TY - GEN
T1 - A multistage vortex visualization method
AU - Jankun-Kelly, M.
AU - Thompson, D. S.
AU - Brewer, W.
AU - Jiang, M.
AU - Machiraju, R.
PY - 2006
Y1 - 2006
N2 - In order to understand complex vortical flows in large data sets, we must be able to detect and visualize vortices in an automated fashion. Additionally, an informative vortex visualization should provide more information that just the location of the vortex core. In this paper, we describe a multistage vortex visualization algorithm that attempts to exploit the availability of additional information to convey vortex characteristics such as core position, extent, strength, etc. The results produced by a traditional vortex detection algorithm are enhanced using a set of postprocessing tools. The multistage visualization method can use the results of any field-based vortex detection technique in which the scalar field has an extrema in the vortex core or can use the results of any method which produces a continuous vortex core line. This flexibility allows the user to select a vortex detection algorithm appropriate for the problem at hand. Our method works on unstructured meshes as well as structured grids and avoids the use of the computationally expensive and potentially nonsmooth gradient during core line extraction and characterization. Its ability to discern both weak and strong vortices as well as vortices in close spatial proximity to each other is another advantage which comes from the use of the local extrema method. Further, our method obtains subcell resolution of the vortex core line through the use of function fitting. We demonstrate the efficacy of our approach by applying it to several test cases. These test cases highlight the strengths and weaknesses of the method. We describe how the algorithm can be improved and draw conclusions based on the results presented herein.
AB - In order to understand complex vortical flows in large data sets, we must be able to detect and visualize vortices in an automated fashion. Additionally, an informative vortex visualization should provide more information that just the location of the vortex core. In this paper, we describe a multistage vortex visualization algorithm that attempts to exploit the availability of additional information to convey vortex characteristics such as core position, extent, strength, etc. The results produced by a traditional vortex detection algorithm are enhanced using a set of postprocessing tools. The multistage visualization method can use the results of any field-based vortex detection technique in which the scalar field has an extrema in the vortex core or can use the results of any method which produces a continuous vortex core line. This flexibility allows the user to select a vortex detection algorithm appropriate for the problem at hand. Our method works on unstructured meshes as well as structured grids and avoids the use of the computationally expensive and potentially nonsmooth gradient during core line extraction and characterization. Its ability to discern both weak and strong vortices as well as vortices in close spatial proximity to each other is another advantage which comes from the use of the local extrema method. Further, our method obtains subcell resolution of the vortex core line through the use of function fitting. We demonstrate the efficacy of our approach by applying it to several test cases. These test cases highlight the strengths and weaknesses of the method. We describe how the algorithm can be improved and draw conclusions based on the results presented herein.
UR - http://www.scopus.com/inward/record.url?scp=34250787696&partnerID=8YFLogxK
U2 - 10.2514/6.2006-946
DO - 10.2514/6.2006-946
M3 - Conference contribution
AN - SCOPUS:34250787696
SN - 1563478072
SN - 9781563478079
T3 - Collection of Technical Papers - 44th AIAA Aerospace Sciences Meeting
SP - 11322
EP - 11336
BT - Collection of Technical Papers - 44th AIAA Aerospace Sciences Meeting
PB - American Institute of Aeronautics and Astronautics Inc.
T2 - 44th AIAA Aerospace Sciences Meeting 2006
Y2 - 9 January 2006 through 12 January 2006
ER -