Computational Modelling Group

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.

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.

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.

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.

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.

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.

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).

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.

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.