Convergence and Quasi-Optimality of an Adaptive Multi-Penalty Discontinuous Galerkin Method

An adaptive multi-penalty discontinuous Galerkin method(AMPDG)for the diffusion problem is considered.Convergence and quasi-optimality of the AM-PDG are proved.Compared with the analyses for the adaptive finite element method or the adaptive interior penalty discontinuous Galerkin method,extra works are done to overcome the difficulties caused by the additional penalty terms.

NEW SYSTEMS OF GENERALIZED QUASI-VARIATIONAL INCLUSIONS IN FC-SPACES AND APPLICATIONS

In this paper, we study some new systems of generalized quasi-variational inclusion problems in FC-spaces without convexity structure.By applying an existence theorem of maximal elements of set-valued mappings due to the author, some new existence theorems of solutions for the systems of generalized quasi-variational inclusion problems are proved in noncompact FC-spaces. As applications, some existence results of solutions for the system of quasi-optimization problems and mathematical programs with the systems of generalized quasi-variational inclusion constraints are obtained in FC-spaces.

ERROR REDUCTION, CONVERGENCE AND OPTIMALITY FOR ADAPTIVE MIXED FINITE ELEMENT METHODS FOR DIFFUSION EQUATIONS

Error reduction, convergence and optimality are analyzed for adaptive mixed finite element methods （AMFEM） for diffusion equations without marking the oscillation of data. Firstly, the quasi-error, i.e. the sum of the stress variable error and the scaled error estimator, is shown to reduce with a fixed factor between two successive adaptive loops, up to an oscillation. Secondly, the convergence of AMFEM is obtained with respect to the quasi-error plus the divergence of the flux error. Finally, the quasi-optimal convergence rate is established for the total error, i.e. the stress variable error plus the data oscillation.

Adaptive Finite Element Modeling Techniques for the Poisson-Boltzmann Equation

We consider the design of an effective and reliable adaptive finite element method(AFEM)for the nonlinear Poisson-Boltzmann equation(PBE).We first examine the two-term regularization technique for the continuous problem recently proposed by Chen,Holst and Xu based on the removal of the singular electrostatic potential inside biomolecules;this technique made possible the development of the first complete solution and approximation theory for the Poisson-Boltzmann equation,the first provably convergent discretization and also allowed for the development of a provably convergent AFEM.However,in practical implementation,this two-term regularization exhibits numerical instability.Therefore,we examine a variation of this regularization technique which can be shown to be less susceptible to such instability.We establish a priori estimates and other basic results for the continuous regularized problem,as well as for Galerkin finite element approximations.We show that the new approach produces regularized continuous and discrete problemswith the samemathematical advantages of the original regularization.We then design an AFEM scheme for the new regularized problem and show that the resulting AFEM scheme is accurate and reliable,by proving a contraction result for the error.This result,which is one of the first results of this type for nonlinear elliptic problems,is based on using continuous and discrete a priori L¥estimates.To provide a high-quality geometric model as input to the AFEM algorithm,we also describe a class of feature-preserving adaptive mesh generation algorithms designed specifically for constructing meshes of biomolecular structures,based on the intrinsic local structure tensor of the molecular surface.All of the algorithms described in the article are implemented in the Finite Element Toolkit(FETK),developed and maintained at UCSD.The stability advantages of the new regularization scheme are demonstrated with FETK through comparisons with the original regularization approach for a model problem.The convergence and accuracy of the overall AFEMalgorithmis also illustrated by numerical approximation of electrostatic solvation energy for an insulin protein.

CONVERGENCE AND OPTIMALITY OF ADAPTIVE MIXED METHODS FOR POISSON’S EQUATION IN THE FEEC FRAMEWORK

Finite Element Exterior Calculus (FEEC) was developed by Arnold, Falk, Winther andothers over the last decade to exploit the observation that mixed variational problems canbe posed on a Hilbert complex, and Galerkin-type mixed methods can then be obtained bysolving finite-dimensional subcomplex problems. Chen, Holst, and Xu (Math. Comp. 78(2009) 35–53) established convergence and optimality of an adaptive mixed finite elementmethod using Raviart–Thomas or Brezzi–Douglas–Marini elements for Poisson’s equationon contractible domains in R^2, which can be viewed as a boundary problem on the deRham complex. Recently Demlow and Hirani (Found. Math. Comput. 14 (2014) 1337–1371) developed fundamental tools for a posteriori analysis on the de Rham complex.In this paper, we use tools in FEEC to construct convergence and complexity resultson domains with general topology and spatial dimension. In particular, we construct areliable and efficient error estimator and a sharper quasi-orthogonality result using a noveltechnique. Without marking for data oscillation, our adaptive method is a contractionwith respect to a total error incorporating the error estimator and data oscillation.