Collaborative Research: Enabling Discovery in High Reynolds Number Turbulence via Advanced Tools for Petascale Simulation and Analysis

协作研究:通过用于千万级模拟和分析的高级工具实现高雷诺数湍流的发现

基本信息

  • 批准号:
    0749286
  • 负责人:
  • 金额:
    $ 38.4万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2007
  • 资助国家:
    美国
  • 起止时间:
    2007-10-01 至 2013-09-30
  • 项目状态:
    已结题

项目摘要

PROPOSAL NO.: OCI - 0749223/0749209/0749235/0749286 PRINCIPAL INVESTIGATOR: P-K YEUNG INSTITUTION: Georgia Institute of Technology COLLABORATIVE RESEARCH: ENABLING DISCOVERY IN HIGH REYNOLDS NUMBER TURBULENCE VIA ADVANCED TOOLS FOR PETASCALE SIMULATION AND ANALYSIS This research will advance the science of turbulent fluid flow at high Reynolds number, by taking full advantage of emerging Petascale computing capabilities to address a number of important research questions, while setting a new standard for open-source code development in CFD. The science emphasis is on simulations at the finest grid resolution and highest Reynolds number possible, for homogeneous turbulence and inhomogeneous turbulence with one direction of spatial inhomogeneity. Elements of advanced computing will include domain decomposition techniques that scale to future Petascale systems with on million processors or more, high node-level performance making use of advanced hardware features, and enhanced capacity for storage and analysis of very large datasets. Open access to both codes and data will be provided for the research community. Turbulence is characterized by disorderly fluctuations over a wide range of scales in time and space, and is a problem of great complexity and societal and technological importance. Direct numerical simulations (DNS), in which fluctuations are computed according to exact conservation equations is an ideal application for Petascale computation, since computations of this complexity are needed to resolve the wide range of spatial and temporal scales, and because the high reliability of DNS data makes such a resource investment worthwhile. To enable PetaScale DNS (PSDNS), a powerful, flexible and extensible open-source suite of software analyzing the resulting data, for flows with no more than one direction of spatial inhomogeneity will be developed. The PSDNS suite, based on highly scalable components developed by the PIs, will be further developed for extreme parallelism. New software will perform many high Reynolds number DNS to answer pressing questions in turbulence research. These simulations and analyses will yield critical discoveries in diverse areas of turbulence research, including intermittency in turbulent dispersion, the high Reynolds number overlap layer in wall-turbulence, and local extinction and reignition in turbulent reacting flows. This research will have broad societal and economic impact through advances in turbulence research and computational science. DNS at unprecedented Reynolds numbers will impact science, engineering, society and competitiveness in such areas as mixing and dispersal of pollutants, design and drag of transportation vehicles, and efficiency and pollution in combustion processes. This activity will also impact education in high performance computing through development of materials based on these Petascale software developments. It will impact education in fluid mechanics and turbulence through materials developed from the simulations. Finally, all of this will be performed while encouraging participation at all levels by under-represented groups.
提案编号:OCI - 0749223/0749209/0749235/0749286 主要研究员:P-K YEUNG 机构:佐治亚理工学院合作研究:通过先进工具实现高雷诺数湍流的发现千万级模拟和分析 这项研究将通过充分利用高雷诺数湍流流体流动的科学 新兴的 Petascale 计算能力可解决许多重要的研究问题,同时为 CFD 开源代码开发制定新标准。科学重点是以最精细的网格分辨率和最高的雷诺数进行模拟,以模拟具有一个空间不均匀方向的均匀湍流和非均匀湍流。高级计算的要素将包括域分解技术,可扩展到具有数百万个或更多处理器的未来 Petascale 系统、利用先进硬件功能的高节点级性能以及增强的超大数据集存储和分析能力。将为研究界提供代码和数据的开放访问。湍流的特点是在时间和空间的大范围内无序波动,是一个非常复杂且具有社会和技术重要性的问题。直接数值模拟(DNS)根据精确的守恒方程计算波动,是 Petascale 计算的理想应用,因为需要这种复杂性的计算来解析广泛的空间和时间尺度,而且 DNS 数据的高可靠性使得这样的资源投资是值得的。为了启用 PetaScale DNS (PSDNS),将开发一套功能强大、灵活且可扩展的开源软件套件,用于分析结果数据,适用于空间不均匀性方向不超过一个的流。 PSDNS 套件基于 PI 开发的高度可扩展组件,将进一步开发以实现极端并行性。新软件将执行许多高雷诺数 DNS 来回答湍流研究中的紧迫问题。这些模拟和分析将为湍流研究的各个领域带来重要发现,包括湍流弥散的间歇性、壁湍流中的高雷诺数重叠层以及湍流反应流中的局部消光和重燃。这项研究将通过湍流研究和计算科学的进步产生广泛的社会和经济影响。前所未有的雷诺数 DNS 将影响科学、工程、社会和竞争力,例如污染物的混合和分散、运输车辆的设计和拖动、以及燃烧过程的效率和污染。这项活动还将通过基于这些 Petascale 软件开发的材料的开发来影响高性能计算的教育。它将通过模拟开发的材料影响流体力学和湍流的教育。最后,所有这一切都将在鼓励代表性不足的群体在各个层面参与的同时进行。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Robert Moser其他文献

