Linear Finite Element Approximation Research Articles

Finite element approximations of nonlinear eigenvalue problems in quantum physics

In this paper, we study finite element approximations of a class of nonlinear eigenvalue problems arising from quantum physics. We derive both a priori and a posteriori finite element error estimates and obtain optimal convergence rates for both linear and quadratic finite element approximations. In particular, we analyze the convergence and complexity of an adaptive finite element method. In our analysis, we utilize certain relationship between the finite element eigenvalue problem and the associated finite element boundary value approximations. We also present several numerical examples in quantum physics that support our theory.

A simple yet effective a posteriori estimator for classical mixed approximation of Stokes equations

The implementation of quadratic velocity, linear pressure finite element approximation methods for the steady-state incompressible (Navier–)Stokes equations is addressed in this work. Three types of a posteriori error indicator are introduced and are shown to give global error estimates that are equivalent to the true discretisation error. Computational results suggest that the solution of local Poisson problems provides a cost-effective error estimation strategy, both from the perspective of accurate estimation of the global error and for the purpose of selecting elements for refinement within a contemporary self-adaptive refinement algorithm.

Quasi-Optimal Triangulations for Gradient Nonconforming Interpolates of Piecewise Regular Functions

Anisotropic adaptive methods based on a metric related to the Hessian of the solution are considered. We propose a metric targeted to the minimization of interpolation error gradient for a nonconforming linear finite element approximation of a given piecewise regular function on a polyhedral domain Ω of ℝ d , d ≥ 2. We also present an algorithm generating a sequence of asymptotically quasi-optimal meshes relative to such a nonconforming discretization and give numerical asymptotic behavior of the error reduction produced by the generated mesh

Recovery-Based Error Estimators for Interface Problems: Mixed and Nonconforming Finite Elements

In [Z. Cai and S. Zhang, SIAM J. Numer. Anal., 47 (2009), pp. 2132–2156], we introduced and analyzed a recovery-based a posteriori error estimator for conforming linear finite element approximation to interface problems. It was shown theoretically that the estimator is robust with respect to the size of jumps provided that the distribution of coefficients is locally monotone. Numerical examples showed that this condition is unnecessary. This paper extends the idea in [Z. Cai and S. Zhang, SIAM J. Numer. Anal., 47 (2009), pp. 2132–2156] to mixed and nonconforming finite element methods for developing and analyzing robust estimators. Numerical results on test problems are also presented. Moreover, an a priori error estimate is obtained when the underlying problem has low regularity.

On Positivity and Maximum-Norm Contractivity in Time Stepping Methods for Parabolic Equations

Abstract In an earlier paper the last two authors studied spatially semidiscrete piecewise linear finite element approximations of the heat equation and showed that, in the case of the standard Galerkin method, the solution operator of the initial-value problem is neither positive nor contractive in the maximum-norm for small time, but that for the lumped mass method these properties hold, if the triangulations are essentially of Delaunay type. In this paper we continue the study by considering fully discrete analogues obtained by discretization also in time. The above properties then carry over to the backward Euler time stepping method, but for other methods the results are more restrictive. We discuss in particular the θ-method and the (0; 2) Padé approximation in one space dimension.

Optimal L ∞-Error Estimate of a Finite Element Method for Hamilton–Jacobi–Bellman Equations

This paper is concerned with the piecewise linear finite element approximation of Hamilton–Jacobi–Bellman equations. We establish the optimal L ∞-error estimate, combining the concepts of subsolution and discrete regularity.

Solution of a Class of Minimal Surface Problem with Obstacle

Plateau’s problem is to determine the surface with minimal area that lies above an obstacle with given boundaryconditions. In this paper, a special example of this class of the problem is given and solved with the linearfinite element method. First, we triangulate the domain of definition, and transform the linear finite elementapproximation into a constrained nonlinear optimization problem. Then we introduce a simple and efficientmethod, named sequential quadratic programming, for solving the constrained nonlinear optimization problem.The sequential quadratic programming is implemented by the fmincon function in the optimization toolbox ofMATLAB. Also, we discuss the relations between the number of grids and the computing time as well as theprecision of the result.

