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Stochastic Volume Rendering of Multi-Phase SPH Data [in press]

Piochowiak, Max; Rapp, Tobias; Dachsbacher, Carsten

In this paper, we present a novel method for the direct volume rendering of large smoothed‐particle hydrodynamics (SPH) simulation data without transforming the unstructured data to an intermediate representation. By directly visualizing the unstructured particle data, we avoid long preprocessing times and large storage requirements. This enables the visualization of large, time‐dependent, and multivariate data both as a post‐process and in situ. To address the computational complexity, we introduce stochastic volume rendering that considers only a subset of particles at each step during ray marching. The sample probabilities for selecting this subset at each step are thereby determined both in a view‐dependent manner and based on the spatial complexity of the data. Our stochastic volume rendering enables us to scale continuously from a fast, interactive preview to a more accurate volume rendering at higher cost. Lastly, we discuss the visualization of free‐surface and multi‐phase flows by including a multi‐material model with volumetric and surface shading into the stochastic volume rendering.

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Verlagsausgabe §
DOI: 10.5445/IR/1000126034
Veröffentlicht am 17.11.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Visualisierung und Datenanalyse (IVD)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 0167-7055, 1467-8659
KITopen-ID: 1000126034
Erschienen in Computer graphics forum
Vorab online veröffentlicht am 27.10.2020
Nachgewiesen in Scopus
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