U.S.-Italy Cooperative Research: Waveform Relaxation Methods

美意合作研究：波形弛豫方法

• 批准号: 9301044
• 负责人: Zdzislaw Jackiewicz
• 金额: $ 1.36万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-06-15 至 1996-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9301044&HistoricalAwards=false
• 关键词: U.S.; Italy; Cooperative; Research; Waveform

9301044 Jackiewicz This two-year award supports US-Italy cooperative research in waveform relaxation methods between Zdzislaw Jackiewicz, Arizona State University, and Alfredo Bellen, University of Trieste, Italy. The objective of their research is to investigate convergence, order, stability, and contractivity properties of time-point relaxation and waveform relaxation Runge-Kutta methods for ordinary differential equations. Such methods are appropriate in a parallel computing environment and have been successfully used for time domain analysis of large dynamical systems. Jackiewicz and Bellen are specialists in waveform relaxation methods, which aim to develop effective numerical methods for systems of ordinary differential equations. The topic area is important because systems of ordinary differential equations arise naturally in modeling a variety of important physical, biological, and geological phenomena and in many industrial applications. This collaboration allows the Italian expertise in parallel methods for differential equations to be complemented by Jackiewicz's experience in general linear methods for differential equations. This should lead to a better understanding of numerical solution of ordinary differential equations in a parallel computing environment. * * *

9301044 Jackiewicz这个为期两年的奖项支持亚利桑那州立大学Zdzislaw Jackiewicz和意大利的里雅斯特大学Alfredo Bellen在波形松弛方法方面的美意合作研究。他们的研究目的是研究常微分方程解的时间点松弛和波形松弛Runge-Kutta方法的收敛、阶、稳定性和收缩性质。这种方法适用于并行计算环境，并已成功地用于大型动力系统的时域分析。Jackiewicz和Bellen是波形松弛方法方面的专家，他们的目标是发展常微分方程组的有效数值方法。这一主题领域很重要，因为常微分方程组在模拟各种重要的物理、生物和地质现象以及在许多工业应用中自然产生。这一合作使意大利在微分方程式并行方法方面的专业知识与Jackiewicz在微分方程式一般线性方法方面的经验相辅相成。这将有助于在并行计算环境中更好地理解常微分方程组的数值解。***