A posteriori error analysis of stabilised FEM for degenerate convex minimisation problems under weak regularity assumptions

BackgroundThe discretisation of degenerate convex minimisation problems experiences numerical difficulties with a singular or nearly singular Hessian matrix.MethodsSome discrete analog of the surface energy in microstrucures is added to the energy functional to define a stabilisation technique.ResultsThis paper proves (a) strong convergence of the stress even without any smoothness assumption for a class of stabilised degenerate convex minimisation problems. Given the limitted a priori error control in those cases, the sharp a posteriori error control is of even higher relevance. This paper derives (b) guaranteed a posteriori error control via some equilibration technique which does not rely on the strict Galerkin orthogonality of the unperturbed problem. In the presence of L2 control in the original minimisation problem, some realistic model scenario with piecewise smooth exact solution allows for strong convergence of the gradients plus refined a posteriori error estimates. This paper presents (c) an improved a posteriori error control in this interface problem and so narrows the efficiency reliability gap.ConclusionsNumerical experiments illustrate the theoretical convergence rates for uniform and adaptive mesh-refinements and the improved a posteriori error control for four benchmark examples in the computational microstructures.

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

[2]  Stefan A. Sauter,et al.  A Posteriori Error Estimation for the Dirichlet Problem with Account of the Error in the Approximation of Boundary Conditions , 2003, Computing.

[3]  Soeren Bartels Numerical Analysis of Some Non-Convex Variational Problems , 2006 .

[4]  R. Glowinski,et al.  Numerical Analysis of Variational Inequalities , 1981 .

[5]  Michel Chipot,et al.  Linearisation at infinity and Lipschitz estimates for certain problems in the calculus of variations , 1986, Proceedings of the Royal Society of Edinburgh: Section A Mathematics.

[6]  R. Kohn,et al.  Numerical study of a relaxed variational problem from optimal design , 1986 .

[7]  Carsten Carstensen,et al.  A Posteriori Finite Element Error Control for the P-Laplace Problem , 2003, SIAM J. Sci. Comput..

[8]  A. Ern,et al.  Guaranteed and robust a posteriori error estimates and balancing discretization and linearization errors for monotone nonlinear problems , 2011 .

[9]  Dorothee Knees,et al.  Global stress regularity of convex and some nonconvex variational problems , 2008 .

[10]  Carsten Carstensen,et al.  Adaptive Finite Element Methods for Microstructures? Numerical Experiments for a 2-Well Benchmark , 2003, Computing.

[11]  Mark Ainsworth,et al.  A Synthesis of A Posteriori Error Estimation Techniques for Conforming , Non-Conforming and Discontinuous Galerkin Finite Element Methods , 2005 .

[12]  Ricardo G. Durán,et al.  An optimal Poincare inequality in L^1 for convex domains , 2003 .

[13]  R. D. James,et al.  Proposed experimental tests of a theory of fine microstructure and the two-well problem , 1992, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.

[14]  Philippe G. Ciarlet,et al.  The finite element method for elliptic problems , 2002, Classics in applied mathematics.

[15]  J. Craggs Applied Mathematical Sciences , 1973 .

[16]  L. R. Scott,et al.  The Mathematical Theory of Finite Element Methods , 1994 .

[17]  Franco Brezzi Michel Fortin,et al.  Mixed and Hybrid Finite Element Methods (Springer Series in Computational Mathematics) , 1991 .

[18]  Carsten Carstensen,et al.  On the Strong Convergence of Gradients in Stabilized Degenerate Convex Minimization Problems , 2010, SIAM J. Numer. Anal..

[19]  Carsten Carstensen,et al.  Inhomogeneous Dirichlet conditions in a priori and a posteriori finite element error analysis , 2004, Numerische Mathematik.

[20]  Andreas Prohl,et al.  Convergence for stabilisation of degenerately convex minimisation problems , 2004 .

[21]  Carsten Carstensen,et al.  Mixed Finite Element Method for a Degenerate Convex Variational Problem from Topology Optimization , 2012, SIAM J. Numer. Anal..

[22]  Carsten Carstensen,et al.  Convergence of adaptive FEM for a class of degenerate convex minimization problems , 2007 .

[23]  S. Nicaise,et al.  An accurate H(div) flux reconstruction for discontinuous Galerkin approximations of elliptic problems , 2007 .

[24]  R. Kohn,et al.  Optimal design and relaxation of variational problems, III , 1986 .

[25]  Barbara I. Wohlmuth,et al.  A Local A Posteriori Error Estimator Based on Equilibrated Fluxes , 2004, SIAM J. Numer. Anal..

[26]  Carsten Carstensen,et al.  Remarks around 50 lines of Matlab: short finite element implementation , 1999, Numerical Algorithms.

[27]  Carsten Carstensen,et al.  Local Stress Regularity in Scalar Nonconvex Variational Problems , 2002, SIAM J. Math. Anal..

[28]  Michel Fortin,et al.  Mixed and Hybrid Finite Element Methods , 2011, Springer Series in Computational Mathematics.

[29]  Gabriel Wittum,et al.  Analysis and numerical studies of a problem of shape design , 1991 .

[30]  Carsten Carstensen,et al.  Numerical solution of the scalar double-well problem allowing microstructure , 1997, Math. Comput..

[31]  Carsten Carstensen,et al.  A convergent adaptive finite element method for an optimal design problem , 2007, Numerische Mathematik.

[32]  Michel Chipot,et al.  Elements of Nonlinear Analysis , 2000 .

[33]  S. Müller Variational models for microstructure and phase transitions , 1999 .