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Collaborative Research: Stochastic and Multiscale Structure Associated with the Navier Stokes Equations

Collaborative Research: Stochastic and Multiscale Structure Associated with the Navier Stokes Equations
合作研究:与纳维斯托克斯方程相关的随机和多尺度结构
批准号:
0073865
负责人:
Rabindra Bhattacharya
金额:
$13.6万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-08-01 至 2002-09-30

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中文摘要
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英文摘要
This project will develop the theory of the motion of fluids as embodied by the Navier-Stokes equations using new probabilistic methods that exploit the power of stochastic calculus and probabilistic limit theory. Although the Navier-Stokes equations are essentially deterministic, the approach used in this work will build on a representation of the equations as a functional of an underlying branching random walk. This representation, which was recently discovered by LeJan and Sznitman in France, is clearly intrinsic to the structure of the Navier-Stokes equations. While this is not the first attempt to use stochastic methods in connection with the flows associated with the Navier-Stokes equations, it does represent an entirely new direction which has the potential to transcend much of existing theory. Specific problems considered in this proposal seek to provide a better understanding of the role of spatial dimensions, boundary conditions, multi-scaling exponents and singularities, viscosity, homogeneity, isotropy and rotational accelerations, stationary flows and long-time evolution. The Navier-Stokes equations describe the basic physics governing the motion of fluid in its various forms of air, water, oil, etc. As such these equations play a fundamental role in science and engineering through the modeling of all varieties of fluid flow, from atmospheric and oceanic circulation to the flow of water beneath the earth's surface. Improved understanding of these equations and their solutions is essential to applications which range from tracking climate change and dispersion of contaminants in the Earth's environment, to more stable aerospace and sea vessel designs. The nonlinearity inherent in these equations makes explicit solutions possible only for the simplest of flows. Consequently the development of a more complete understanding of these equations at all physical length scales ranks among the most important outstanding problems of contemporary mathematical physics
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Nonparametric Statistical Image Analysis: Theory and Applications
  • 批准号:
    1811317
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2018
  • 负责人:
    Rabindra Bhattacharya
  • 依托单位:
Nonparametric Statistics and Riemannian Geometry in Image Analysis: New Perspectives with Applications in Biology, Medicine, Neuroscience and Machine Vision
  • 批准号:
    1406872
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $12.0万
  • 财政年份:
    2014
  • 负责人:
    Rabindra Bhattacharya
  • 依托单位:
Collaborative Research: New directions in nonparametric inference on manifolds with applications to shapes and images
  • 批准号:
    1107053
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $18.0万
  • 财政年份:
    2011
  • 负责人:
    Rabindra Bhattacharya
  • 依托单位:
Collaborative Research: Nonparametric Theory on Manifolds of Shapes and Images, with Applications to Biology, Medical Imaging and Machine Vision
  • 批准号:
    0806011
  • 项目类别:
    Standard Grant
  • 资助金额:
    $16.0万
  • 财政年份:
    2008
  • 负责人:
    Rabindra Bhattacharya
  • 依托单位:
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Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
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