resulting data need to be stored and made available, using different hardware, software and networking technologies.

Image: 512MB Harddisk source

For queries about this topic, contact Richard Boardman.

View the calendar of events relating to this topic.

Projects

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'.

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.

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.

Assessment of the performance of novel RANS and hybrid turbulence models on the flow around a cylinder

Manuel Diaz Brito

The turbulent flow around a circular cylinder is a widely studied problem in fluid dynamics. At a certain characteristic Reynolds numbers the development of a turbulent wake occurs simultaneously with separation of the laminar boundary layer. The mechanisms defining this critical flow state are very complex to predict computationally. In this project the suitability of novel non-linear eddy viscosity closures and a hybrid Flow Simulation Methodology formulation to face these massively separated flows is studied. The flow predicting capabilities of the baseline EASM, ?-?-EASM and FSM-?-?-EASM tested are contrasted with the industrial renowned k-?-SST turbulence model. In the visualisation of the results it is evident that the ?-?-EASM has greater flexibility estimating the components of the Reynolds stresses with respect to the baseline EASM and the k-?-SST. Although dome differences are observed, the prediction of the critical flow around a cylinder is not accurately achieved by any of these RANS models, but the FSM-?-?-EASM shows great resemblance with the validation data, demonstrating capabilities of resolving very complex flow phenomena with minimum user input if the computational grid is fine enough. In order to demonstrate even greater advantages of non-linear models it was postulated that the addition of a streamwise impinging vortex hitting the leading edge of the cylinder would make the flow field fully three-dimensional. First attempts were tried in this route but time constraints limited the ultimate scope of the present work.

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.

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.

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.

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.

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.

Population24/7: space-time specific population surface modelling

Samantha Cockings, David Martin, Samuel Leung (Investigators)

Project funded by Economic and Social Research Council to compute time-specific geographical representations of population distribution.

Prediction of Psychopathology by MRT data

We aim to predict psychopathological outcomes in adults by functional brain data using multilevel regression and crossvaligdation strategies.

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.

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!

Study of global instability in separated flows at high Mach number

Neil Sandham, Zhiwei Hu (Investigators), Kangping Zhang

Flow instability is observed when extending two-dimensional (2D) stable flow into three-dimensional (3D). Development of instability varies along different spanwise length. Thresholds are also discovered for the flow studied to become instable.

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.

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.

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.