I am looking at the pde of the type $u_t=\mathcal{L}u$ for some elliptic operator $\mathcal{L}$ and on some domain $D$. Assume I am solving that with a finite difference method and want to estimate the error. Thus, I create a mesh over $D$ and compute the error in discrete $L^2$ norm, that is at every point on the grid I take the difference between the function itself and an approximate solution, square it and sum up. This sum includes all the points, including the boundary points. By Lax theorem the rate of convergence is the rate of local truncation error PROVIDED the problem is well posed and the derivatives in local truncation error are bounded. However, assume it can be shown that the weak solution exist and unique and is sufficiently smooth inside of the domain but on the boundaries it is only satisfied in a weak sense, and lacks regularity. So there is no hope that the terms in local truncation error are bounded on the boundary, they are not even defined there. Thus, how do all these points on the boundary contribute to the error? They exist even if we refine a mesh, more than that we add points with it. Please let me know should I take into account irregularity on the boundary.
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Elliptic problems have weak singularities at reentrant corners, therefore you must interpret solutions weakly, making strong form discretizations like finite differences less natural than weak form discretizations (like finite element methods) to analyze and compute with. The canonical analysis text is
Solution of elliptic systems in domains with reentrant corners is the canonical problem in adaptive finite element methods, thus the topic of thousands of papers. A good place to get started on the background theory is
There are numerous open source software packages that use adaptive refinement guided by a posteriori error estimators to solve elliptic problems in domains with reentrant corners. |
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This is one of the many reasons why the analysis of finite element methods is so much simpler than that of finite difference methods... |
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