Analysis of the Vanishing Moment Method and its Finite Element Approximations for Second-order Linear Elliptic PDEs in Non-divergence Form
Xiaobing Feng, Thomas Lewis, and Stefan Schnake

TL;DR
This paper investigates the Vanishing Moment Method for second-order elliptic PDEs in non-divergence form, proposing a finite element approach with error analysis and numerical validation.
Contribution
It introduces a novel finite element method for the Vanishing Moment approximation of non-divergence form PDEs, with proven error estimates and numerical results.
Findings
The method achieves optimal error estimates in the H^2 norm.
Numerical tests confirm the effectiveness of the proposed finite element approach.
The Vanishing Moment Method provides a stable and accurate approximation for second-order elliptic PDEs.
Abstract
This paper is concerned with continuous and discrete approximations of strong solutions of second-order linear elliptic partial differential equations (PDEs) in non-divergence form. The continuous approximation of these equations is achieved through the Vanishing Moment Method (VMM) which adds a small biharmonic term to the PDE. The structure of the new fourth-order PDE is a natural fit for Galerkin-type methods unlike the original second order equation since the highest order term is in divergence form. The well-posedness of the weak form of the perturbed fourth order equation is shown as well as error estimates for approximating the strong solution of the original second-order PDE. A finite element method is then proposed for the fourth order equation, and its existence and uniqueness of solutions as well as optimal error estimates in the norm are shown. Lastly,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDifferential Equations and Numerical Methods · Advanced Numerical Methods in Computational Mathematics · Advanced Mathematical Modeling in Engineering