Recovery-Based Error Estimator for Interface Problems: Conforming Linear Elements

This paper studies a new recovery-based a posteriori error estimator for the conforming linear finite element approximation to elliptic interface problems. Instead of recovering the gradient in the continuous finite element space, the flux is recovered through a weighted $L^2$ projection onto $H(\mathrm{div})$ conforming finite element spaces. The resulting error estimator is analyzed by establishing the reliability and efficiency bounds and is supported by numerical results. This paper also proposes an adaptive finite element method based on either the recovery-based estimators or the edge estimator through local mesh refinement and establishes its convergence. In particular, it is shown that the reliability and efficiency constants as well as the convergence rate of the adaptive method are independent of the size of jumps.

A multiscale finite element space–time discretization method for transient transport phenomena using bubble functions

A space–time finite element discretization method for unsteady transport phenomena is formulated using a variational multiscale finite element scheme. The described discretization is based on the utilization of bubble function enriched finite elements. The scheme is applied to model unsteady diffusion and convection–diffusion equations. It is shown that any temporal and spatial instabilities can be removed by appropriate enrichment of linear Lagrangian finite element approximations in the context of the standard Galerkin method. The proposed scheme is compared with widely used θ time stepping method. Numerical results generated by the proposed scheme are validated via their comparison with the analytical solution of a bench mark problem.

The discrete maximum principle for linear simplicial finite element approximations of a reaction–diffusion problem

This paper provides a sufficient condition for the discrete maximum principle for a fully discrete linear simplicial finite element discretization of a reaction–diffusion problem to hold. It explicitly bounds the dihedral angles and heights of simplices in the finite element partition in terms of the magnitude of the reaction coefficient and the spatial dimension. As a result, it can be computed how small the acute simplices should be for the discrete maximum principle to be valid. Numerical experiments suggest that the bound, which considerably improves a similar bound in [P.G. Ciarlet, P.-A. Raviart, Maximum principle and uniform convergence for the finite element method, Comput. Methods Appl. Mech. Eng. 2 (1973) 17–31.], is in fact sharp.

Cascadic multigrid methods for parabolic problems

In this paper, we consider the cascadic multigrid method for a parabolic type equation. Backward Euler approximation in time and linear finite element approximation in space are employed. A stability result is established under some conditions on the smoother. Using new and sharper estimates for the smoothers that reflect the precise dependence on the time step and the spatial mesh parameter, these conditions are verified for a number of popular smoothers. Optimal error bounds are derived for both smooth and non-smooth data. Iteration strategies guaranteeing both the optimal accuracy and the optimal complexity are presented.

Domain decomposition preconditioners for elliptic equations with jump coefficients

AbstractThis paper provides a proof of the robustness of the overlapping domain decomposition preconditioners for the linear finite element approximation of second‐order elliptic boundary value problems with strongly discontinuous coefficients. By analyzing the eigenvalue distribution of the domain decomposition preconditioned system, we prove that only a small number of eigenvalues may deteriorate with respect to the discontinuous jump or mesh size, and all the other eigenvalues are bounded below and above nearly uniformly with respect to the jump and mesh size. As a result, we prove that the convergence rate of the preconditioned conjugate gradient methods is nearly uniform with respect to the large jump and mesh size. Copyright © 2008 John Wiley & Sons, Ltd.

UNIFORM CONVERGENT MULTIGRID METHODS FOR ELLIPTIC PROBLEMS WITH STRONGLY DISCONTINUOUS COEFFICIENTS

This paper gives a solution to an open problem concerning the performance of various multilevel preconditioners for the linear finite element approximation of second-order elliptic boundary value problems with strongly discontinuous coefficients. By analyzing the eigenvalue distribution of the BPX preconditioner and multigrid V-cycle preconditioner, we prove that only a small number of eigenvalues may deteriorate with respect to the discontinuous jump or meshsize, and we prove that all the other eigenvalues are bounded below and above nearly uniformly with respect to the jump and meshsize. As a result, we prove that the convergence rate of the preconditioned conjugate gradient methods is uniform with respect to the large jump and meshsize. We also present some numerical experiments to demonstrate the theoretical results.

