Gearld-Yamasaki, Michael

NASA NTRS1998

Automatic Vortex Core Detection

An eigenvector method for vortex identification has been applied to recent numerical and experimental studies in external flow aerodynamics. This paper shows that it is an effective way to extract and visualize features such as vortex cores, spiral vortex breakdowns, and vortex bursts. The algorithm has also been incorporated in a finite element flow solver to guide an automatic mesh refinement program. Results show that this approach can resolve small scale vortical structures in helicopter rotor simulations which are not captured on coarse meshes.

Kenwright, David↗

NASA NTRS1998

Feature Detection in Linked Derived Spaces

This paper describes by example a strategy for plotting and interacting with data in multiple metric spaces. The example system was designed for use with time-varying computational fluid dynamics (CFD) datasets, but the methodology is directly applicable to other types of field data. The central objects embodied by the tool are {\em portraits}, which show the data in various coordinate systems, while preserving their spatial connectivity and temporal variability. The coordinates are derived in various ways from the field data, and an important feature is that new and derived portraits can be created interactively. The primary operations supported by the tool are brushing and linking: the user can select a subset of a given portrait, and this subset is highlighted in all portraits. The user can combine highlighted subsets from an arbitrary number of portraits with the usual logical operators, thereby indicating where an arbitrarily complex set of conditions holds. The system is useful for exploratory visualization and feature detection in multivariate data.

Henze, Chris↗