Abstract
Streamline is one of the main methods for flow field visualization, which describes the distribution pattern of the flow field through the flow trajectory of seed points. Currently, most of the work focuses on seed point placement and streamline generation in feature regions. For context regions (blank areas), i.e., context regions without features, however, there is little research conducted. In fact, the context regions carry some flow field information, which can assist researcher in deeply understanding the entire spatial distribution of the flow field as well as the continuous transition between different feature regions. However, it is a challenging problem to generate suitable streamlines in context regions. If the streamlines are not positioned properly or have a too large number, they may severely occlude the feature regions, while too few streamlines may be difficult to fill in the entire information of the flow field. To address the problem, this article proposes a new method for seed point placement that mainly focuses on context regions. The method is divided into two steps: finding context regions and then placing seed points in context regions. Firstly, use 3D to 2D projection transformation and region connectivity algorithm to find context regions, where no feature streamlines pass through. The streamlines in a context region often have similar directions due to being away from critical points. Then, according to the direction of the streamlines, evenly place seed points in the 3D space. As a result, spatially uniform streamlines are generated to fill the context regions, which makes the flow field information more complete. Qualitative and quantitative evaluations show that the method proposed in this article can generate visually uniform streamlines in context regions, together with feature streamlines, which can help researchers to coherently understand the overall characteristics of the flow field.
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Acknowledgements
This research was sponsored by the National Natural Science Foundation of China under Grant No. 62032023. The authors would like to express sincere gratitude to Professor Jun Tao from Sun Yat-sen University for his invaluable assistance. His guidance and support were instrumental in implementing the GVF method for evaluating the quality of placed streamlines. The authors will like to thank Bill Kuo, Wei Wang, Cindy Bruyere, Tim Scheitlin, and Don Middleton of the U.S. National Center for Atmospheric Research (NCAR) and the U.S. National Science Foundation (NSF) for providing the Weather Research and Forecasting (WRF) Model simulation data of Hurricane Isabel.
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Zhang, Q., Mo, Z., Wang, H. et al. A seed point placement method for generating streamlines in context regions. J Vis 27, 1227–1244 (2024). https://doi.org/10.1007/s12650-024-01019-4
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DOI: https://doi.org/10.1007/s12650-024-01019-4