Collaborative Research - ITR-High Order Partial Differential Equations:Theory, Computational Tools, and Applications in Image Processing, Computer Graphics, Biology, and Fluids

协作研究 - ITR-高阶偏微分方程：理论、计算工具以及在图像处理、计算机图形学、生物学和流体中的应用

• 批准号: 0323886
• 负责人: Ron Fedkiw
• 金额: $ 35万
• 依托单位: Stanford University
• 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: 2003-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0323886&HistoricalAwards=false
• 关键词: Collaborative; Research; ITR; Order; Partial

This project seeks to develop a comprehensive research and education program in the area of computationalmethods and simulations of physical systems described by high order Partial Differential Equations (PDEs). The program will unify algorithmic, visualization, theoretical, and experimental efforts as well as address applications in areas of science and technology, including computer graphics, image processing, biology, and fluids.Intellectual merit of the proposed activityThis project advances knowledge in the area of high order PDEs, with particular emphasis on curved surface data, and produces enabling technology to address fundamental problems in biology, image processing, computer graphics, and fluids in general. The novel science is in the computationaltechniques, experimental research, and diverse applications addressed by a multi-disciplinary team. Thisproject brings together the five fields of computer science, applied mathematics, mechanical engineering, physics, and electrical and computer engineering.Broader impacts of the proposed activityWith the increasing interest in high order PDEs, the computational tools and experience resulting from this project impact beyond the particular applications in this proposal. Students will receive unusually broadinterdisciplinary training and the workshop planned further brings experts from different fields together. New public domain software incorporating the developed algorithms enables researchers from different fields using higher order PDEs to perform state-of-the-art numerical simulations and graphics rendering of their application of interest.Educational initiatives of this research program include: (1) new interdisciplinary training of graduate students and postdocs through co-mentoring by PIs in different fields; (2) new interdisciplinary courses in computer graphics, numerical analysis, and modeling/simulation of physical phenomena described by higher order PDEs; (3) a workshop bringing together for the first time diverse scientific researchers using high order PDEs.

该项目致力于在高阶偏微分方程组(PDE)描述的物理系统的计算方法和模拟方面开发一个全面的研究和教育计划。该计划将统一算法、可视化、理论和实验工作，并解决科学和技术领域的应用，包括计算机图形学、图像处理、生物学和流体。拟议活动的智力优点本项目推进高阶偏微分方程组领域的知识，特别强调曲面数据，并产生使技术能够解决生物学、图像处理、计算机图形学和一般流体的基本问题。这门新颖的科学是由一个多学科团队在计算技术、实验研究和各种应用方面进行的。该项目汇集了计算机科学、应用数学、机械工程、物理、电气和计算机工程五个领域。拟议活动的广泛影响随着人们对高阶PDE的兴趣日益增加，该项目产生的计算工具和经验的影响超出了本提案中的特定应用。学生将接受异常广泛的跨学科培训，计划中的研讨会进一步将来自不同领域的专家聚集在一起。这项研究计划的教育倡议包括：(1)通过不同领域的PI的共同指导，对研究生和博士后进行新的跨学科培训；(2)新的跨学科课程，涉及计算机图形学、数值分析和由高阶PDE描述的物理现象的建模/模拟；(3)首次将使用高阶PDE的不同科学研究人员聚集在一起。