Recovery methods for evolution and nonlinear problems

Functions in finite dimensional spaces are, in general, not smooth enough to be differentiable in the classical sense and “recovered” versions of their first and second derivatives must be sought for certain applications. In this work we make use of recovered derivatives for applications in finite element schemes for two different purposes. We thus split this Thesis into two distinct parts. In the first part we derive energy-norm aposteriori error bounds, using gradient recovery (ZZ) estimators to control the spatial error for fully discrete schemes of the linear heat equation. To our knowledge this is the first completely rigorous derivation of ZZ estimators for fully discrete schemes for evolution problems, without any restrictive assumption on the timestep size. An essential tool for the analysis is the elliptic reconstruction technique introduced as an aposteriori analog to the elliptic (Ritz) projection. Our theoretical results are backed up with extensive numerical experimentation aimed at (1) testing the practical sharpness and asymptotic behaviour of the error estimator against the error, and (2) deriving an adaptive method based on our estimators. An extra novelty is an implementation of a coarsening error “preindicator”, with a complete implementation guide in ALBERTA (versions 1.0–2.0). In the second part of this Thesis we propose a numerical method to approximate the solution of second order elliptic problems in nonvariational form. The method is of Galerkin type using conforming finite elements and applied directly to the nonvariational(or nondivergence) form of a second order linear elliptic problem. The key tools are an appropriate concept of the “finite element Hessian” based on a Hessian recovery and a Schur complement approach to solving the resulting linear algebra problem. The method is illustrated with computational experiments on linear PDEs in nonvariational form. We then use the nonvariational finite element method to build a numerical method for fully nonlinear elliptic equations. We linearise the problem via Newton’s method resulting in a sequence of nonvariational elliptic problems which are then approximated with the nonvariational finite element method. This method is applicable to general fully nonlinear PDEs who admit a unique solution without constraint. We also study fully nonlinear PDEs when they are only uniformly elliptic on a certain class of functions. We construct a numerical method for the Monge–Ampere equation based on using “finite element convexity” as a constraint for the aforementioned nonvariational finite element method. This method is backed up with numerical experimentation.

[1]  Jinchao Xu,et al.  Asymptotically Exact A Posteriori Error Estimators, Part I: Grids with Superconvergence , 2003, SIAM J. Numer. Anal..

[2]  Ricardo H. Nochetto,et al.  Elliptic reconstruction and a posteriori error estimates for fully discrete linear parabolic problems , 2006, Math. Comput..

[3]  Xiaobing Feng,et al.  Analysis of Galerkin Methods for the Fully Nonlinear Monge-Ampère Equation , 2007, J. Sci. Comput..

[4]  Pedro Morin,et al.  On Convex Functions and the Finite Element Method , 2008, SIAM J. Numer. Anal..

[5]  F. Brezzi,et al.  Finite dimensional approximation of nonlinear problems , 1981 .

[6]  Ricardo H. Nochetto,et al.  Data Oscillation and Convergence of Adaptive FEM , 2000, SIAM J. Numer. Anal..

[7]  Jinhai Chen,et al.  Convergence behaviour of inexact Newton methods under weak Lipschitz condition , 2006 .

[8]  H. Stetter Analysis of Discretization Methods for Ordinary Differential Equations , 1973 .

[9]  Xue-Cheng Tai,et al.  Superconvergence for the Gradient of Finite Element Approximations by L2 Projections , 2002, SIAM J. Numer. Anal..

[10]  Kunibert G. Siebert,et al.  A BASIC CONVERGENCE RESULT FOR CONFORMING ADAPTIVE FINITE ELEMENTS , 2008 .

[11]  N. Krylov On the general notion of fully nonlinear second-order elliptic equations , 1995 .

[12]  Wolfgang Dahmen,et al.  Adaptive Finite Element Methods with convergence rates , 2004, Numerische Mathematik.

[13]  Carsten Carstensen,et al.  Each averaging technique yields reliable a posteriori error control in FEM on unstructured grids. Part I: Low order conforming, nonconforming, and mixed FEM , 2002, Math. Comput..

[14]  Alfred H. Schatz SOME NEW LOCAL ERROR ESTIMATES IN NEGATIVE NORMS WITH AN APPLICATION TO LOCAL A POSTERIORI ERROR ESTIMATION , 2006 .

[15]  Mark Ainsworth,et al.  A Posteriori Error Estimators and Adaptivity for Finite Element Approximation of the Non-Homogeneous Dirichlet Problem , 2001, Adv. Comput. Math..

[16]  Joseph E. Pasciak,et al.  On the stability of the L2 projection in H1(Omega) , 2002, Math. Comput..

[17]  Zhimin Zhang A Posteriori Error Estimates on Irregular Grids Based on Gradient Recovery , 2001, Adv. Comput. Math..

[18]  Carsten Carstensen,et al.  Merging the Bramble-Pasciak-Steinbach and the Crouzeix-Thomée criterion for H1-stability of the L2-projection onto finite element spaces , 2002, Math. Comput..

[19]  O. Lakkis,et al.  Gradient recovery in adaptive finite-element methods for parabolic problems , 2009, 0905.2764.

[20]  Jeffrey S. Ovall Function, Gradient, and Hessian Recovery Using Quadratic Edge-Bump Functions , 2007, SIAM J. Numer. Anal..

