From 30660ca65aa271373440cce7b06125d04e548258 Mon Sep 17 00:00:00 2001 From: David Wells Date: Sat, 28 Apr 2018 17:30:09 -0400 Subject: [PATCH] Remove trailing spaces in step-6. --- examples/step-6/doc/results.dox | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/examples/step-6/doc/results.dox b/examples/step-6/doc/results.dox index 7c75a7540c..b9cff892b3 100644 --- a/examples/step-6/doc/results.dox +++ b/examples/step-6/doc/results.dox @@ -230,7 +230,7 @@ O}(N^{1/2})$ and because each iteration requires around ${\cal O}(N)$ operations the total CPU time grows like ${\cal O}(N^{3/2})$ (for the few smallest meshes, the CPU time is so small that it doesn't record). Note that even though it is the simplest -method, Jacobi is the fastest for this problem. +method, Jacobi is the fastest for this problem. The situation changes slightly when the finite element is not a bi-quadratic one as set in the constructor of this program, but a @@ -255,7 +255,7 @@ operations it has to perform. This is not to say that Jacobi is actually a good preconditioner -- for problems of appreciable size, it is definitely not, and other methods will be substantially better -- but really only that it is fast because its implementation is so simple that it can -compensate for a larger number of iterations. +compensate for a larger number of iterations. The message to take away from this is not that simplicity in preconditioners is always best. While this may be true for the current @@ -272,7 +272,7 @@ of preconditioners that can achieve this, namely geometric (step-16, step-37, step-39) or algebraic multigrid (step-31, step-40, and several others) preconditioners. They are, however, significantly more complex than -the preconditioners outlined above. +the preconditioners outlined above. Finally, the last message to take home is that when the data shown above was generated (in 2008), linear @@ -287,8 +287,8 @@ solving problems in 3d to high accuracy remains a challenge.

A better mesh

-If you look at the meshes above, you will see even though the domain is the -unit disk, and the jump in the coefficient lies along a circle, the cells +If you look at the meshes above, you will see even though the domain is the +unit disk, and the jump in the coefficient lies along a circle, the cells that make up the mesh do not track this geometry well. The reason, already hinted at in step-1, is that by default the Triangulation class only sees a bunch of coarse grid cells but has, of course, no real idea what kind of geometry they @@ -516,7 +516,7 @@ on how smooth exactly the boundary of the domain is, and how smooth the right hand side is. Some regularity of the solution may be lost at the boundary, but one generally has that the solution is twice more differentiable in compact subsets of the domain than the right hand side. -If, in particular, the right hand side satisfies $f\in C^\infty(\Omega)$, then +If, in particular, the right hand side satisfies $f\in C^\infty(\Omega)$, then $u \in C^\infty(\Omega_i)$ where $\Omega_i$ is any compact subset of $\Omega$ ($\Omega$ is an open domain, so a compact subset needs to keep a positive distance from $\partial\Omega$). @@ -526,12 +526,12 @@ at an equation with a non-constant coefficient $a(\mathbf x)$: @f[ -\nabla \cdot (a \nabla u) = f. @f] -Here, if $a$ is not smooth, then the solution will not be smooth either, +Here, if $a$ is not smooth, then the solution will not be smooth either, regardless of $f$. In particular, we expect that wherever $a$ is discontinuous along a line (or along a plane in 3d), the solution will have a kink. This is easy to see: if for example $f$ -is continuous, then $f=-\nabla \cdot (a \nabla u)$ needs to be -continuous. This means that $a \nabla u$ must be continuously differentiable +is continuous, then $f=-\nabla \cdot (a \nabla u)$ needs to be +continuous. This means that $a \nabla u$ must be continuously differentiable (not have a kink). Consequently, if $a$ has a discontinuity, then $\nabla u$ must have an opposite discontinuity so that the two exactly cancel and their product yields a function without a discontinuity. But for $\nabla u$ to have @@ -550,7 +550,7 @@ $W^{1,\infty}$. It is not very difficult to create cases where the solution is in a space $H^{1+s}$ where we can get $s$ to become as small as we want. Such cases are often used to test adaptive finite element methods because the mesh will have to resolve the singularity that causes -the solution to not be in $W^{1,\infty}$ any more. +the solution to not be in $W^{1,\infty}$ any more. The typical example one uses for this is called the Kellogg problem (referring to the paper "On the Poisson equation with intersecting interfaces" -- 2.39.5