Authors:
M. Edmunds
1
;
R. S. Laramee
1
;
R. Malki
1
;
I. Masters
1
;
Y. Wang
2
;
G. Chen
3
;
E. Zhang
4
and
N. Max
5
Affiliations:
1
Swansea University, United Kingdom
;
2
Shenzhen VisuCA Key Lab/SIAT, China
;
3
University of Houston, United States
;
4
Oregon State University, United States
;
5
University of California, United States
Keyword(s):
Automatic Stream Surface Seeding, Data Clustering, Scalar Field Data, Irregular and Unstructured Grids, Focus + Context Techniques, Flow Visualisation.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Flow Visualization
;
Scientific Visualization
;
Spatial Data Visualization
;
Vector/Tensor Field Visualization
Abstract:
The ability of a CFD engineer to study, capture, and visualise 3D flow simulation data is a challenge. Stream surfaces are a useful tool for visualising 3D flow because of their ability to convey many field attributes from their structure. It is important that the CFD engineer can interact with, and examine specific characteristics of the CFD data. We introduce an interactive, cluster based stream surface placement strategy for structured and unstructured CFD data. A two-phase hybrid clustering algorithm is used to visualise interesting subsets of the flow. An interactive tree map interface provides a visual overview and enables interactive selection of cluster details corresponding to interesting features of the data at which to place stream surfaces. We demonstrate the performance and effectiveness of our interactive framework on a range of flow simulations and provide domain expert evaluation of the results, providing valuable insight for the CFD engineers.