[21]  Yuri V. Vassilevski,et al.  On a discrete Hessian recovery for P 1 finite elements , 2002, J. Num. Math..

[22]  L. R. Scott,et al.  Finite element interpolation of nonsmooth functions satisfying boundary conditions , 1990 .

[23]  Christian Kreuzer,et al.  Quasi-Optimal Convergence Rate for an Adaptive Finite Element Method , 2008, SIAM J. Numer. Anal..

[24]  Zhimin Zhang,et al.  Analysis of recovery type a posteriori error estimators for mildly structured grids , 2003, Math. Comput..

[25]  A. Schmidt,et al.  Design of Adaptive Finite Element Software , 2005 .

[26]  R. Jensen The maximum principle for viscosity solutions of fully nonlinear second order partial differential equations , 1988 .

[27]  Omar Lakkis,et al.  A Posteriori Error Control for Discontinuous Galerkin Methods for Parabolic Problems , 2008, SIAM J. Numer. Anal..

[28]  Nils-Erik Wiberg,et al.  Adaptive procedure with superconvergent patch recovery for linear parabolic problems , 1997 .

[29]  Alan Demlow,et al.  A Posteriori Error Estimates in the Maximum Norm for Parabolic Problems , 2007, SIAM J. Numer. Anal..

[30]  Long Chen,et al.  Optimal anisotropic meshes for minimizing interpolation errors in Lp-norm , 2007, Math. Comput..

[31]  Christine Bernardi,et al.  A posteriori analysis of the finite element discretization of some parabolic equations , 2004, Math. Comput..

[32]  Endre Süli,et al.  Sparse finite element approximation of high-dimensional transport-dominated diffusion problems , 2008 .

[33]  Roland Glowinski,et al.  Numerical methods for fully nonlinear elliptic equations of the Monge-Ampère type , 2006 .

[34]  Volker John,et al.  A numerical study of a posteriori error estimators for convection–diffusion equations , 2000 .

[35]  Eun-Jae Park,et al.  Mixed finite element methods for nonlinear second-order elliptic problems , 1995 .

[36]  P. Clément Approximation by finite element functions using local regularization , 1975 .

[37]  Bo Li,et al.  Analysis of a Class of Superconvergence Patch Recovery Techniques for Linear and Bilinear Finite Elements , 1999 .

[38]  Klaus Böhmer,et al.  On Finite Element Methods for Fully Nonlinear Elliptic Equations of Second Order , 2008, SIAM J. Numer. Anal..

[39]  Jinchao Xu,et al.  Recent Progress in Computational and Applied PDES , 2002 .

[40]  Kenneth Eriksson,et al.  Adaptive finite element methods for parabolic problems. I.: a linear model problem , 1991 .

[41]  Zhimin Zhang,et al.  Superconvergence of the Derivative Patch Recovery Technique and A Posteriori Error Estimation , 1995 .

[42]  Gabriel Wittum,et al.  Asymptotically exact a posteriori estimators for the pointwise gradient error on each element in irregular meshes. Part 1: A smooth problem and globally quasi-uniform meshes , 2001, Math. Comput..

[43]  Mary Fanett A PRIORI L2 ERROR ESTIMATES FOR GALERKIN APPROXIMATIONS TO PARABOLIC PARTIAL DIFFERENTIAL EQUATIONS , 1973 .

[44]  Omar Lakkis,et al.  Elliptic reconstruction and a posteriori error estimates for fully discrete linear parabolic problems , 2006, Math. Comput..

[45]  Jia Feng,et al.  An adaptive finite element algorithm with reliable and efficient error control for linear parabolic problems , 2004, Math. Comput..

[46]  P. Bassanini,et al.  Elliptic Partial Differential Equations of Second Order , 1997 .

[47]  Adam M. Oberman A convergent difference scheme for the infinity Laplacian: construction of absolutely minimizing Lipschitz extensions , 2004, Math. Comput..

[48]  R. Verfürth A posteriori error estimates for nonlinear problems: finite element discretizations of elliptic equations , 1994 .

[49]  C. Kelley Iterative Methods for Linear and Nonlinear Equations , 1987 .

[50]  Lars B. Wahlbin,et al.  Asymptotically exact a posteriori estimators for the pointwise gradient error on each element in irregular meshes. Part II: The piecewise linear case , 2004, Math. Comput..

[51]  M. Picasso Adaptive finite elements for a linear parabolic problem , 1998 .

[52]  Wenbin Liu,et al.  A posteriori FE error control for p-Laplacian by gradient recovery in quasi-norm , 2006, Math. Comput..

[53]  Dmitriy Leykekhman,et al.  A posteriori error estimates by recovered gradients in parabolic finite element equations , 2008 .

[54]  Marco Picasso,et al.  An Anisotropic Error Indicator Based on Zienkiewicz-Zhu Error Estimator: Application to Elliptic and Parabolic Problems , 2002, SIAM J. Sci. Comput..

[55]  Panagiotis E. Souganidis,et al.  A rate of convergence for monotone finite difference approximations to fully nonlinear, uniformly elliptic PDEs , 2008 .

[56]  Dmitriy Leykekhman,et al.  Pointwise localized error estimates for parabolic finite element equations , 2004, Numerische Mathematik.

[57]  Andreas Veeser,et al.  A posteriori error estimators, gradient recovery by averaging, and superconvergence , 2006, Numerische Mathematik.