MDC: A Numerical Laboratory for Multi-Model Multi-Domain Computational Methods in Aerodynamics and Acoustics

MDC：空气动力学和声学多模型多领域计算方法的数值实验室

• 批准号: 9527169
• 负责人: David Keyes
• 金额: $ 113.06万
• 依托单位: Old Dominion University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-10-01 至 1999-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9527169&HistoricalAwards=false
• 关键词: MDC; Numerical; Laboratory; Multi; Model

9527169 Keyes This project will develop public use software to implement two important paradigms for domain decomposition: medium-grained data decomposition and course-grained task decomposition. In addition, it will enhance the theory of task decomposition with respect to two specific applications involving multiple physics, aerodynamics and physics. It will attempt to verify the theory behind the two paradigms, and the develop software which combines the strength of both. Effective multi-domain parallel solutions to multi-model coupled field problems will have widespread usefulness, particularly in light of the growing emphasis on multidisciplinary analysis and optimization. The current pioneers of multidisciplinary optimization are finding it necessary to revisit the lower levels of the constituent modeling hierarchies. It is not practical to simultaneously upgrade all of the low-level models employed inside of optimization loops to the complex models used in the state-of -the-art of the individual disciplines, for reasons of complexity and severe ill-conditioning. This creates an obvious niche for the deliverables of this proposal - highly performant solvers with built-in support for multi-model analysis.

9527169 KEYES该项目将开发公共使用软件，以实现域分解的两个重要范式：中粒数据分解和课程元件任务分解。 此外，它将相对于涉及多种物理学，空气动力学和物理学的两个特定应用来增强任务分解理论。 它将尝试验证两个范式背后的理论，并结合两者的强度的开发软件。 多模型耦合场问题的有效多域并行解决方案将具有广泛的有用性，尤其是鉴于人们对多学科分析和优化的重视日益强调。 当前的多学科优化的开拓者发现，有必要重新审视组成模型层次结构的较低级别。 出于复杂性和严重的不良条件的原因，同时将优化回路内部使用的所有低级模型升级到了最新学科最新的复杂模型。 这为该提案的可交付成果创造了一个明显的利基市场 - 高性能的求解器，并为多模型分析提供了支持。