Veranstaltungen 

Veranstaltungen der Fakultät für Mathematik

The adaptive discontinuous Galerkin methods on polygonal and polyhedral meshes, als osnao

Termin

21.11.2019, 14:15 Uhr - ca. 15:30 Uhr

Veranstaltungsort
M 511
Abstract
PDE models are often characterised by local features such as solution singularities/layers and domains with complicated boundaries. These special features make the design of accurate numerical solutions challenging, or require huge amount of computational resources. One way of achieving complexity reduction of the numerical solution for such PDE models is to design novel numerical methods which support general meshes consisting of polygonal/polyhedral elements, such that local features of the model can be resolved in efficiently by adaptive choices of such general meshes. In this talk, we first will review the recently developed hp-version symmetric interior penalty discontinuous Galerkin (dG) finite element method for the numerical approximation of PDEs on general computational meshes consisting of polygonal/polyhedral (polytopic) and even curved elements. The key feature of the proposed dG method is that the stability and hp-version a-priori error bound are derived based on the specific choice of the interior penalty parameters which allows for edges/faces degeneration. Moreover, under certain practical mesh assumptions, the proposed dG method was proven to be available to incorporate essentially arbitrarily-shaped elements with an arbitrary number of faces or even curved faces. Because of utilising general shaped elements, the dG method shows a great flexibility in designing an adaptive algorithm by refining or coarsening general polytopic elements. Next, we will present recent results on a new a posteriori error analysis for the dG method on general-shaped elements. The new a posteriori error analysis generalizes the know results for hp-dG methods to admit arbitrary number of irregular hanging nodes per element. Finally, a series of numerical experiments is also presented, highlighting the good performance of the proposed dG method.
Vortragende(r)
Prof. Zhaonan Dong
Herkunft der/des Vortragenden
University of Leicester