$h-p$ spectral element methods for three dimensional elliptic problems on non-smooth domains using parallel computers

Details $h-p$ spectral element methods for three dimensional elliptic problems on non-smooth domains using parallel computers $h-p$ spectral element methods for three dimensional elliptic problems on non-smooth domains using parallel computers

2011-10-11

arxiv.org/abs/1110.2316v1

Mathematics

Numerical Analysis

278 pages, 62 figures, 16 tables

Scientific paper

Elliptic partial differential equations arise in many fields of science and engineering such as steady state distribution of heat, fluid dynamics, structural/mechanical engineering, aerospace engineering and seismology etc. In three dimensions it is well known that the solutions of elliptic boundary value problems have singular behavior near the corners and edges of the domain. The singularities which arise are known as vertex, edge, and vertex-edge singularities. We propose a nonconforming h-p spectral element method to solve three dimensional elliptic boundary value problems on non-smooth domains to exponential accuracy. To overcome the singularities which arise in the neighbourhoods of the vertices, vertex-edges and edges we use local systems of coordinates. These local coordinates are modified versions of spherical and cylindrical coordinate systems in their respective neighbourhoods. Away from these neighbourhoods standard Cartesian coordinates are used. In each of these neighbourhoods we use a geometrical mesh which becomes finer near the corners and edges. We then derive differentiability estimates in these new set of variables and a stability estimate on which our method is based for a non-conforming h-p spectral element method. The Sobolev spaces in vertex-edge and edge neighbourhoods are anisotropic and become singular at the corners and edges. The method is essentially a least-squares collocation} method and a solution can be obtained using Preconditioned Conjugate Gradient Method (PCGM). To solve the minimization problem we need to solve the normal equations for the least-squares problem. The residuals in the normal equations can be obtained without computing and storing mass and stiffness matrices. Computational results for a number of model problems confirm the theoretical estimates obtained for the error and computational complexity.

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