Browsing by Author "Ferrari, Simon"

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    Evolution Surfaces for Spatiotemporal Visualization of Vortex Features
    (2019-09-10) Ferrari, Simon; Hu, Yaoping; Martinuzzi, Robert John
    Turbulent fluid flow data is often 4-dimensional (4D), spatially and temporally complex, and requires specific techniques for visualization. Common visualization techniques neglect the temporal aspect of the data, limiting the ability to convey feature motion or offering the user a complicated visualization. To remedy this, we present an approach – evolution surfaces – focused on the spatiotemporal rendering of user-selected flow features (i.e., vortices). By abstracting the spatial representation of these features, the approach renders their spatiotemporal behavior with reduced visual complexity. The behavior of vortex features are presented as surfaces, with textures indicating properties of motion and evolution events (e.g., bifurcation and amalgamation) represented by the surface topology. We evaluated the approach on two datasets generated from empirical measurement and computational simulation (Re = 28000 and Re = 1200 respectively). Our approach’s focus on handling evolution events makes it capable of visualizing higher Reynolds number (Re) flows than other surface-based techniques. This approach has been assessed by fluid dynamicists to assert the validity for flow analysis. Evolution surfaces offer a compact visualization of spatiotemporal vortex behaviors, opening potential avenues for exploration and analysis of fluid flows.
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    Visualizing 4D Spatiotemporal Vortex Behavior Through Evolution Surfaces
    (2019-03-20) Ferrari, Simon; Hu, Yaoping; Krishnamurthy, Diwakar; Helaoui, Mohamed; Johansen, Craig T.; Boulanger, Pierre
    Turbulent fluid flow data is often 4-dimensional (4D), spatially and temporally complex, and requires specific techniques for visualization. Common visualization techniques neglect the temporal aspect of the data, limiting their ability to convey feature motion. Existing spatiotemporal visualization techniques either do not support 3D vortices, or they must reduce temporal resolution to preserve visual clarity. In sacrificing temporal resolution these techniques can no longer accurately detect or portray feature evolution events. The objective of this thesis is to develop a method to present the spatiotemporal behavior of vortices with a focus on temporal fidelity. To achieve this goal this thesis presents an approach – evolution surfaces – which abstracts the spatial representation of vortices to render their spatiotemporal behavior with reduced visual complexity. The behavior of vortex features are presented as surfaces, with textures indicating properties of motion and evolution events (e.g., bifurcation and amalgamation) represented by the surface topology. This approach has been implemented in a prototype software system and used to examine empirical and computer-simulated turbulent flow datasets ranging from Reynolds number Re = 300 to Re = 86000. Additionally, the reduction in visual complexity offered by evolution surfaces has enabled simultaneous rendering of multiple shedding cycles for analysis of long-term vortex shedding behavior patterns. These results have been compared to existing spatiotemporal visualization techniques using qualitative and quantitative metrics. This approach has been assessed by fluid dynamicists to assert its validity and future potential. Evolution surfaces offer a compact visualization of spatiotemporal vortex behaviors, opening potential avenues for exploration and analysis of turbulent fluid flows.
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    Visualizing three-dimensional vortex shedding through evolution surface clusters
    (2019-11-01) Ferrari, Simon; Hu, Yaoping; Morton, Chris R.; Martinuzzi, Robert John
    Turbulent vortex shedding in the wake of a bluff body often contains cycle-to-cycle variations in the shape, trajectory, and intensity of vortices. Existing flow visualization techniques cannot effectively present these variations and, consequently, their influence on the aerodynamics to the user. This paper explores a new flow visualization approach to represent quasi-periodic vortex shedding over multiple shedding cycles concurrently. This approach uses a reduced-dimension representation of spatiotemporal vortex progression (called evolution surfaces) and ensemble visualization techniques (clustering). The resulting visualization can be used to identify topological changes in the behavior and strengths of coherent structures (i.e. vortices) in unsteady flows. This approach is applied in two case studies of bluff body wakes with Reynolds Numbers Re = 1200 (Hemmati et al. 2016c) and Re = 300 (Morton et al. 2018). In prior work, classification of these wakes’ dynamics was based on energy fluctuation and shedding topology. However, these techniques are not well suited for representing characteristic changes between shedding regimes. In the present work, it has been shown that evolution surface clusters help to identify topological changes characterizing cycle-to-cycle variations in vortex behavior, while reducing visual clutter. The results indicate that evolution surface clusters are a promising visualization tool for comparative analysis of unsteady vortex dynamics in turbulent wakes.