CAREER: Transition to Turbulence and Mixing for Rayleigh Taylor Instability with Acceleration Reversal
职业生涯:加速反转的瑞利泰勒不稳定性过渡到湍流和混合
基本信息
- 批准号:1453056
- 负责人:
- 金额:$ 50万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-06-01 至 2021-11-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
1453056BanerjeeThe focus of this proposal is to use both computational and experimental components to elucidate mixing in variable density turbulence (i.e., when two fluids of different density mix because of turbulence). The bulk of prior research in this area has focused on the easier case of transport of mass without effects on the flow field, and on canonical flows (e.g., channel flows, jet flows, boundary layers). The proposed research aims to overcome the difficulties associated with experimental studies of non-canonical flows (these flows are the ones commonly found in industry and in nature), and to measure turbulence quantities in unprecedented details in new settings. Such work can open up developments in other areas of fluid dynamics, including multiphase flow, heat transfer and combustion and shock-driven flows. The proposed educational activities include the involvement of a local community college in the PI's research, the development of an educational video series that would be available through iTunes, and the inclusion of 8th to 12th graders in summer camps for research. The goal of the proposed research is to investigate the Rayleigh-Taylor instability in variable density flows using both experiments and simulations. This instability occurs when two fluids of different density are in contact, and the denser fluid is accelerated by the lighter fluid. The PI has built a rather unique experimental facility that would enable him to complete the experimental part of the proposed work. It is a device that allows the control of acceleration and deceleration of the fluid in a rotating system. The experimental system even allows the switch from acceleration to deceleration and then further reversals of acceleration. The PI proposes the use of planar laser-induced fluorescence, PLIF, and stereo-Particle Image Velocimetry to obtain high order statistics for the flow and scalar fields. In order to complement the experiments with state-of-the-art simulations, the PI has established a collaboration with LANL to conduct direct numerical simulations (DNS) of the flow.
该建议的重点是使用计算和实验组件来阐明变密度湍流中的混合(即,当不同密度的两种流体由于湍流而混合时)。在这一领域的大量先前研究集中在对流场没有影响的质量传输的更容易的情况下,以及规范流(例如,槽流、射流、边界层)。拟议的研究旨在克服与非规范流(这些流是在工业和自然界中常见的)的实验研究相关的困难,并在新的设置中以前所未有的细节测量湍流量。这些工作可以开辟流体动力学其他领域的发展,包括多相流,传热和燃烧以及冲击驱动流。拟议的教育活动包括让当地一所社区学院参与PI的研究,开发一个教育视频系列,通过iTunes提供,并将8至12年级学生纳入夏令营进行研究。本文的目的是通过实验和模拟研究变密度流中的瑞利-泰勒不稳定性。这种不稳定性发生在两种不同密度的流体接触时,并且较轻的流体加速了较重的流体。PI已经建立了一个相当独特的实验设施,使他能够完成拟议工作的实验部分。它是一种允许控制旋转系统中流体加速和减速的装置。实验系统甚至允许从加速切换到减速,然后进一步逆转加速。PI建议使用平面激光诱导荧光,PLIF,和立体粒子图像测速获得高阶统计的流量和标量场。为了用最先进的模拟来补充实验,PI与LANL建立了合作关系,对流动进行直接数值模拟(DNS)。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Two-point spectral model for variable-density homogeneous turbulence
变密度均匀湍流的两点谱模型
- DOI:10.1103/physrevfluids.3.124608
- 发表时间:2018
- 期刊:
- 影响因子:2.7
- 作者:Pal, Nairita;Kurien, Susan;Clark, Timothy;Aslangil, Denis;Livescu, Daniel
- 通讯作者:Livescu, Daniel
Numerical investigation of initial condition effects on Rayleigh-Taylor instability with acceleration reversals
- DOI:10.1103/physreve.94.053114
- 发表时间:2016-11-18
- 期刊:
- 影响因子:2.4
- 作者:Aslangil, Denis;Banerjee, Arindam;Lawrie, Andrew G. W.
