A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications

Franz Sauer, Jinrong Xie, Kwan-Liu Ma

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a 'unit cell' based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

Original languageEnglish (US)
Article number7676418
Pages (from-to)2248-2261
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Volume23
Issue number10
DOIs
StatePublished - Oct 1 2017

Keywords

  • data structures
  • Flow visualization
  • large-scale data
  • multi-resolution
  • particle data
  • volume data

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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