A fantasy adventure game as a learning environment: why learning to program is so difficult and what can be done about it
作为学习环境的奇幻冒险游戏:为什么学习编程如此困难以及可以采取什么措施
Acute and Chronic Toxicity of Uncured Resin Feedstocks for Vat Photopolymerization 3D Printing to a Cladoceran (Ceriodaphnia Dubia)
  • DOI:
    10.1007/s00128-023-03698-5
  • 发表时间:
    2023-02-16
  • 期刊:
  • 影响因子:
    2.200
  • 作者:
    Mark Ballentine;Alan Kennedy;Nicolas Melby;Anthony Bednar;Robert Moser;Lee C. Moores;Erik M. Alberts;Charles H. Laber;Rebecca A. Crouch
  • 通讯作者:
    Rebecca A. Crouch

Robert Moser的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Robert Moser', 18)}}的其他基金

Collaborative Research: CDS&E: Generalizable RANS Turbulence Models through Scientific Multi-Agent Reinforcement Learning
合作研究:CDS
  • 批准号:
    2347422
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Large Eddy Simulation in Complex Turbulent Flows with Coarse Resolution
复杂湍流中的粗分辨率大涡模拟
  • 批准号:
    2321473
  • 财政年份:
    2023
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
A Framework for Predictive Hybrid Models of Turbulence
湍流预测混合模型的框架
  • 批准号:
    1904826
  • 财政年份:
    2019
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: NISC SI2-S2I2 Conceptualization of CFDSI: Model, Data, and Analysis Integration for End-to-End Support of Fluid Dynamics Discovery and Innovation
合作研究:NISC SI2-S2I2 CFDSI 概念化:模型、数据和分析集成,用于流体动力学发现和创新的端到端支持
  • 批准号:
    1743191
  • 财政年份:
    2018
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Continuing Grant
A Workshop on the Development of Fluid Mechanics Community Software and Data Resources
流体力学社区软件和数据资源开发研讨会
  • 批准号:
    0950102
  • 财政年份:
    2009
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Development and Implementation of Practical Optimal LES Models
实用最优 LES 模型的开发和实施
  • 批准号:
    0530600
  • 财政年份:
    2005
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Development and Implementation of Practical Optimal LES Models
实用最优 LES 模型的开发和实施
  • 批准号:
    0352552
  • 财政年份:
    2004
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Optimal Large Eddy Simulation of Turbulence
湍流的优化大涡模拟
  • 批准号:
    0001435
  • 财政年份:
    2000
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Continuing Grant
A Workshop to Facilitate Coordinated Experimental/Computational Contributions to LES Modeling
促进 LES 建模协调实验/计算贡献的研讨会
  • 批准号:
    9910929
  • 财政年份:
    1999
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Controlling Turbulence as a Chaotic System
将湍流作为混沌系统进行控制
  • 批准号:
    9729189
  • 财政年份:
    1998
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Enabling Cloud-Permitting and Coupled Climate Modeling via Nonhydrostatic Extensions of the CESM Spectral Element Dynamical Core
合作研究:通过 CESM 谱元动力核心的非静水力扩展实现云允许和耦合气候建模
  • 批准号:
    2332469
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Continuing Grant
Collaborative Research: SHF: Medium: Enabling Graphics Processing Unit Performance Simulation for Large-Scale Workloads with Lightweight Simulation Methods
合作研究:SHF:中:通过轻量级仿真方法实现大规模工作负载的图形处理单元性能仿真
  • 批准号:
    2402804
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: CPS: NSF-JST: Enabling Human-Centered Digital Twins for Community Resilience
合作研究:CPS:NSF-JST:实现以人为本的数字孪生,提高社区复原力
  • 批准号:
    2420846
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Enabling GPU Performance Simulation for Large-Scale Workloads with Lightweight Simulation Methods
合作研究:SHF:中:通过轻量级仿真方法实现大规模工作负载的 GPU 性能仿真
  • 批准号:
    2402806
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: SHF: Medium: Enabling GPU Performance Simulation for Large-Scale Workloads with Lightweight Simulation Methods
合作研究:SHF:中:通过轻量级仿真方法实现大规模工作负载的 GPU 性能仿真
  • 批准号:
    2402805
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: Enabling Cloud-Permitting and Coupled Climate Modeling via Nonhydrostatic Extensions of the CESM Spectral Element Dynamical Core
合作研究:通过 CESM 谱元动力核心的非静水力扩展实现云允许和耦合气候建模
  • 批准号:
    2332468
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Continuing Grant
Collaborative Research: SII-NRDZ: SweepSpace: Enabling Autonomous Fine-Grained Spatial Spectrum Sensing and Sharing
合作研究:SII-NRDZ:SweepSpace:实现自主细粒度空间频谱感知和共享
  • 批准号:
    2348589
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: CPS: NSF-JST: Enabling Human-Centered Digital Twins for Community Resilience
合作研究:CPS:NSF-JST:实现以人为本的数字孪生,提高社区复原力
  • 批准号:
    2420847
  • 财政年份:
    2024
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: OAC Core: An Integrated Framework for Enabling Temporal-Reliable Quantum Learning on NISQ-era Devices
合作研究:OAC Core:在 NISQ 时代设备上实现时间可靠的量子学习的集成框架
  • 批准号:
    2311950
  • 财政年份:
    2023
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
Collaborative Research: CPS: Medium: Enabling Data-Driven Security and Safety Analyses for Cyber-Physical Systems
协作研究:CPS:中:为网络物理系统实现数据驱动的安全和安全分析
  • 批准号:
    2414176
  • 财政年份:
    2023
  • 资助金额:
    $ 38.4万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了