Enhanced Line Integral Convolution with Flow Feature Detection

https://doi.org/10.21949/14036731995PDFResearch PaperNAS 2-14303AviationFlow fieldsFlow visualizationUnsteady flowFlowAnalysisFlow distributionFlow feature detectionFlow patternsFlow separation and reattachmentsFlow simulationsImage enhancementsLIC methodUnited StatesAmes Research CenterOkada, ArthurLane, DavidAmes Research CenterUnited States. National Aeronautics and Space AdministrationNTL-AVIATION-AVIATIONUS Transportation CollectionPrepared ca. 1995. The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain [Cabral & Leedom '93]. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This some-times makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.88