Immersive isosurface visualisation for engineering datasets

Kadek Ananta Satriadi, Kingsley Stephens, Callum Atkinson, Maxime Cordeil, Tobias Czauderna

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

The visualisation of isosurfaces is an important step towards the understanding of many physical phenomena. Physical simulations produce large amounts of quantitative numerical information which need to be interpreted by domain experts. Traditionally, researchers use standard tools to create isosurface visualisations from fluid simulations and extract knowledge. With the recent evolution of display technology, it is now possible to create immersive visualisations of such data. Benefits include a higher bandwidth of communication between the data and the user, e. g., by using stereoscopic display technology and head tracking. Since the data is intrinsically 3D spatial, the use of the immersive environment supports natural visualisation, exploration, and analysis of isosurfaces. In this paper, we present the study and the design of a method and a workflow to display isosurfaces in heterogeneous immersive environments. In particular, we address the problem of scale and structure inherent to this type of data. We provide a set of tools to process large volume datasets to eventually display it in 3D immersive environments. We demonstrate the workflow of tools with a usage scenario that involves a dataset from direct numerical simulation of a wall-bounded turbulent flow.

LanguageEnglish
Title of host publication2017 International Symposium on Big Data Visual Analytics (BDVA)
EditorsWolfgang Mayer, Michael Wybrow
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-8
Number of pages8
ISBN (Electronic)9781538607817, 9781538607800
DOIs
Publication statusPublished - 17 Nov 2017
EventInternational Symposium on Big Data Visual Analytics 2017 - Adelaide, Australia
Duration: 7 Nov 201710 Nov 2017
http://bdva.net/2017/

Conference

ConferenceInternational Symposium on Big Data Visual Analytics 2017
Abbreviated titleBDVA 2017
CountryAustralia
CityAdelaide
Period7/11/1710/11/17
Internet address

Cite this

Satriadi, K. A., Stephens, K., Atkinson, C., Cordeil, M., & Czauderna, T. (2017). Immersive isosurface visualisation for engineering datasets. In W. Mayer, & M. Wybrow (Eds.), 2017 International Symposium on Big Data Visual Analytics (BDVA) (pp. 1-8). [8114624] Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BDVA.2017.8114624
Satriadi, Kadek Ananta ; Stephens, Kingsley ; Atkinson, Callum ; Cordeil, Maxime ; Czauderna, Tobias. / Immersive isosurface visualisation for engineering datasets. 2017 International Symposium on Big Data Visual Analytics (BDVA). editor / Wolfgang Mayer ; Michael Wybrow. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 1-8
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Satriadi, KA, Stephens, K, Atkinson, C, Cordeil, M & Czauderna, T 2017, Immersive isosurface visualisation for engineering datasets. in W Mayer & M Wybrow (eds), 2017 International Symposium on Big Data Visual Analytics (BDVA)., 8114624, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 1-8, International Symposium on Big Data Visual Analytics 2017, Adelaide, Australia, 7/11/17. https://doi.org/10.1109/BDVA.2017.8114624

Immersive isosurface visualisation for engineering datasets. / Satriadi, Kadek Ananta; Stephens, Kingsley; Atkinson, Callum; Cordeil, Maxime; Czauderna, Tobias.

2017 International Symposium on Big Data Visual Analytics (BDVA). ed. / Wolfgang Mayer; Michael Wybrow. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 1-8 8114624.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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Satriadi KA, Stephens K, Atkinson C, Cordeil M, Czauderna T. Immersive isosurface visualisation for engineering datasets. In Mayer W, Wybrow M, editors, 2017 International Symposium on Big Data Visual Analytics (BDVA). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 1-8. 8114624 https://doi.org/10.1109/BDVA.2017.8114624