Current Trends in Computational Methods for PDEs

The development of Computational methods for partial differential equations (PDEs) is a key tool for the development of science and technology. For its development, it is important to have a deep understanding of the classical and new methodologies used in numerical methods. The summer school will provide an overview of some techniques that allow one to address the computational challenges encountered in different applications. Some of these methodologies include: high order approximation, mixed finite elements, discontinuous Galerkin (DG) methods, domain decomposition and multilevel techniques, adaptivity, a-posteriori error analysis, approximation by sampling methods, sparse grids, ENO and WENO schemes and TVD-reconstructions.