Imperial College London

Professor Peter Vincent

Faculty of EngineeringDepartment of Aeronautics

Professor of Computational Fluid Dynamics
 
 
 
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Contact

 

+44 (0)20 7594 1975p.vincent

 
 
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Location

 

211City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Koch:2019:10.1109/LDAV.2018.8739233,
author = {Koch, MK and Kelly, PHJ and Vincent, PE},
doi = {10.1109/LDAV.2018.8739233},
pages = {104--105},
publisher = {Institute of Electrical and Electronics Engineers},
title = {Towards in-situ vortex identification for peta-scale CFD using contour trees},
url = {http://dx.doi.org/10.1109/LDAV.2018.8739233},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - Turbulent flows exist in many fields of science and occur in a wide range of engineering applications. While in the past broad knowledge has been established regarding the statistical properties of turbulence at a range of Reynolds numbers, there is a lack of under-standing of the detailed structure of these flows. Since the physical processes involve a vast number of structures, extremely large data sets are required to fully resolve a flow field in both space and time. To make the analysis of such data sets possible, we propose a frame-work that uses state-of-the-art contour tree construction algorithms to identify, classify and track vortices in turbulent flow fields produced by large-scale high-fidelity massively-parallel computational fluid dynamics solvers such as PyFR. Since disk capacity and I/O have become a bottleneck for such large-scale simulations, the proposed framework will be applied in-situ, while relevant data is still in device memory.
AU - Koch,MK
AU - Kelly,PHJ
AU - Vincent,PE
DO - 10.1109/LDAV.2018.8739233
EP - 105
PB - Institute of Electrical and Electronics Engineers
PY - 2019///
SP - 104
TI - Towards in-situ vortex identification for peta-scale CFD using contour trees
UR - http://dx.doi.org/10.1109/LDAV.2018.8739233
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000480379800017&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/73764
ER -