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Numerical Methods and Algorithms for Fully Nonlinear Second Order Evolution Equations with Applications

Numerical Methods and Algorithms for Fully Nonlinear Second Order Evolution Equations with Applications
全非线性二阶演化方程的数值方法和算法及其应用
批准号:
1016173
负责人:
Xiaobing Feng
金额:
$22.5万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-08-15 至 2014-07-31

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中文摘要
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英文摘要
Fully nonlinear second order partial differential equations (PDEs) are referred to a class of nonlinear second order PDEs which are nonlinear in (at least one) second order partial derivatives of unknown functions. Such a class of PDEs arise from many scientific and engineering fields including astrophysics, differential geometry, geostrophic fluid dynamics, image processing, kinetic theory, materials science, mass transportation, meteorology, and optimal control. They constitute the most difficult class of PDEs to analyze analytically and to approximate numerically. Building on the PI's recent success on developing convergent and efficient numerical methods and algorithms for fully nonlinear second order (time-independent) elliptic PDEs, the proposed research project intends to carry out a comprehensive and systematic study of numerical methods and algorithms for fully nonlinear second order (time-dependent) evolution PDEs. The objectives of the proposed research include (i) to develop the vanishing moment method and the moment solution theory for fully nonlinear second order evolution PDEs, (ii) to develop fully discrete Galerkin type numerical methods (e.g. finite element methods, mixed finite element methods, spectral and discontinuous Galerkin methods) for fully nonlinear second order evolution PDEs based on the vanishing moment methodology, (iii) to apply and/or to adapt the developed numerical methods to a number of emerging application problems which are governed by fully nonlinear second order PDEs, (iv) to develop computer codes for implementing the proposed numerical methods. As numerical approximations of fully nonlinear second order evolution PDEs is an untouched sub-area within the numerical PDEs and those PDEs arise from many important applications in astrophysics, differential geometry, geostrophic fluid dynamics, image processing, kinetic theory, materials science, mass transportation, meteorology, and optimal control, the completion of the proposed research project is expected to have a profound impact on solving this class of PDEs and on providing the much needed capability and enabling tools for solving a range of important application problems which are governed by fully nonlinear second order PDEs. As a by-product, the moment solution theory is expected to give some insights to our understanding of the viscosity solution theory, and might be very likely to provide a logical and natural generalization and extension for the viscosity solution theory which is not natural and neither practical from the computational point of view. The educational component of this project is to engage and train graduate students in developing necessary applied and computational mathematics knowledge and skills so that they can pursue a successful career in science and engineering in the future.
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Novel Numerical Methods for Nonlinear Stochastic PDEs and High Dimensional Computation
  • 批准号:
    2309626
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $37.96万
  • 财政年份:
    2023
  • 负责人:
    Xiaobing Feng
  • 依托单位:
Efficient Numerical Methods and Algorithms for Nonlinear Stochastic Partial Differential Equations
  • 批准号:
    2012414
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.5万
  • 财政年份:
    2020
  • 负责人:
    Xiaobing Feng
  • 依托单位:
Novel numerical methods for fully nonlinear second order elliptic and parabolic Monge-Ampere and Hamilton-Jacobi-Bellman equations
  • 批准号:
    1620168
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $27.0万
  • 财政年份:
    2016
  • 负责人:
    Xiaobing Feng
  • 依托单位:
Novel Discontinuous Galerkin Finite Element Methods for Second Order Fully Nonlinear Equations and High Frequency Wave Equations
  • 批准号:
    1318486
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.0万
  • 财政年份:
    2013
  • 负责人:
    Xiaobing Feng
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data