Domain decomposition for multiscale PDEs

We consider additive Schwarz domain decomposition preconditioners for piecewise linear finite element approximations of elliptic PDEs with highly variable coefficients. In contrast to standard analyses, we do not assume that the coefficients can be resolved by a coarse mesh. This situation arises often in practice, for example in the computation of flows in heterogeneous porous media, in both the deterministic and (Monte–Carlo simulated) stochastic cases. We consider preconditioners which combine local solves on general overlapping subdomains together with a global solve on a general coarse space of functions on a coarse grid. We perform a new analysis of the preconditioned matrix, which shows rather explicitly how its condition number depends on the variable coefficient in the PDE as well as on the coarse mesh and overlap parameters. The classical estimates for this preconditioner with linear coarsening guarantee good conditioning only when the coefficient varies mildly inside the coarse grid elements. By contrast, our new results show that, with a good choice of subdomains and coarse space basis functions, the preconditioner can still be robust even for large coefficient variation inside domains, when the classical method fails to be robust. In particular our estimates prove very precisely the previously made empirical observation that the use of low-energy coarse spaces can lead to robust preconditioners. We go on to consider coarse spaces constructed from multiscale finite elements and prove that preconditioners using this type of coarsening lead to robust preconditioners for a variety of binary (i.e., two-scale) media model problems. Moreover numerical experiments show that the new preconditioner has greatly improved performance over standard preconditioners even in the random coefficient case. We show also how the analysis extends in a straightforward way to multiplicative versions of the Schwarz method.

Monotone convergence of finite element approximations of obstacle problems

The purpose of the work is to study the monotone convergence of numerical solutions of obstacle problems under mesh refinement when the obstacle is convex. We prove monotone convergence of piecewise linear finite element approximations for one-dimensional obstacle problems. We demonstrate by giving a example that such monotone convergence will not hold in the two-dimensional case.

A posteriori error estimates for the Steklov eigenvalue problem

In this paper we introduce and analyze an a posteriori error estimator for the linear finite element approximations of the Steklov eigenvalue problem. We define an error estimator of the residual type which can be computed locally from the approximate eigenpair and we prove that, up to higher order terms, the estimator is equivalent to the energy norm of the error. Finally, we prove that the volumetric part of the residual term is dominated by a constant times the edge residuals, again up to higher order terms.

Convergence of free boundaries in discrete obstacle problems

We show that a piecewise linear finite element approximation of the obstacle problem gives an approximate free boundary converges, in an appropriate distance, to the free boundary of the continuous problem under a stability condition on the obstacle.

Residual-type a posteriori error estimate for parabolic obstacle problems

In this paper, a posteriori error estimates were derived for piecewise linear finite element approximations to parabolic obstacle problems. The instrumental ingredient was introduced as a new interpolation operator which has optimal approximation properties and preserves positivity. With the help of the interpolation operator the upper and lower bounds were obtained.

Supraconvergence and Supercloseness of a Scheme for Elliptic Equations on Nonuniform Grids

In this paper, we study the convergence of a finite difference scheme on nonuniform grids for the solution of second-order elliptic equations with mixed derivatives and variable coefficients in polygonal domains subjected to Dirichlet boundary conditions. We show that the scheme is equivalent to a fully discrete linear finite element approximation with quadrature. It exhibits the phenomenon of supraconvergence, more precisely, for s ∈ [1,2] order O(h s )-convergence of the finite difference solution, and its gradient is shown if the exact solution is in the Sobolev space H 1+s (Ω). In the case of an equation with mixed derivatives in a domain containing oblique boundary sections, the convergence order is reduced to O(h 3/2−ε) with ε > 0 if u ∈ H 3(Ω). The second-order accuracy of the finite difference gradient is in the finite element context nothing else than the supercloseness of the gradient. For s ∈ {1,2}, the given error estimates are strictly local.

Localized pointwise a posteriori error estimates for gradients of piecewise linear finite element approximations to second-order quasilinear elliptic problems

Two types of pointwise a posteriori error estimates are presented for gradients of finite element approximations of second-order quasilinear elliptic Dirichlet boundary value problems over convex polyhedral domains $\Omega$ in space dimension n \ge 2. We first give a residual estimator which is equivalent to \|\nabla(u-u_h)\|_{L_\infty(\Omega) up to higher-order terms. The second type of residual estimator is designed to control \nabla(u-u_h)locally over any subdomain of $\Omega$. It is a novel a posteriori counterpart to the localized or weighted a priori estimates of [Sch98]. This estimator is shown to be equivalent (up to higher-order terms) to the error measured in a weighted global norm which depends on the subdomain of interest. All estimates are proved for general shape-regular meshes which may be highly graded and unstructured. The constants in the estimates depend on the unknown solution u in the nonlinear case, but in a fashion which places minimal restrictions on the regularity of u.