Importance-Driven Particle Techniques for Flow Visualization

Abstract

Particle tracing has been established as a powerful visualization technique to show the dynamics of 3D flows. Particle tracing in 3D, however, quickly overextends the viewer due to the massive amount of visual information that is typically produced by this technique. In this paper, we present strategies to reduce this amount at the same time revealing important structures in the flow. As an importance measure, we introduce a simple, yet effective clustering approach for vector fields, and we use scalar flow quantities at different scales in combination with user-defined regions of interest. These measures are used to control the shape, the appearance, and the density of particles in such a way that the user can focus on the dynamics in important regions at the same time preserving context information. We also introduce a new focus for particle tracing, so called anchor lines. Anchor lines are used to analyze local flow features by visualizing how much particles separate over time and how long it takes until they have separated to a fixed distance. It is of particular interest if the finite time Lyapunov exponent -a scalar quantity that measures the rate of separation of infinitesimally close particles in the flow -is used to guide the placement of anchor lines. The effectiveness of our approaches for the visualization of 3D flow fields is validated using synthetic fields as well as real simulation data.they generate a representation of the entire field. Even by using advanced visualization options like halos [11], transfer functions and clipping geometries [21], and flow-guided importance measures [31], it has been shown difficult to overcome these limitations without loosing relevant information.

Time‐Dependent 2‐D Vector Field Topology: An Approach Inspired by Lagrangian Coherent Structures

“…Haller [Hal01] has shown that they can be formulated as ridges in the field of the finite‐time Lyapunov exponent [Hal01] (FTLE), measuring the divergence of trajectories, and Lekien et al [LCM*05] have confirmed that LCS behave as material lines (in 2‐D) or material surfaces (in 3‐D). The FTLE‐based approach has recently attracted much interest in the visualization community [BKKW08, STM08], however, it does not in an intrinsic way single out special points, classify them, and characterize their neighbourhood. There is however such a classification for material lines and surfaces, due to Haller [Hal01].…”

Autonomous Particles for Interactive Flow Visualization

“…Observing moving particles is a powerful way to experience a flow [BKKW08]. To facilitate this experience for a large class of different flows has been the main motivation for our work.…”

“…Later they introduced an importance driven scale‐space approach to target visual clutter and information overload in the work of Bürger et al . [BKKW08]. As a different application, Van Pelt et al .…”

Evaluating Sampling Strategies for Visualizing Uncertain Multi-Phase Fluid Simulation Data

“…Botchen et al [7] presented a texturebased method using blurred streaklines to convey uncertainty information in two-dimensional flow fields obtained from measurements. A focus-and-context flow visualization method was presented by Bürger et al [8], who combined spatial importance measures with particle glyphs. Specifically for Method of Moments-based simulations, Hlawitschka et al [9] and Hummel et al [10] proposed a visualization approach featuring sampling in addition to parametric bubble glyphs, which were shaped according to local flow properties.…”