From: wolf Date: Tue, 16 Apr 2002 08:34:13 +0000 (+0000) Subject: Almost finish everything. X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=43537213555301f56f34847e8842f988102cac3f;p=dealii-svn.git Almost finish everything. git-svn-id: https://svn.dealii.org/trunk@5655 0785d39b-7218-0410-832d-ea1e28bc413d --- diff --git a/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/intro.html b/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/intro.html index c59cfdf609..0aba96ec67 100644 --- a/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/intro.html +++ b/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/intro.html @@ -1,2 +1,177 @@

Introduction

+ +

Background and purpose

+ +

+In this example program, we will not so much be concerned with +describing new ways how to use deal.II and its facilities, but rather +with presenting methods of writing modular and extensible finite +element programs. The main reason for this is the size and complexity +of modern research software: applications implementing modern error +estimation concepts and adaptive solution methods tend to become +rather large. For example, the three largest applications by the main +authors of deal.II, are at the time of writing of this example +program: +

    +
  1. a program for solving conservation hyperbolic equations by the + Discontinuous Galerkin Finite Element method: 33,775 lines of + code; +
  2. a parameter estimation program: 28,980 lines of code; +
  3. a wave equation solver: 21,020 lines of code. +
+(The library proper - without example programs and +test suite - has slightly more than 150,000 lines of code.) In +the opinion of the author of this example program, the sizes of these +applications are at the edge of what one person, even an experienced +programmer, can manage. +

+ +

+The numbers above make one thing rather clear: monolithic programs that +are not broken up into smaller, mostly independent pieces have no way +of surviving, since even the author will quickly lose the overview of +the various dependencies between different parts of a program. Only +data encapsulation, for example using object oriented programming +methods, and modularization by defining small but fixed interfaces can +help structure data flow and mutual interdependencies. It is also an +absolute prerequisite if more than one person is developing a program, +since otherwise confusion will quickly prevail as one developer +would need to know if another changed something about the internals of +a different module if they were not cleanly separated. +

+ +

+In previous examples, you have seen how the library itself is broken +up into several complexes each building atop the underying ones, but +relatively independent of the other ones: +

    +
  1. the triangulation class complex, with associated iterator classes; +
  2. the finite element classes; +
  3. the DoFHandler class complex, with associated iterators, built on + the triangulation and finite element classes; +
  4. the classes implementing mappings between unit and real cells; +
  5. the FEValues class complex, built atop the finite elements and + mappings. +
+Besides these, and a large number of smaller classes, there are of +course the following ``tool'' modules: +
    +
  1. output in various graphical formats; +
  2. linear algebra classes. +
+

+ + +

+The goal of this program is now to give an example of how a relatively +simple finite element program could be structured such that we end up +with a set of modules that are as independent of each other as +possible. This allows to change the program at one end, without having to +worry that it might break at the other, as long as we do not touch the +interface through which the two ends communicate. The interface in +C++, of course, is the declaration of abstract base classes. +

+ +

+Here, we will implement (again) a Laplace solver, although with a +number of differences compared to previous example programs: +

    +
  1. The classes that implement the process of numerically solving the + equation are no more responsible for driving the process of + ``solving-estimating error-refining-solving again'', but we delegate + this to external functions. This allows first to use it as a + building block in a larger context, where the solution of a + Laplace equation might only be one part (for example, in a + nonlinear problem, where Laplace equations might have to be solved + in each nonlinear step). It would also allow to build a framework + around this class that would allow using solvers for other + equations (but with the same external interface) instead, in case + some techniques shall be evaluated for different types of partial + differential equations. +
  2. It splits the process of evaluating the computed solution to a + separate set of classes. The reason is that one is usually not + interested in the solution of a PDE per se, but rather in certain + aspects of it. For example, one might wish to compute the traction + at a certain boundary in elastic computations, or in the signal of + a seismic wave at a receiver position at a given + location. Sometimes, one might have an interest in several of + these aspects. Since the evaluation of a solution is something + that does not usually affect the process of solution, we split it + off into a separate module, to allow for the development of such + evaluation filters independently of the development of the solver + classes. +
  3. Separate the classes that implement mesh refinement from the + classes that compute the solution. +
  4. Separate the description of the test case with which we will + present the program, from the rest of the program. +
+

+ +

+The things the program does are not new. In fact, this is more like a +melange of previous programs, cannibalizing various parts and +functions from earlier examples. It is the way they are arranged in +this program that should be the focus of the reader. +

+ +

+Once you have worked through the program, you will remark that it is +already somewhat complex in its structure. Nevertheless, it +only has about 850 lines of code, without comments. In real +applications, there would of course be comments and class +documentation, which would bring that to maybe 1200 lines. Yet, compared to +the applications listed above, this is still small, as they are 20 to +25 times as large. For programs as large, a proper design right from +the start is thus indispensible. Otherwise, it will have to be +redesigned at one point in its life, once it becomes too large to be +manageable. +

