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Vortex Models of Turbulence and Large-Eddy Simulation

Vortex Models of Turbulence and Large-Eddy Simulation
湍流涡模型和大涡模拟
批准号:
9634222
负责人:
Dale Pullin
金额:
$25.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1996
资助国家:
美国
项目状态:
已结题
起止时间:
1996-09-01 至 1999-08-31

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英文摘要
ABSTRACT Proposal Number: 9634222 Principal Investigator: Pullin This is a continuation grant to investigate the role of dynamics and kinematics of stretched vortices in describing the fine scales of turbulence with special emphasis on the relation of the fine and inertial range scales to the large scales in the context of large eddy simulation. The research will focus on three areas: a) continued development and testing of an LES model of for flows of increasing complexity, b) completion of the calculation of the longitudinal-velocity structure functions followed by the calculation of other structure functions of other turbulence quantities such as pressure and dissipation, and c) continuation of supporting research in vortex dynamics which will enhance our understanding of the structure of turbulence. This is an extension of prior work in which a standard model of turbulence was developed on the basis of the stretched vortex model of Lundgren.
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Maximum Entropy Closure of Boltzmann-Equation Moment-Hierarchy
  • 批准号:
    1418903
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.89万
  • 财政年份:
    2014
  • 负责人:
    Dale Pullin
  • 依托单位:
Large-eddy simulation of smooth and rough-wall turbulent boundary-layer flows at arbitrary Reynolds numbers
  • 批准号:
    1235605
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.98万
  • 财政年份:
    2012
  • 负责人:
    Dale Pullin
  • 依托单位:
Multi-scale geometry of Lagrangian and vortex-surface fields in turbulence
  • 批准号:
    1016111
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2010
  • 负责人:
    Dale Pullin
  • 依托单位:
Multi-scale, Geometrical Study of Eddy-structure in Turbulence
  • 批准号:
    0714050
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.75万
  • 财政年份:
    2007
  • 负责人:
    Dale Pullin
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
新型手性NAD(P)H Models合成及生化模拟