The ever-growing size and complexity of flow data produced from many scientific, engineering and medical simulations pose significant challenges which are not thoroughly addressed by existing visualization techniques. These challenges include computation, interaction, visualization and user challenges. Addressing the computation challenge is a central research focus and remains a prominent direction in the field, while the other challenges are often overlooked. The goal of this CAREER project is to address these less investigated challenges by pioneering a comprehensive framework toward effective visual understanding of flow fields. It contributes to the state of the art flow visualization by promoting an innovative database approach to shape-based field line modeling and classification, investigating new string-, sketch- and graph-based interfaces and interactions for flow field exploration, and exploring occlusion and clutter reduction through unconventional streamline repositioning and automatic tour generation. The general approach developed in this research is expected to substantially improve our ability to visually understand a wide spectrum of flow fields, ranging from the traditional application of fluid flows to new applications such as traffic flows, cash flows and message flows. This project will provide training for graduate and undergraduate students in the area of data visualization and scientific computing via capstone class projects. A pedagogical toolbox will be designed along with web-based resources to support teaching visualization classes through expressive demos, potentially benefiting universities nationwide with a similar teaching need. The PI will continue to attract underrepresented students through university and department outreach programs and engage local middle and high school students through summer youth programs.
This research tackles the fundamental challenges in visualizing large, complex three-dimensional steady and unsteady flow fields. Underlying the proposed work is a novel database approach to field line shape encoding, classification and interrogation. The PI will integrate and unify a variety of concepts from geometric modeling, computer vision and data mining to create robust visual characters and words from field lines for shape analysis and organization. Novel interfaces and interactions will be introduced to enable intuitive retrieval of partial field lines via textual and visual forms, and examination of hierarchical field lines and their spatiotemporal relationships in the transformed graph space. Innovative streamline repositioning for focus+context viewing and automatic tour for examining hidden or occluded flow features will be devised to move from clutter to clarity in the visualization. The success of this research will benefit a wide variety of applications within and beyond graphics and visualization, such as shape analysis, visual perception, database organization, game development, and visualization in education.
The PI will collaborate with scientists and researchers at university, industry and national labs, applying the proposed solutions to solve real-world problems. Research results will be evaluated through both domain expert reviews and formal user studies. Selected research outcomes will be integrated into user-engaging educational applications that will be run on tablet devices and delivered to the general public for wide dissemination. This CAREER project will build a solid foundation for addressing key challenges in flow visualization, and lead to multidisciplinary collaborations spanning atmospheric cloud, combustion chemistry and cardiovascular research. It will also produce fruitful deliverables, featuring the first-ever benchmark field line shape database, tutorials and workshops at premier visualization conferences, and pedagogical tools and game apps.
