Computational and Algorithmic Representations of Geonetric Objects - CARGO: Computational Topology for Exploring Time-varying Volume Data

几何对象的计算和算法表示 - CARGO：用于探索时变体积数据的计算拓扑

• 批准号: 0138426
• 负责人: Jack Snoeyink
• 金额: $ 10万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-05-01 至 2003-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0138426&HistoricalAwards=false
• 关键词: Computational; Algorithmic; Representations; Geonetric; Objects

DMS-0138426Jack S. SnoeyinkScientific measurements and computer simulations of phenomena like air turbulence, nuclear explosions, or combustion in an engine, when conducted at high-performance computing facilities, produce vast amounts of four-dimensional data representing how variables such as temperature andpressure change over time. This incubation project brings together researchers at UNC Chapel Hill, Georgia Tech, and Lawrence Livermore National Labs to develop a prototype visualization tool that can both quickly compute such iso-surfaces from such data sets and also provide a global summary that can indicate where a user should look in the data set to find interesting phenomena.The approach to be taken is to extend work on contour trees to a "Morse theory for a parameterized family of functions" that is sufficient to visualize 4D data from 2D iso-surfaces or slices. When scientists, engineers, and students can explore the data that comes from simulation, their understanding of the process that is being simulated can only improve.This not only increases the return from the national investment in high-performance computing centers, but can also result in, for example, cleaner-burning engines.

DMS-0138426Jack S. Snoeyink 对空气湍流、核爆炸或发动机燃烧等现象的科学测量和计算机模拟，在高性能计算设施上进行时，会产生大量的四维数据，表示温度和压力等变量如何变化随着时间的推移。该孵化项目汇集了北卡罗来纳大学教堂山分校、佐治亚理工学院和劳伦斯利弗莫尔国家实验室的研究人员，开发了一种原型可视化工具，该工具既可以根据此类数据集快速计算此类等值面，也可以提供全局摘要，以指示用户在哪里应该在数据集中寻找有趣的现象。所采取的方法是将等高线树的工作扩展到“参数化函数族的莫尔斯理论”，该理论足以可视化来自 2D 等值面的 4D 数据或切片。 当科学家、工程师和学生能够探索来自模拟的数据时，他们对模拟过程的理解只会提高。这不仅增加了国家对高性能计算中心的投资回报，还可以带来例如，在更清洁的燃烧发动机中。