High performance computing for challenging problems in computational fluid dynamics

Lawson, S. J., Woodgate, M., Steijl, R. and Barakos, G. N. (2012) High performance computing for challenging problems in computational fluid dynamics. Progress in Aerospace Sciences, 52, pp. 19-29. (doi:10.1016/j.paerosci.2012.03.004)

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Abstract

High Performance Computing (HPC) is necessary in the analysis of complex flows using Computational Fluid Dynamics (CFD) since it allows problems to be tackled within realistic time scales or it allows for new problems to be explored. In recent years, the exponential growth of computing performance was also combined with the increasing availability of large scale computing resources, for the benefit of the CFD research. In this paper, two challenging problems are presented using time-marching methods: the flow inside a cavity exposed to a high-speed flow and the flow around a helicopter landing on a ship. All flow cases presented here needed the use of supercomputing resources, such as the UK High-End Computing Tera-scale Resource (HECToR) or the JUROPA system at Juelich, Germany. The use of fine grids for the first case allowed for the details of the flow to be revealed at a level sufficient for engineering analysis. In addition, the fundamental mechanism of the interaction between pressure waves and shear layer along the cavity opening was revealed for the first time in computational results. To the knowledge of the authors, the second case of the helicopter ship landing has been attempted for the first time, and the results presented here help to show the benefits of HPC in this area of research.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Barakos, Professor George and Woodgate, Dr Mark and Steijl, Dr Rene
Authors: Lawson, S. J., Woodgate, M., Steijl, R., and Barakos, G. N.
College/School:College of Science and Engineering > School of Engineering > Aerospace Sciences
Journal Name:Progress in Aerospace Sciences
Publisher:Elsevier Ltd.
ISSN:0376-0421
ISSN (Online):1873-1724

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