Visiometrics of complex physical processes:
Diagnosing vortex dominated flows
Victor M. Fernandez 
, Norman J. Zabusky and Deborah Silver 
Department of Mechanical and Aerospace Engineering and CAIP
Center,
Rutgers University, Piscataway, NJ 08855
Department of Electrical and Computer Engineering and CAIP
Center,
Rutgers University, Piscataway, NJ 08855
We present applications of the visiometrics approach, which
emphasizes the quantification of diagnostics to obtain physical
insight into complex physical processes. This methodology is applied
to study both the vortex collapse problem via Biot-Savart reduced
models as well as the exploration of Navier-Stokes turbulence direct
simulations with a 
mesh resolution. The feature extraction and
data reduction algorithms introduced provide insight into the types
of problems that arise in dealing with very large datasets. The
developed tools are based on thresholding, object segmentation and low
order ellipsoidal representations and are applied to searching
coherent vortex structures associated with maxima events in the
turbulence field. In addition, we emphasize the importance of sharing
tasks between supercomputers and workstations, where each machine may
work more efficiently at different stages of the data processing. We
have obtained visualizations that show the structure of the dominant
coherent objects in the turbulent flow. The reduced representations
employed make it possible to examine different types of fields for
possible correlations. The quantification of the objects identified by
the feature extraction algorithms, should contribute to the building
of models that consider both coherent structures and the random
background observed in Navier-Stokes turbulence.