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: Missouri University of Science and Technology
• 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
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640865&HistoricalAwards=false
• 关键词: DNS; Pressure; Fluctuations; Induced; Supersonic

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.

了解湍流边界层引起的压力脉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，作用在飞行器气动表面上的脉动压力在振动载荷中起着重要的作用，并且常常导致疲劳和颤振等破坏性效应。 因此，深入了解边界引起的压力波动的性质对于运载火箭和其他重要应用的结构设计是必不可少的。拟议的工作旨在使用蓝色沃茨的计算能力，以提供基础，在超音速的湍流边界层引起的全球压力场的深入了解和在不同的流动条件下的波动压力场的依赖。这一认识将有助于提高对壁面湍流的认识，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。克服动荡的摩擦消耗了美国能源预算的很大一部分。2012年，在美国各地的地面、空中或水上运输人员/货物的车辆消耗了超过四分之一的年度能源支出来克服湍流摩擦。壁面湍流的研究将有助于更好的车辆设计和先进的流动控制技术的运输车辆的部署。此外，该项目的研究活动充分结合了教育和推广计划，以激发和满足下一代工程师不断增长的教育需求。该项目的研究目标是研究可压缩边界层中的粘性压力场的结构。这将通过使用Blue沃茨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。许多现有的边界层诱导的压力波动的分析是基于泊松方程在不可压缩流的背景下，但超音速流的压力场是由声波方程，是明显不太了解。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，以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及其缩放，并在各种频率/波数范围内对压力波动的起源进行高保真度的理解。

项目成果

Characterization of Freestream Disturbances in Conventional Hypersonic Wind Tunnels

传统高超声速风洞中自由流扰动的表征

• 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
• 作者: Huang, Junji;Duan, Lian;Wang, Jianxun;Sun, Rui;Xiao, Heng
• 通讯作者: Xiao, Heng

Effect of wall cooling on boundary-layer-induced pressure fluctuations at Mach 6

• 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

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
• 作者: Duan, Lian;Nicholson, Gary L.;Huang, Junji;Casper, Katya M.;Wagnild, Ross;Bitter, Neal
• 通讯作者: Bitter, Neal

Prediction of Reynolds stresses in high-Mach-number turbulent boundary layers using physics-informed machine learning

• DOI: 10.1007/s00162-018-0480-2
• 发表时间: 2018-08
• 期刊: Theoretical and Computational Fluid Dynamics
• 影响因子: 3.4
• 作者: Jian-Xun Wang;Junji Huang;L. Duan;Heng Xiao