Collaborative Research: Large Numerical Simulations of Turbulence and Reynolds, Schmidt and Rossby Number Scalings

合作研究：湍流和雷诺数、施密特数和罗斯贝数缩放的大型数值模拟

• 批准号: 0553867
• 负责人: Pui-Kuen Yeung
• 金额: --
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0553867&HistoricalAwards=false
• 关键词: Collaborative; Research; Large; Numerical; Simulations

PROPOSAL NO.: CTS-0553867 / 0553602PRINCIPAL INVESTIGATOR: P-K YEUNG/ K. R. SREENIVASANINSTITUTION: GIT / U. OF MD COLLEGE PARKHIGH RESOLUTION NUMERICAL SIMULATIONS OF TURBULENCE The objectives of this project are to utilize supercomputing power at the highest level to advance understanding of turbulent flows, via innovative and rigorous analyses of large numerical simulation databases, and via systematic sharing of data with a community of collaborators while pushing the frontiers of computational turbulence. Emphasis is placed on the dependence of local fluctuations on scale size in space and time, and on several major non-dimensional parameters that express the effects of a wide range of scales in both fixed and moving frames of reference, of different degrees of molecular diffusion, and of Coriolis forces in a rotating frame. The PIs will conduct high resolution (computational mesh of 4096 cubed, or 69 billion grid points) simulations and interrogate the database using their combined expertise in simulation, theory and experiment to provide definitive answers to fundamental aspects of turbulence, such as intermittency, multifractals, anisotropy, Lagrangian similarity, mixing at high Schmidt numbers, rotating turbulence at low Rossby numbers. Furthermore, the range of new ideas tested and stimulated by the database will be greatly expanded through working with a group of highly regarded researchers, who will be able to access the data hosted at two NSF TeraGrid sites (SDSC and PSC) in a seamless manner. The proposed activity will have wide impact because of the importance of turbulence in many fields of science and engineering, the uniqueness of the simulation database generated using millions of supercomputer hours, and innovative arrangements with at least two NSF-supported supercomputer centers for sharing data effectively with many researchers with varied interests in the US and abroad. Advances in the science of turbulent flow will have long-term impact in many problems important to society, including fossil fuel combustion, marine life in oceanography, and newer technologies such as nanomaterial synthesis, all of which depend on turbulent mixing at the small scales. Graduate students will have unique and inspiring opportunities to work at the forefront of scientific computing and develop broader perspectives by working closely with many distinguished researchers in the field. Similar considerations are expected to motivate qualified undergraduates from under-represented groups.

提案号：CTS-0553867 /0553602主题研究者：P-K Yeung / K。R. Sreenivasaninstitution：Git / MD College Parkhigh分辨率的数值模拟该项目的湍流的数值模拟该项目的最高级别能够通过超级层次的范围来实现巨大的能力，并通过构成数字的构图，构成数字的湍流，构成湍流，构成湍流，模拟数据库，以及通过系统共享与合作者社区的系统共享，同时推动计算湍流的前沿。 重点放在局部波动对空间和时间量表大小的依赖性，以及在固定和移动的参考框架，不同程度的分子扩散和旋转框架中的Coriolis力的范围范围广泛的范围范围的几个主要非二维参数上。 The PIs will conduct high resolution (computational mesh of 4096 cubed, or 69 billion grid points) simulations and interrogate the database using their combined expertise in simulation, theory and experiment to provide definitive answers to fundamental aspects of turbulence, such as intermittency, multifractals, anisotropy, Lagrangian similarity, mixing at high Schmidt numbers, rotating turbulence at low Rossby numbers. 此外，通过与一组备受推崇的研究人员合作，将大大扩展数据库测试和刺激的新想法的范围，他们将能够以无缝的方式访问两个NSF Teragrid网站（SDSC和PSC）的数据。 由于在许多科学和工程领域的湍流的重要性，使用数百万个超级计算机小时的仿真数据库的独特性以及与至少两个由NSF支持的超级法规中心与许多有效的数据共享数据有效共享的数据库的创新安排，因此提出的活动将产生广泛的影响，以及与我们和Aud and Aud和Afrof的各种利益的许多研究人员一起生成的仿真数据库。湍流科学的进步将对许多对社会重要的问题产生长期影响，包括化石燃料燃烧，海洋学中的海洋生物以及诸如纳米材料综合的新技术，所有这些都取决于在小规模上的湍流混合。研究生将有独特而鼓舞人心的机会在科学计算的最前沿工作，并通过与该领域的许多杰出研究人员紧密合作，发展更广泛的观点。 预计类似的考虑会激发代表性不足的群体的合格本科生。