Show simple item record

dc.contributor.authorHummel, Mathiasen_US
dc.contributor.authorBujack, Roxanaen_US
dc.contributor.authorJoy, Kenneth I.en_US
dc.contributor.authorGarth, Christophen_US
dc.contributor.editorEnrico Bertini and Niklas Elmqvist and Thomas Wischgollen_US
dc.date.accessioned2016-06-09T09:42:23Z
dc.date.available2016-06-09T09:42:23Z
dc.date.issued2016en_US
dc.identifier.isbn978-3-03868-014-7en_US
dc.identifier.issn-en_US
dc.identifier.urihttp://dx.doi.org/10.2312/eurovisshort.20161153en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.description.abstractComputing power outpaces I/O bandwidth in modern high performance computers, which leads to temporal sparsity in flow simulation data. Experiments show that Lagrangian flow representations (where pathlines are retrieved from short-time flow maps using interpolation and concatenation) outperform their Eulerian counterparts in advection tasks under these circumstances. Inspired by these results, we present the theoretical estimate of the Lagrangian error for individual pathlines, depending on the choice of temporal as well as spatial resolution. In-situ, this measure can be used to steer the output resolution and post-hoc, it can be used to visualize the uncertainty of the pathlines. To validate our theoretical bounds, we evaluate the measured and the estimated error for several example flow fields.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectVisualization [Humanen_US
dc.subjectcentered computing]en_US
dc.subjectVisualization application domainsen_US
dc.subjectScientific visualizationen_US
dc.titleError Estimates for Lagrangian Flow Field Representationsen_US
dc.description.seriesinformationEuroVis 2016 - Short Papersen_US
dc.description.sectionheadersFlow Visualizationen_US
dc.identifier.doi10.2312/eurovisshort.20161153en_US
dc.identifier.pages7-11en_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record