- 通讯作者:Lawrie, Andrew G. W.
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Arindam Banerjee其他文献
Passive and reactive scalar measurements in a transient high-Schmidt-number Rayleigh–Taylor mixing layer
- DOI:
10.1007/s00348-012-1328-y - 发表时间:
2012-06-05 - 期刊:
- 影响因子:2.500
- 作者:
Arindam Banerjee;Lakshmi Ayyappa Raghu Mutnuri - 通讯作者:
Lakshmi Ayyappa Raghu Mutnuri
Integral Closure of Powers of Edge Ideals of Weighted Oriented Graphs
- DOI:
10.1007/s40306-024-00558-0 - 发表时间:
2024-10-17 - 期刊:
- 影响因子:0.300
- 作者:
Arindam Banerjee;Kanoy Kumar Das;Sirajul Haque - 通讯作者:
Sirajul Haque
AmbientFlow: Invertible generative models from incomplete, noisy measurements
AmbientFlow:来自不完整、噪声测量的可逆生成模型
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Varun A. Kelkar;Rucha Deshpande;Arindam Banerjee;M. Anastasio - 通讯作者:
M. Anastasio
Technology acceptance model and customer engagement: mediating role of customer satisfaction
技术接受模型和客户参与:客户满意度的中介作用
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:3
- 作者:
R. P. Kumar;Arindam Banerjee;Zahran Al;S. Ananda - 通讯作者:
S. Ananda
Private equity in developing nations
- DOI:
10.1057/jam.2008.12 - 发表时间:
2008-06-23 - 期刊:
- 影响因子:1.400
- 作者:
Arindam Banerjee - 通讯作者:
Arindam Banerjee
Arindam Banerjee的其他文献
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{{ truncateString('Arindam Banerjee', 18)}}的其他基金
NRT - Stakeholder Engaged Equitable Decarbonized Energy Futures
NRT - 利益相关者参与的公平脱碳能源期货
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2244162 - 财政年份:2023
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$ 50万 - 项目类别:
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Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
合作研究:基于物理的机器学习用于次季节气候预测
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2130835 - 财政年份:2021
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
III: Small: Stochastic Algorithms for Large Scale Data Analysis
III:小型:大规模数据分析的随机算法
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2131335 - 财政年份:2021
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$ 50万 - 项目类别:
Continuing Grant
PFI-TT: Advancing the Technology Readiness of Pylon Fairings for Tidal Turbines
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- 批准号:
1919184 - 财政年份:2019
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$ 50万 - 项目类别:
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III:小型:大规模数据分析的随机算法
- 批准号:
1908104 - 财政年份:2019
- 资助金额:
$ 50万 - 项目类别:
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Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
合作研究:基于物理的机器学习用于次季节气候预测
- 批准号:
1934634 - 财政年份:2019
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
Towards an improved understanding of tidal turbine dynamics in a turbulent marine environment
提高对湍流海洋环境中潮汐涡轮机动力学的理解
- 批准号:
1706358 - 财政年份:2017
- 资助金额:
$ 50万 - 项目类别:
Standard Grant
III: Medium: Collaborative Research: Bayesian Modeling and Inference for Quantifying Terrestrial Ecosystem Functions
III:媒介:协作研究:量化陆地生态系统功能的贝叶斯建模和推理
- 批准号:
1563950 - 财政年份:2016
- 资助金额:
$ 50万 - 项目类别:
Continuing Grant
BIGDATA: F: DKA: Collaborative Research: High-Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data
BIGDATA:F:DKA:协作研究:时空气候数据的高维统计机器学习
- 批准号:
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$ 50万 - 项目类别:
Standard Grant
EAGER: Collaborative Research: Learning Relations between Extreme Weather Events and Planet-Wide Environmental Trends
EAGER:合作研究:学习极端天气事件与全球环境趋势之间的关系
- 批准号:
1451986 - 财政年份:2014
- 资助金额:
$ 50万 - 项目类别:
Standard Grant
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