CAREER: Discoveries in compressible turbulence and turbulent mixing through Petascale simulations and analysis

职业：通过千万亿次模拟和分析发现可压缩湍流和湍流混合

• 批准号: 1054966
• 负责人: Diego Donzis
• 金额: $ 42.12万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-02-15 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1054966&HistoricalAwards=false
• 关键词: CAREER; Discoveries; compressible; turbulence; turbulent

ABSTRACTCompressible turbulent flows, characterized by a wide range of spatial and temporal scales,occur in many natural (supernovae explosions, volcanic eruptions, solar wind) and engineeringsystems (commercial and supersonic flight and propulsion, reacting flows). Due to their complexity,though, our fundamental understanding remains very limited, especially at high Reynolds numbers,restricting our ability to predict natural phenomena and design better engineering devices.This research advances the knowledge of compressible turbulence only possible through massivesimulations enabled by Cyberinfrastructure pushing, in turn, the frontiers of computational fluiddynamics. The simulations, unprecedented in size and detail, require novel software that efficientlyuses hundreds of thousands of processors at Petascale levels and set the path for simulations at evenlarger scales. The emphasis is in extreme parallelism exploring advanced features likely to existin future architectures including communication libraries, programming models and accelerators.The tremendous details unveiled by the simulations provide a unique opportunity for investigatorsto understand long-standing issues such as small-scale universality, inertial-range scaling, intermittency and largely unexplored areas such as mixing and dispersion of contaminants. Results aremade available through a portal which allows the community to obtain flow fields, statistics andcodes, and analyze massive datasets remotely.Research and education are integrated at the interface between high-performance computing(HPC) and fluid mechanics. The educational goal is to (i) inspire students, including those fromunderrepresented groups, to pursue careers in HPC and fluid mechanics, and (ii) educate futurescientists and engineers capable of deploying Petascale solutions to important societal and technological problems. Educational and research activities are integrated through curricular innovation,undergraduate research and the portal which is also used to disseminate results to a broader audience.

摘要可压缩湍流具有广泛的时空尺度，存在于许多自然系统（超新星爆炸、火山喷发、太阳风）和工程系统（商业和超音速飞行与推进、反应流）中。然而，由于它们的复杂性，我们的基本理解仍然非常有限，特别是在高雷诺数下，限制了我们预测自然现象和设计更好的工程设备的能力。这项研究推进了可压缩湍流的知识，只有通过网络基础设施的大规模模拟才能实现，反过来，计算流体动力学的前沿。这些模拟在规模和细节上都是前所未有的，需要新颖的软件来有效地使用千兆级的数十万个处理器，并为更大规模的模拟铺平道路。重点是极端并行性，探索未来架构中可能存在的高级特性，包括通信库、编程模型和加速器。模拟揭示的大量细节为研究人员提供了一个独特的机会来理解长期存在的问题，如小规模的普遍性，惯性范围的缩放，间歇性和大部分未开发的领域，如污染物的混合和分散。结果可通过门户网站获得，该门户网站允许社区获取流场，统计数据和代码，并远程分析大量数据集。研究和教育是集成在高性能计算（HPC）和流体力学之间的接口。教育目标是(i)激励学生，包括那些代表性不足的群体，追求高性能计算和流体力学的职业生涯，（ii）培养未来的科学家和工程师能够部署千兆级解决方案来解决重要的社会和技术问题。教育和研究活动通过课程创新、本科生研究和门户网站进行整合，门户网站也用于向更广泛的受众传播成果。