UFLOW: visualizing uncertainty in fluid flow

Lodha,; Pang,; Sheehan,; Wittenbrink,

doi:10.1109/visual.1996.568116

Cited by 71 publications

(54 citation statements)

References 22 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Examples for this kind of visualization are glyphs [Lodha et al 1996;Wittenbrink et al 1995], the reaction diffusion model [Sanderson et al 2004], cross advection and error diffusion [Botchen et al 2005], and additional color schemes [Botchen et al 2006]. All of these techniques show the effect of the uncertainty locally or for a very short integration time.…”

Section: Related Workmentioning

confidence: 99%

Closed stream lines in uncertain vector fields

Otto

Germer

Theisel

2011

Proceedings of the 27th Spring Conference on Computer Graphics

View full text Add to dashboard Cite

Figure 1: Segment of the Pacific Ocean: volume renderings of the particle distributions visualize attracting (blue) and repelling (red) structures. There are two attracting and two repelling closed stream lines. AbstractWe present a method for the detection and visualization of closed stream lines topologically acting as sources or sinks in uncertain 2D and 3D vector fields. For their detection, we apply a Monte Carlo simulation which generates particle distribution functions representing sinks and sources. We show that in the uncertain case there is no structural difference between critical points and closed orbits. This allows the application of critical point extractors to closed stream lines as well. We show applications for some synthetic and real world examples.

show abstract

Section: Related Workmentioning

confidence: 99%

Closed stream lines in uncertain vector fields

Otto

Germer

Theisel

2011

Proceedings of the 27th Spring Conference on Computer Graphics

View full text Add to dashboard Cite

show abstract

“…36 However, it is beyond our scope to examine all of these techniques. Therefore, only streamlines, vector plots and vorticity color maps are used in various figures throughout this paper.…”

Section: System Performancementioning

confidence: 99%

Cardiac Flow Analysis Applied to Phase Contrast Magnetic Resonance Imaging of the Heart

et al. 2009

View full text Add to dashboard Cite

Abstract-Phase contrast magnetic resonance imaging is performed to produce flow fields of blood in the heart. The aim of this study is to demonstrate the state of change in swirling blood flow within cardiac chambers and to quantify it for clinical analysis. Velocity fields based on the projection of the three dimensional blood flow onto multiple planes are scanned. The flow patterns can be illustrated using streamlines and vector plots to show the blood dynamical behavior at every cardiac phase. Large-scale vortices can be observed in the heart chambers, and we have developed a technique for characterizing their locations and strength. From our results, we are able to acquire an indication of the changes in blood swirls over one cardiac cycle by using temporal vorticity fields of the cardiac flow. This can improve our understanding of blood dynamics within the heart that may have implications in blood circulation efficiency. The results presented in this paper can establish a set of reference data to compare with unusual flow patterns due to cardiac abnormalities. The calibration of other flow-imaging modalities can also be achieved using this well-established velocityencoding standard.

show abstract

“…A number of studies that present methods for quality visualisation have also studied their usability (Aerts et al, 2003;Cliburn et al, 2002;Fisher, 1993; Gershon, 1992;Kardos et al, 2006;Kinkeldey et al, 2014a;Lodha et al, 1996;MacEachren et al, 1998;Pang, 2001;Schweizer and Goodchild, 1992). In the following paragraphs, a number of guidelines for VGI quality visualisation in relation to user experience are discussed, once again taking the two main user profiles into account: the novice user and the expert user/scientist.…”

Section: Quality Visualisation Methods and Vgi Datamentioning

confidence: 99%

Visualisation and Communication of VGI Quality

Skopeliti

Antoniou²,

Bandrova

2017

Mapping and the Citizen Sensor

View full text Add to dashboard Cite

The flourishing of VGI projects has transformed the average web user into an eager geographic data user and contributor. As it is difficult for the crowd to perceive VGI quality, visualisation can play a critical role in communicating data quality. At the same time, although VGI quality has been a prominent research topic for scientists, quality visualisation has not been exploited to its full potential. Since the crowd encompasses a diverse pool of users, VGI quality visualisation caters for different needs and exhibits variable functionality, operating as an awareness tool for the novice user as well as an exploration tool for the expert user / scientist. The scope of this chapter is to present a framework for VGI quality visualisation that takes into account factors such as methods for quality visualisation of spatial data, the nature of VGI data quality, user profiles and the visualisation environment. In addition, a review of the available methods for data quality visualisation, which have emerged from cartography, is presented, and a number of guidelines for VGI quality visualisation are proposed, taking into account user characteristics.

show abstract

UFLOW: visualizing uncertainty in fluid flow

Cited by 71 publications

References 22 publications

Closed stream lines in uncertain vector fields

Closed stream lines in uncertain vector fields

Cardiac Flow Analysis Applied to Phase Contrast Magnetic Resonance Imaging of the Heart

Visualisation and Communication of VGI Quality

Contact Info

Product

Resources

About