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An adaptive high order discontinuous Galerkin method with error control for the Hamilton-Jacobi equations.

机译:Hamilton-Jacobi方程的带误差控制的自适应高阶不连续Galerkin方法。

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摘要

In the first part of this thesis, we propose and study an adaptive version of the discontinuous Galerkin method for the one-dimensional Hamilton-Jacobi equations. It works as follows. Given the tolerance and the degree of the polynomial of the approximate solution, the adaptive algorithm finds a mesh on which the approximate solution has an Linfinity-distance to the viscosity solution no bigger than the prescribed tolerance. The algorithm uses three main tools. The first is an iterative solver combining the explicit Runge-Kutta Discontinuous Galerkin method and the implicit Newton's method that enables us to solve the Hamilton-Jacobi equations efficiently. The second is a new a posteriori error estimate based on the approximate resolution of an approximate problem for the actual error. The third is a method that allows us to find a new mesh as a function of the old mesh and the ratio of the a posteriori error estimate to the tolerance. We display extensive numerical evidence that indicates that, for any given polynomial degree, the method achieves its goal with optimal complexity independently of the tolerance. This is done in the framework of one-dimensional steady-state model problems with periodic boundary conditions. The second part of this thesis is devoted to a study of the discontinuous Galerkin method for the two-dimensional steady-state Hamilton-Jacobi equations. The algorithm is also based on an iterative solver combining the explicit Runge-Kutta discontinuous Galerkin finite element method and the implicit Newton's method. There are two main contributions of this algorithm. The first is an appropriate incorporation of a slope limiter into the Newton's method. The second is the recovery of the solution to the Hamilton-Jacobi equations from that to the corresponding conservation laws. As a result, at least (k + 1)-th and k-th order of accuracy, for even and odd k respectively, is observed for smooth problems when k-th degree polynomials are used. We also study a simple adaptive version of this method applied to problems with nonsmooth solutions. Given the degree of the polynomial of the approximate solution, k ≥ 2, the algorithm starts with a uniform mesh and refines the subsequent meshes nonuniformly depending on whether the slope limiter is applied or not. We obtain faster convergence to the viscosity solution when the adaptive method is applied. This is done in the framework of two-dimensional steady-state model problems with periodic boundary conditions.
机译:在本文的第一部分中,我们提出并研究了针对一维Hamilton-Jacobi方程的不连续Galerkin方法的自适应版本。它的工作原理如下。给定近似解的容差和多项式度,自适应算法会找到一个网格,在该网格上,近似解与粘度解的Linfinity距离不大于规定的容差。该算法使用三个主要工具。第一个是将显式Runge-Kutta间断Galerkin方法和隐式牛顿方法相结合的迭代求解器,使我们能够有效地求解Hamilton-Jacobi方程。第二种是基于实际误差的近似问题的近似分辨率的新的后验误差估计。第三种是允许我们根据旧网格以及后验误差估计值与公差之比找到新网格的方法。我们显示了广泛的数值证据,表明对于任何给定的多项式,该方法均能以最佳复杂度实现其目标,而与公差无关。这是在具有周期边界条件的一维稳态模型问题的框架内完成的。本文的第二部分专门研究二维稳态哈密顿-雅各比方程的不连续伽勒金方法。该算法还基于将显式Runge-Kutta不连续Galerkin有限元方法和隐式Newton方法相结合的迭代求解器。该算法有两个主要贡献。首先是在牛顿法中适当结合了一个斜率限制器。第二个是从汉密尔顿-雅各比方程的解到相应的守恒律的恢复。结果,当使用第k次多项式时,对于平滑问题,分别观察到至少偶数和奇数k的至少(k +1)和k阶精度。我们还研究了此方法的简单自适应版本,适用于非光滑解的问题。给定近似解的多项式度数k≥2,该算法从均匀网格开始,然后根据是否应用斜率限制器,不均匀地细化后续网格。当采用自适应方法时,我们可以更快地收敛到粘度解。这是在具有周期边界条件的二维稳态模型问题的框架内完成的。

著录项

  • 作者

    Chen, Yanlai.;

  • 作者单位

    University of Minnesota.;

  • 授予单位 University of Minnesota.;
  • 学科 Mathematics.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 93 p.
  • 总页数 93
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 数学;
  • 关键词

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