Title
A Finite Element/Operator-Splitting Method for the Numerical Solution of the Two Dimensional Elliptic Monge-Ampère Equation.
Abstract
We discuss in this article a novel method for the numerical solution of the two-dimensional elliptic Monge–Ampère equation. Our methodology relies on the combination of a time-discretization by operator-splitting with a mixed finite element based space approximation where one employs the same finite-dimensional spaces to approximate the unknown function and its three second order derivatives. A key ingredient of our approach is the reformulation of the Monge–Ampère equation as a nonlinear elliptic equation in divergence form, involving the cofactor matrix of the Hessian of the unknown function. With the above elliptic equation we associate an initial value problem that we discretize by operator-splitting. To enforce the pointwise positivity of the approximate Hessian we employ a hard thresholding based projection method. As shown by our numerical experiments, the resulting methodology is robust and can handle a large variety of triangulations ranging from uniform on rectangles to unstructured on domains with curved boundaries. For those cases where the solution is smooth and isotropic enough, we suggest also a two-stage method to improve the computational efficiency, the second stage being reminiscent of a Newton-like method. The methodology discussed in this article is able to handle domains with curved boundaries and unstructured meshes, using piecewise affine continuous approximations, while preserving optimal, or nearly optimal, convergence orders for the approximation error.
Year
DOI
Venue
2019
10.1007/s10915-018-0839-y
J. Sci. Comput.
Keywords
DocType
Volume
Fully nonlinear elliptic partial differential equations, Monge–Ampère equations, Operator-splitting method, Finite element approximations, Mixed finite element methods, Tychonoff regularization, Variational crimes
Journal
79
Issue
ISSN
Citations 
1
1573-7691
0
PageRank 
References 
Authors
0.34
14
4
Name
Order
Citations
PageRank
Roland Glowinski118850.44
Hao Liu215320.47
Shingyu Leung316418.35
Jianliang Qian431534.71