CAREER: Effective Analysis, Exploration and Visualization of Big Flow Data to Understand Dynamic Flows

许多科学、工程和医学模拟产生的流量数据的规模和复杂性不断增长，这给现有的可视化技术带来了重大挑战。这些挑战包括计算、交互、可视化和用户挑战。解决计算挑战是研究的中心焦点，也是该领域的一个突出方向，而其他挑战往往被忽视。这个CAREER项目的目标是通过开创一个全面的框架，对流场进行有效的视觉理解，来解决这些较少被研究的挑战。它通过促进基于形状的场线建模和分类的创新数据库方法，研究新的基于字符串，草图和图形的流场勘探接口和交互，以及通过非常规流线重新定位和自动巡回生成来探索遮挡和杂波减少，从而促进了最先进的流可视化。本研究开发的一般方法有望大大提高我们从视觉上理解广泛流场的能力，范围从流体流动的传统应用到交通流、现金流和信息流等新应用。该项目将通过顶点课程项目为研究生和本科生提供数据可视化和科学计算领域的培训。一个教学工具箱将与基于网络的资源一起设计，通过富有表现力的演示来支持可视化课程的教学，这可能会使全国有类似教学需求的大学受益。PI将继续通过大学和院系外展项目吸引代表性不足的学生，并通过暑期青年项目吸引当地初高中学生。本研究解决了大型、复杂的三维定常和非定常流场可视化的基本挑战。提出的工作基础是一个新的数据库方法来场线形编码，分类和查询。PI将整合和统一几何建模、计算机视觉和数据挖掘的各种概念，以创建健壮的视觉字符和用于形状分析和组织的场线单词。将引入新的界面和交互，以便通过文本和视觉形式直观地检索部分场线，并检查分层场线及其在转换后的图空间中的时空关系。创新的流线重新定位聚焦+上下文查看和自动巡回检查隐藏或遮挡流特征将被设计从杂乱到清晰的可视化。这项研究的成功将有利于图形和可视化内外的各种应用，如形状分析、视觉感知、数据库组织、游戏开发和教育中的可视化。PI将与大学、工业和国家实验室的科学家和研究人员合作，将提出的解决方案应用于解决现实世界的问题。研究结果将通过领域专家评论和正式的用户研究来评估。选定的研究成果将被整合到用户参与的教育应用程序中，这些应用程序将在平板设备上运行，并向公众广泛传播。这个CAREER项目将为解决流动可视化中的关键挑战奠定坚实的基础，并导致跨大气云、燃烧化学和心血管研究的多学科合作。它还将产生富有成效的可交付成果，包括有史以来第一个基准现场线形数据库，顶级可视化会议的教程和研讨会，以及教学工具和游戏应用程序。

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.