Collaborative Research: Hybrid Modeling for Design, Estimation, and Analysis

协作研究：设计、估算和分析的混合建模

• 批准号: 0310546
• 负责人: James Damon
• 金额: --
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-06-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0310546&HistoricalAwards=false
• 关键词: Collaborative; Research; Hybrid; Modeling; Design

This is a collaborative research project between the Universities of Utah and North Carolina at Chapel Hill. The project is advancing the state of the art in geometric modeling by constructing a set of new surface representations that are sufficiently general to solve a wide range of problems in geometric surface design, estimation, and analysis. This work is founded on the assertion that no single representation is adequate to solve efficiently and accurately the myriad computational and analytical problems arising in modern applications. The strategy, therefore, is to develop a framework that systematically combines parametric and implicit surface representations. This project will examine the complementary nature of two particular representations: non-uniform B-splines (NURBs) and level sets. It will develop methods which provide: mutual tracking of the representations, analysis of the topology and singularities which occur, and mechanisms for communicating important topological events between representations. This project will also examine applications of this framework to computer aided design and terrain modeling and analysis. When modeling 3D objects with surfaces, one is faced with a wide range of different surface representations. Each representation has corresponding drawbacks and advantages. Many modeling applications, such as computer-aided design and terrain analysis, require shapes to be modified in order to match some input data or to suit the needs of a user or designer. Therefore, one of the most important aspects of a surface representation is how it affords a user or a computer algorithm the facility to modify a shape, i.e. to deform one shape into another slightly different shape. Some representations provide a user with a great deal of control, but are constrained to a limited specific set of shapes. Other representations can represent a wide range of shapes, but only with a limited accuracy. An important concern in modifying a shape is how the representation handles cases where the surface folds back and touches itself. This is called a singularity and it indicates that the surface might be transitioning from one class of shapes to another. Different surface representations handle such singularities in different ways. This work will try to improve the technology for modifying shapes and handling singularities by combining two different shape representations and extending relevant singularity theory. This exploration should yield new tools for designing shapes and new tools for building and analyzing the shapes of measured surfaces, such as those generated from terrains. The collaboration between Utah (031075) and the University of North Carolina Chapel Hill (0310546) provides this project with specialized skills in singularity theory and unique educational opportunities for computer science students to learn more about this important subject in mathematics.

这是犹他大学和北卡罗来纳大学教堂山分校的合作研究项目。该项目通过构建一组新的表面表示来推进几何建模的艺术状态，这些表面表示足够普遍，可以解决几何表面设计，估计和分析中的广泛问题。这项工作是建立在断言，没有一个单一的表示是足以解决有效和准确的无数计算和分析问题出现在现代应用。因此，策略是开发一个框架，系统地结合参数和隐式表面表示。本项目将研究两种特殊表示的互补性：非均匀b样条（nurb）和水平集。它将开发的方法提供：表示的相互跟踪，拓扑和奇点的分析，以及在表示之间传递重要拓扑事件的机制。该项目还将研究该框架在计算机辅助设计和地形建模与分析中的应用。当对带有表面的3D物体建模时，人们面临着各种不同的表面表示。每种表现形式都有相应的缺点和优点。许多建模应用程序，如计算机辅助设计和地形分析，需要修改形状，以匹配某些输入数据或满足用户或设计师的需要。因此，表面表示最重要的方面之一是它如何为用户或计算机算法提供修改形状的设施，即将一个形状变形为另一个略有不同的形状。有些表示为用户提供了大量的控制，但仅限于有限的特定形状集。其他表示可以表示各种形状，但精度有限。在修改形状时，一个重要的问题是如何处理表面折回并接触自身的情况。这被称为奇点，它表明曲面可能从一类形状过渡到另一类形状。不同的表面表示以不同的方式处理这样的奇点。本工作将尝试通过结合两种不同的形状表示和扩展相关的奇点理论来改进形状修改和奇点处理技术。这种探索将产生设计形状的新工具，以及构建和分析测量表面形状的新工具，例如由地形产生的形状。犹他大学（031075）和北卡罗来纳大学教堂山分校（0310546）之间的合作为该项目提供了奇点理论的专业技能，并为计算机科学专业的学生提供了独特的教育机会，让他们更多地了解这一重要的数学学科。