The aim of this project is to develop, analyze, and implement the finite element method for fully nonlinear second order partial differential equations (PDEs). The research is based on a recent discovery of the PI that Lagrange finite element methods and discontinuous Galerkin methods can be used to approximate the Monge-Ampere equation, the prototypical fully nonlinear second order PDE. As these methods are simple to implement, the computation of the highly nonlinear problem can be performed efficiently and accurately. The project will expand on these results to obtain simple, efficient, yet accurate numerical schemes for a general class of fully nonlinear equations. In addition, the PI will develop and analyze various discretization methods including mixed finite element methods, local discontinuous Galerkin methods, hybridizable Galerkin methods, and Petrov Galerkin methods.

Mathematical modeling plays a key role in the investigation and understanding of many phenomena occurring in the natural sciences, the social sciences and engineering. Yet even for simple problems, closed form solutions are unavailable, and therefore their numerical approximations are the only viable option. As the problems become ever more complex, the need for novel computational methods and innovative analysis becomes imperative to put the United States in the forefront in science and engineering. The class of problems studied in this project arise in numerous mathematical modeling applications including weather phenomena, determining the initial shape of the universe, optimal reflector design, differential geometry, optimal transport, mathematical finance, image processing, and mesh generation. Despite their significance in the physical sciences and pure and applied mathematics, the numerical approximation of these problems remains a relatively untouched area. Therefore, there is a growing need to develop accurate schemes for these types of equations. As progress of solving any of these application problems largely depends on progress of solving their governing equations, and since numerical methods for these equations are still in their infancy, any progress in the design, implementation, and convergence analysis will have an immediate impact in advancing these application areas.

Agency
National Science Foundation (NSF)
Institute
Division of Mathematical Sciences (DMS)
Type
Standard Grant (Standard)
Application #
1115421
Program Officer
Junping Wang
Project Start
Project End
Budget Start
2011-08-01
Budget End
2012-08-31
Support Year
Fiscal Year
2011
Total Cost
$127,184
Indirect Cost
Name
Louisiana State University
Department
Type
DUNS #
City
Baton Rouge
State
LA
Country
United States
Zip Code
70803