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DNS of Pressure Fluctuations Induced by Supersonic Turbulent Boundary Layers

DNS of Pressure Fluctuations Induced by Supersonic Turbulent Boundary Layers
超音速湍流边界层引起的压力脉动的 DNS
批准号:
1640865
负责人:
Lian Duan
金额:
$0.63万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2019-08-31

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中文摘要
翻译
了解湍流边界层引起的压力波动的物理性质具有重要的理论和实际意义。从实际应用的角度来看,飞行器气动表面的脉动压力在振动载荷中起着重要的作用,并经常导致疲劳和颤振等损伤效应。因此,深入了解边界引起的压力波动的性质对运载火箭的结构设计和其他重要应用至关重要。本工作旨在利用Blue Waters的计算能力,为深入了解超音速湍流边界层诱导的全局压力场以及不同流动条件下脉动压力场的依赖关系提供基础。这样的认识将推动壁面湍流的最新知识,并有助于壁面湍流的建模和控制。此外,该项目的更广泛影响将是使运输车辆节省宝贵的能源。克服湍流摩擦消耗了美国能源预算的很大一部分。2012年,美国各地的地面、空中或水上运输人员/货物的车辆消耗了超过年度能源消耗的四分之一来克服湍流摩擦。壁面湍流的研究将有助于更好的车辆设计和先进的交通工具流动控制技术的部署。此外,该项目的研究活动与教育和推广计划充分结合,以激励和满足下一代工程师不断增长的教育需求。本课题的研究目的是研究可压缩边界层中湍流压力场的结构。这将通过使用Blue Waters对可压缩湍流边界层进行高雷诺数直接数值模拟(DNS)来实现。现有的许多边界层压力波动分析都是基于不可压缩流动中的泊松方程,但对于超声速流动,压力场是由声波方程控制的,对其了解甚少。在这项工作中,PI将生成可压缩湍流边界层的高雷诺数DNS数据,从根本上了解边界层不同区域之间的非局部压力相关耦合。特别是,这项工作将侧重于研究压力统计数据及其缩放,并对各种频率/波数范围内压力波动的起源进行高保真的理解。
英文摘要
Understanding the physics of the pressure fluctuations induced by turbulent boundary layers are of major theoretical and practical importance. From a practical point of view, the fluctuating pressure on aerodynamic surfaces of flight vehicles plays an important role in vibrational loading and often leads to damaging effects as fatigue and flutter. An in-depth knowledge of the nature of boundary-induced pressure fluctuations is thus essential to the structural design of launch vehicles and other important applications. The proposed work aims to use the computational power of the Blue Waters to provide the basis for an in-depth understanding of the global pressure field induced by turbulent boundary layers at supersonic speeds and the dependence of the fluctuating pressure field at different flow conditions. Such an understanding will advance the state of the art knowledge of wall-bounded turbulence and contribute to the modeling and control of wall-bounded turbulence. Additionally, the broader impact of the project will be to enable valuable energy savings of transport vehicles. Overcoming turbulent friction consumes a large fraction of the United States energy budget. In 2012, vehicles that transport people/goods on ground, air or water throughout the U.S. consumed more than a quarter of the annual energy expenditure to overcome turbulent friction. The study of wall-bounded turbulent flows will contribute to better vehicle designs and the deployment of advanced flow control techniques for transport vehicles. Furthermore, the research activities of the project fully integrates with an education and outreach programs to inspire and meet the ever-increasing educational demands of next-generation engineers.The research objective of this project is to investigate the structure of the turbulentpressure field in compressible boundary layers. This will be achieved by carrying out high-Reynolds-number direct numerical simulations (DNS) of compressible turbulent boundary layers using Blue Waters. Many existing analysis of the boundary-layer-induced pressure fluctuations is based on the Poisson equation in the context of incompressible flows, but for supersonic flows the pressure field is governed by the acoustic wave equation and is significantly less understood. In this work, the PI will generate high-Reynolds-number DNS data of compressible turbulent boundary layers to fundamentally understand the non-local pressure-related coupling between different regions of the boundary layer. In particular, this work will focus on studying pressure statistics and their scaling and developing a high-fidelity understanding of the origin of the pressure fluctuations in various frequency/wave-number ranges.
期刊论文(7)
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科研奖励(0)
会议论文
DOI: 10.2514/1.a34290
发表时间: 2019
期刊: Journal of Spacecraft and Rockets
影响因子: 1.6
作者: [Duan, Lian, Choudhari, Meelan M., Chou, Amanda, Munoz, Federico, Radespiel, Rolf, Schilden, Thomas, Schröder, Wolfgang, Marineau, Eric C., Casper, Katya M., Chaudhry, Ross S.]
通讯作者: Chaudhry, Ross S.
High-Mach-Number Turbulence Modeling using Machine Learning and Direct Numerical Simulation Database
使用机器学习和直接数值模拟数据库进行高马赫数湍流建模
DOI: 10.2514/6.2017-0315
发表时间: 2017
期刊: 55th AIAA Aerospace Sciences Meeting
影响因子: --
作者: [Huang, Junji, Duan, Lian, Wang, Jianxun, Sun, Rui, Xiao, Heng]
通讯作者: Xiao, Heng
DOI: 10.1017/jfm.2017.212
发表时间: 2017-05
期刊: Journal of Fluid Mechanics
影响因子: 3.7
作者: [Chao Zhang;L. Duan;Meelan Choudhari]
通讯作者: Chao Zhang;L. Duan;Meelan Choudhari
Direct Numerical Simulation of Nozzle-Wall Pressure Fluctuations in a Mach 8 Wind Tunnel
8 马赫风洞中喷嘴壁压力脉动的直接数值模拟
DOI: 10.2514/6.2019-0874
发表时间: 2019
期刊: AIAA Scitech 2019 Forum
影响因子: --
作者: [Duan, Lian, Nicholson, Gary L., Huang, Junji, Casper, Katya M., Wagnild, Ross, Bitter, Neal]
通讯作者: Bitter, Neal
CBET-EPSRC: Transition and Turbulence in Compressible Boundary Layers Subjected to Concave Surface Curvature
Interaction of a Shock wave with a Homogeneous Field of Acoustic Waves: Theory and Simulation
  • 批准号:
    2001125
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $16.03万
  • 财政年份:
    2019
  • 负责人:
    Lian Duan
  • 依托单位:
CBET-EPSRC: Transition and Turbulence in Compressible Boundary Layers Subjected to Concave Surface Curvature
  • 批准号:
    2001127
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.5万
  • 财政年份:
    2019
  • 负责人:
    Lian Duan
  • 依托单位:
REU Site: Collaborative Research: Undergraduate Research in Computational Data Analytics for Advancing Human Services
  • 批准号:
    1659513
  • 项目类别:
    Standard Grant
  • 资助金额:
    $3.13万
  • 财政年份:
    2017
  • 负责人:
    Lian Duan
  • 依托单位:
海外基金