Separation and attachment lines are topologically significant curves that exist on 2D surfaces in 3D vector fields. Two algorithms are presented, one point-based and one element-based, that extract separation and attachment lines using eigenvalue analysis of a locally linear function. Unlike prior techniques based on piecewise numerical integration, these algorithms use robust analytical tests that can be applied independently to any point in a vector field. The feature extraction is fully automatic and suited to the analysis of large-scale numerical simulations. The strengths and weaknesses of the two algorithms are evaluated using analytic vector fields and also results from computational fluid dynamics (CFD) simulations. We show that both algorithms detect open separation lines-a type of separation that is not captured by conventional vector field topology algorithms.

A fully automatic feature detection algorithm is presented that locates and distinguishes lines of flow separation and attachment on surfaces in 3D numerical flow fields. The algorithm is based on concepts from 2D phase-plane analysis of linear vector fields. Unlike prior visualization techniques based on particle tracing or flow topology, the phase-plane algorithm detects separation using local analytic tests. The results show that it not only detects the standard closed separation lines but also the illusive open separation lines which are not captured by flow topology methods.

An eigenvector method for vortex identification has been applied to recent numerical and experimental studies in external flow aerodynamics. It is shown to be an effective way to extract and visualize features such as vortex cores, spiral vortex breakdowns, vortex bursting, and vortex diffusion. Several problems are reported and illustrated. These include: disjointed line segments, detecting non-vortical flow features, and vortex core displacement. Future research and applications are discussed, such as using vortex cores to guide automatic grid refinement.

The paper describes the Field Encapsulation Library (FEL), which provides a grid independent application programmer's interface to gridded three dimensional field data. The C++ implementation of FEL is described, stressing the way in which the class hierarchy hides the underlying grid structure in a way that allows visualization algorithms to be written in a completely grid independent manner. Appropriately defined coordinate classes play an important role in providing this grid independence. High performance point location routines for data access are described and performance times are provided.

Streak lines and particle traces are effective visualization techniques for studying unsteady fluid flows. For real time applications, accuracy is often sacrificed to achieve interactive frame rates. Physical space particle tracing algorithms produce the most accurate results although they are usually too expensive for interactive applications. An efficient physical space algorithm is presented which was developed for interactive investigation and visualization of large, unsteady, aeronautical simulations. Performance has been increased by applying tetrahedral decomposition to speed up point location and velocity interpolation in curvilinear grids. Preliminary results from batch computations showed that this approach was up to six times faster than the most common algorithm which uses the Newton-Raphson method and trilinear interpolation. Results presented show that the tetrahedral approach also permits interactive computation and visualization of unsteady particle traces. Statistics are given for frame rates and computation times on single and multiprocessors. The benefits of interactive feature detection in unsteady flows are also demonstrated.

An efficient algorithm is presented for computing particle paths, streak lines and time lines in time-dependent flows with moving curvilinear grids. The integration, velocity interpolation, and step size control are all performed in physical space which avoids the need to transform the velocity field into computational space. This leads to higher accuracy because there are no Jacobian matrix approximations, and expensive matrix inversions are eliminated. Integration accuracy is maintained using an adaptive step size control scheme which is regulated by the path line curvature. The problem of point location and interpolation in physical space is simplified by decomposing hexahedral cells into tetrahedral cells. This enables the point location to be done analytically and substantially faster than with a Newton-Raphson iterative method. Results presented show this algorithm is up to six times faster than particle tracers which operate on hexahedral cells, and produces almost identical traces.

A methodology has been developed for constructing streamlines and particle paths in numerically generated fluid velocity fields. A graphical technique is used to convert the discretely defined flow within a cell into one represented by two three-dimensional stream functions. Streamlines are calculated by tracking constant values of each stream function, a process which corresponds to finding the intersection of two stream surfaces. The tracking process is mass conservative and does not use a time stepping method for integration, thus eliminating a computationally intensive part of traditional tracking algorithms. The method can be applied generally to any three-dimensional compressible or incompressible steady flow. Results presented compare the performance of the new method to the most commonly used scheme and show that calculation times can be reduced by an order of magnitude.>