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Velocity Gradient Statistics in Fully Developed Turbulence - Statistical Evolution Equations, DNS Investigations and Implications for Reduced Models

Velocity Gradient Statistics in Fully Developed Turbulence - Statistical Evolution Equations, DNS Investigations and Implications for Reduced Models
完全发展的湍流中的速度梯度统计 - 统计演化方程、DNS 研究和简化模型的含义
批准号:
224977886
负责人:
Dr. Michael Wilczek
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Fellowships
财政年份:
2012
资助国家:
德国
项目状态:
已结题
起止时间:
2011-12-31 至 2013-12-31

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中文摘要
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英文摘要
The small scales of fully developed hydrodynamic turbulence can be comprehensively characterized in terms of the derivatives of the velocity field, which define the velocity gradient tensor. In this project, the statistical properties of these small-scale features are studied within the framework of exact statistical equations governing the evolution of the probability density functions of the velocity gradient tensor. Due to the nonlinear and nonlocal character of the equations of fluid motion, the resulting statistical equations appear unclosed when only a finite number of spatial points is considered. Within the project, the information missing due to this closure problem will be contributed by data from direct numerical simulations. In particular, the influence of the local self-amplification, dissipation and nonlocal pressure contributions will be studied. The goal is to gain a deeper understanding of the impact of these dynamical contributions on the observed small-scale statistics. Apart from characterizing the shape and evolution of the studied statistical quantities, the results will help to formulate improved closures for low-dimensional stochastic models. By this, a natural connection between fundamental turbulence research and applied modeling, e.g. in the field of wind energy conversion, is established.
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DOI: 10.1088/1742-6596/524/1/012104
发表时间: 2014
期刊: Journal of Physics: Conference Series
影响因子: --
作者: [M. Wilczek, R.J.A.M. Stevens, Y. Narita, C. Meneveau]
通讯作者: C. Meneveau
Effective Description of Superstructures in Turbulent Convection and Simple Turbulent Shear Flows
国内基金
海外基金
基于肺结节多正交位CT图像Curvelet纹理构建 Gradient Boosting 集成预测模型
  • 批准号:
    81172772
  • 项目类别:
    面上项目
  • 资助金额:
    40.0万元
  • 批准年份:
    2011
  • 负责人:
    郭秀花
  • 依托单位: