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We consider scalar semilinear elliptic PDEs, where the nonlinearity is strongly monotone, but only locally Lipschitz continuous. To linearize the arising discrete nonlinear problem, we employ a damped Zarantonello iteration, which leads to…

Numerical Analysis · Mathematics 2025-03-13 Maximilian Brunner , Dirk Praetorius , Julian Streitberger

We consider a general nonsymmetric second-order linear elliptic PDE in the framework of the Lax-Milgram lemma. We formulate and analyze an adaptive finite element algorithm with arbitrary polynomial degree that steers the adaptive…

Numerical Analysis · Mathematics 2023-11-28 Maximilian Brunner , Pascal Heid , Michael Innerberger , Ani Miraçi , Dirk Praetorius , Julian Streitberger

We consider adaptive finite element methods for second-order elliptic PDEs, where the arising discrete systems are not solved exactly. For contractive iterative solvers, we formulate an adaptive algorithm which monitors and steers the…

Numerical Analysis · Mathematics 2021-07-14 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Stefan Schimanko

We propose an adaptive iteratively linearized finite element method (AILFEM) in the context of strongly monotone nonlinear operators in Hilbert spaces. The approach combines adaptive mesh-refinement with an energy-contractive linearization…

Numerical Analysis · Mathematics 2025-03-18 Ani Miraçi , Dirk Praetorius , Julian Streitberger

This chapter provides an overview of state-of-the-art adaptive finite element methods (AFEMs) for the numerical solution of second-order elliptic partial differential equations (PDEs), where the primary focus is on the optimal interplay of…

Numerical Analysis · Mathematics 2024-04-11 Philipp Bringmann , Ani Miraçi , Dirk Praetorius

We analyze a goal-oriented adaptive algorithm that aims to efficiently compute the quantity of interest $G(u^\star)$ with a linear goal functional $G$ and the solution $u^\star$ to a general second-order nonsymmetric linear elliptic partial…

Numerical Analysis · Mathematics 2024-11-18 Philipp Bringmann , Maximilian Brunner , Dirk Praetorius , Julian Streitberger

This paper concerns the inclusion of Newton's method into an adaptive finite element method (FEM) for the solution of nonlinear partial differential equations (PDEs). It features an adaptive choice of the damping parameter in the Newton…

Numerical Analysis · Mathematics 2025-12-23 Philipp Bringmann , Maximilian Brunner , Dirk Praetorius

We revisit a unified methodology for the iterative solution of nonlinear equations in Hilbert spaces. Our key observation is that the general approach from [Heid & Wihler, Math. Comp. 89 (2020), Calcolo 57 (2020)] satisfies an energy…

Numerical Analysis · Mathematics 2021-02-18 Pascal Heid , Dirk Praetorius , Thomas P. Wihler

We prove convergence with optimal algebraic rates for an adaptive finite element method for nonlinear equations with strongly monotone operator. Unlike prior works, our analysis also includes the iterative and inexact solution of the…

Numerical Analysis · Mathematics 2018-11-27 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Bernhard Stiftner

We analyze optimal complexity of adaptive finite element methods (AFEMs) for general second-order linear elliptic partial differential equations (PDEs) in the Lax-Milgram setting. To this end, we formulate an adaptive algorithm which steers…

Numerical Analysis · Mathematics 2026-04-21 Thomas Führer , Paula Hilbert , Ani Miraçi , Dirk Praetorius

In this article we study adaptive finite element methods (AFEM) with inexact solvers for a class of semilinear elliptic interface problems. We are particularly interested in nonlinear problems with discontinuous diffusion coefficients, such…

Numerical Analysis · Mathematics 2016-08-24 Michael Holst , Ryan Szypowski , Yunrong Zhu

This work proposes an $r$-adaptive finite element method (FEM) using neural networks (NNs). The method employs the Ritz energy functional as the loss function, currently limiting its applicability to symmetric and coercive problems, such as…

We consider an adaptive algorithm for finite element methods for the isogeometric analysis (IGAFEM) of elliptic (possibly non-symmetric) second-order partial differential equations in arbitrary space dimension $d\ge2$. We employ…

Numerical Analysis · Mathematics 2017-11-20 Gregor Gantner , Daniel Haberlik , Dirk Praetorius

We prove the quasi-optimal convergence of a standard adaptive finite element method (AFEM) for nonlinear elliptic second-order equations of monotone type. The adaptive algorithm is based on residual-type a posteriori error estimators and…

Numerical Analysis · Mathematics 2010-10-07 Eduardo M. Garau , Pedro Morin , Carlos Zuppa

We propose a new algorithm for Adaptive Finite Element Methods (AFEMs) based on smoothing iterations (S-AFEM), for linear, second-order, elliptic partial differential equations (PDEs). The algorithm is inspired by the ascending phase of the…

Numerical Analysis · Mathematics 2020-12-18 Ornela Mulita , Stefano Giani , Luca Heltai

We analyze adaptive mesh-refining algorithms for conforming finite element discretizations of certain non-linear second-order partial differential equations. We allow continuous polynomials of arbitrary, but fixed polynomial order. The…

Numerical Analysis · Mathematics 2014-03-14 Michael Feischl , Thomas Führer , Dirk Praetorius

We present the first rigorous convergence analysis of the smoothed adaptive finite element method (S-AFEM) proposed in [Mulita, Giani, Heltai: SIAM J. Sci. Comput. 43, 2021]. S-AFEM modifies the classical adaptive finite element method…

Numerical Analysis · Mathematics 2026-01-29 Philipp Bringmann , Christoph Lietz , Dirk Praetorius

We study an iterative Galerkin method for quasilinear elliptic problems in the Browder-Minty setting. The resulting discrete nonlinear systems are solved by linearization via a (damped) Zarantonello iteration. Unlike prior work, adaptive…

Numerical Analysis · Mathematics 2026-05-25 Maximilian Brunner , Gregor Gantner , Christoph Lietz , Dirk Praetorius

The Zarantonello fixed-point iteration is an established linearization scheme for quasilinear PDEs with strongly monotone and Lipschitz continuous nonlinearity in Hilbert spaces. This paper presents a weighted least-squares minimization for…

Numerical Analysis · Mathematics 2026-02-24 Philipp Bringmann , Dirk Praetorius

The ultimate goal of any numerical scheme for partial differential equations (PDEs) is to compute an approximation of user-prescribed accuracy at quasi-minimal computational time. To this end, algorithmically, the standard adaptive finite…

Numerical Analysis · Mathematics 2025-01-30 Philipp Bringmann , Michael Feischl , Ani Miraci , Dirk Praetorius , Julian Streitberger
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