UNS: Collaborative Research: Turbulent Flame Structure of Cavity Stabilized Reacting Shear Layers: Effects of Flow Compressibility, Heat Release, and Finite-rate Kinetics
UNS:合作研究:腔稳定反应剪切层的湍流火焰结构:流动压缩性、放热和有限速率动力学的影响
基本信息
- 批准号:1511520
- 负责人:
- 金额:$ 32.4万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-06-01 至 2019-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
1511791(Chelliah)/1511520(Cutler)/1510222(Edwards)High-speed and supersonic combustion is of vital importance to high-speed transport. The research team comprised of experimentalist and numerical modelers will try to understand, using a unique facility and state-of-art numerical models, how fuel burning at such high speed happens and how stable combustion can be achieved. A team of undergraduate and graduate students will be involved in the research and the data and results will be widely published. To understand the flame stabilization mechanism requires the understanding flame structure resulting from the interaction between the chemical reaction, which releases heat, and the flow. Under high-speed conditions, the flow is turbulent. The proposal focuses on this interaction under supersonic conditions where compressibility also plays a role. The flow geometry chosen is high-speed reacting shear flow over cavity, which is commonly believed to be a good candidate for supersonic combustion and propulsion. The proposed facility (located at the lead PI's institution - UVa) is unique, which has been developed over the past decades and is well and appropriately leveraged for the proposed research. Fundamental data on flame structure and statistics on key species are to be obtained experimentally. Computational results using DNS (Direct Numerical Simulation) will supplement the experiments to provide additional information not accessible from experiments in developing submodels, which can be used in the future development of high-speed propulsion combustors. The experimental data are of archival value. Close collaboration proposed with researchers from government labs would likely amplify its usefulness.
1511791(Chelliah)/1511520(Cutler)/1510222(Edwards)High-speed和超音速燃烧对高速运输至关重要。由实验者和数值建模人员组成的研究小组将使用独特的设备和最先进的数值模型,试图了解燃料如何在如此高速的情况下燃烧,以及如何实现稳定的燃烧。一个由本科生和研究生组成的团队将参与这项研究,数据和结果将广泛发布。要了解火焰稳定的机理,需要了解由释放热量的化学反应和流动之间的相互作用产生的火焰结构。在高速条件下,流动是湍动的。该提议的重点是在超音速条件下的这种相互作用,其中可压缩性也起着作用。所选择的流型为高速反应剪切流,通常被认为是超音速燃烧和推进的良好候选者。拟议的设施(位于牵头的国际和平研究所-UVA)是独一无二的,它是在过去几十年中发展起来的,并为拟议的研究充分和适当地利用了杠杆作用。火焰结构的基本数据和关键物种的统计数据将通过实验获得。使用直接数值模拟的计算结果将补充实验,在开发子模型时提供从实验中无法获得的额外信息,可用于未来高速推进燃烧室的开发。实验数据具有一定的档案价值。与政府实验室的研究人员提议的密切合作可能会扩大其用处。
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)
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Andrew Cutler其他文献
Navacaprant, a Novel Kappa Opioid Receptor Antagonist for Major Depressive Disorder: A Randomized Placebo-Controlled Phase 2 Trial
- DOI:
10.1016/j.biopsych.2024.02.031 - 发表时间:
2024-05-15 - 期刊:
- 影响因子:
- 作者:
Sanjay Mathew;Andrew Cutler;Nicole Visitacion;Michael Gold;Jason Yuan;Bill Aurora - 通讯作者:
Bill Aurora
RE-KINECT, A REAL-WORLD, PROSPECTIVE TARDIVE DYSKINESIA SCREENING STUDY: AN EVALUATION OF BASELINE CHARACTERISTICS IN OLDER PATIENTS
- DOI:
10.1016/j.jagp.2019.01.132 - 发表时间:
2019-03-01 - 期刊:
- 影响因子:
- 作者:
Stanley Caroff;Andrew Cutler;Caroline Tanner;Karen Yeomans;William Lenderking;Huda Shalhoub;Jun Chen;Ericha Anthony;Chuck Yonan - 通讯作者:
Chuck Yonan
Zuranolone in Major Depressive Disorder: Interim Safety Results From a Phase 3, Open-Label, Longitudinal Study
- DOI:
10.1016/j.biopsych.2021.02.413 - 发表时间:
2021-05-01 - 期刊:
- 影响因子:
- 作者:
Andrew Cutler;Scott T. Aaronson;Gregory W. Mattingly;Samuel T. Wilkinson;Robert Lasser;Indrani Nandy;Brian Werneburg;Jeffrey Jonas;Stephen J. Kanes;Timothy Mariano - 通讯作者:
Timothy Mariano
Psychometric properties of the Federal Unit Scale for general psychopathology screening without iatrogenic effects
无医源性影响的一般精神病理学筛查的联邦单位量表的心理测量特性
- DOI:
10.1016/j.jpsychires.2025.02.057 - 发表时间:
2025-04-01 - 期刊:
- 影响因子:3.200
- 作者:
Tyler M. Moore;Kathryn Walker;Franz Hell;Grayson Rosenblad;Andrew Cutler;Adam R. Teed;Maria (Coté) J. Auil;Rex Jung;Shobi S. Ahmed - 通讯作者:
Shobi S. Ahmed
The general factor of personality (GFP) in natural language: A deep learning approach
自然语言中的人格一般因素(GFP):一种深度学习方法
- DOI:
10.1016/j.jrp.2025.104635 - 发表时间:
2025-08-01 - 期刊:
- 影响因子:3.100
- 作者:
Dimitri van der Linden;Andrew Cutler;Putri A. van der Linden;Curtis S. Dunkel - 通讯作者:
Curtis S. Dunkel
Andrew Cutler的其他文献
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