+ +

+Despite of this, all three programs listed above have undergone major +revisions, or even rewrites. The wave program, for example, was once +entirely teared to parts when it was still significantly smaller, just +to assemble it again in a more modular form. By that time, it had +become impossible to add functionality without affecting older parts +of the code (the main problem with the code was the data flow: in time +dependent application, the major concern is when to store data to disk +and when to reload it again; if this is not done in an organized +fashion, then you end up with data released too early, loaded too +late, or not released at all). Although the present example program +thus draws from sevelar years of experience, it is certainly not +without flaws in its design, and in particular might not be suited for +an application where the objective is different. It should serve as an +inspiration for writing your own application in a modular way, to +avoid the pitfalls of too closely coupled codes. +

+ + +

What the program does

+ +

+What the program actually does is not even the main point of this +program, the structure of the program is more important. However, in a +few words, a description would be: solve the Laplace equation for a +given right hand side such that the solution is the function + u(x,t)=exp(x+sin(10y+5x2)) . The goal of the +computation is to get the value of the solution at the point +x0=(0.5,0.5), and to compare the accuracy with +which we resolve this value for two refinement criteria, namely global +refinement and refinement by the error indicator by Kelly et al. which +we have already used in previous examples. +

+ +

+The results will, as usual, be discussed in the respective section of +this document. In doing so, we will find a slightly irritating +observation about the relative performance of the two refinement +criteria. In a later example program, building atop this one, we will +devise a different method that should hopefully perform better than +the techniques discussed here. +

+ +

+So much now for all the theoretical and anecdotal background. The best +way of learning about a program is to look at it, so here it is: +

diff --git a/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/results.html b/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/results.html index 51041370d3..81ccd6d393 100644 --- a/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/results.html +++ b/deal.II/doc/tutorial/chapter-2.step-by-step/step-13.data/results.html @@ -2,38 +2,62 @@

Results

+

+The results of this program are not that interesting - after all +its purpose was not to demonstrate some new mathematical idea, and +also not how to program with deal.II, but rather to use the material +which we have developed in the previous examples to form something +which demonstrates a way to build modern finite element software in a +modular and extensible way. +

+ +

+Nevertheless, we of course show the results of the program. Of +foremost interest is the point value computation, for which we had +implemented the corresponding evaluation class. The results (i.e. the +output) of the program looks as follows: 

-Running tests with "global" refinement criterion:
--------------------------------------------------
-Refinement cycle: 0 1 2 3 4 5 6
-DoFs  u(x_0)
-   25 1.2868
-   81 1.6945
-  289 1.4658
- 1089 1.5679
- 4225 1.5882
-16641 1.5932
-66049 1.5945
-
-Running tests with "kelly" refinement criterion:
-------------------------------------------------
-Refinement cycle: 0 1 2 3 4 5 6 7 8 9 10 11
-DoFs  u(x_0)
-   25 1.2868
-   47 0.8775
-   89 1.5365
-  165 1.2974
-  316 1.6442
-  589 1.5221
- 1090 1.5724
- 2035 1.5622
- 3754 1.5916
- 7100 1.5876
-13059 1.5942
-24749 1.5933
+    Running tests with "global" refinement criterion:
+    -------------------------------------------------
+    Refinement cycle: 0 1 2 3 4 5 6
+    DoFs  u(x_0)
+       25 1.2868
+       81 1.6945
+      289 1.4658
+     1089 1.5679
+     4225 1.5882
+    16641 1.5932
+    66049 1.5945
+
+    Running tests with "kelly" refinement criterion:
+    ------------------------------------------------
+    Refinement cycle: 0 1 2 3 4 5 6 7 8 9 10 11
+    DoFs  u(x_0)
+       25 1.2868
+       47 0.8775
+       89 1.5365
+      165 1.2974
+      316 1.6442
+      589 1.5221
+     1090 1.5724
+     2035 1.5622
+     3754 1.5916
+     7100 1.5876
+    13059 1.5942
+    24749 1.5933
+

+ +

+What surprises here is that the the exact value is 1.59492, and that +it is therefore suprisingly complicated to compute the solution to +only one per cent accuracy, although the solution is smooth (in fact +infinite often differentiable). This smoothness is shown in the +graphical output generated by the program, here coarse grid and the +first 9 refinement steps of the Kelly refinement indicator: +

@@ -91,3 +115,94 @@ DoFs u(x_0)
+ +

+While we're already at watching pictures, this is the eighth grid, as +viewed from top: +

+ +

+ Kelly, grid 8 +

+ + + +

+However, we are not yet finished with evaluation the point value +computation. In fact, plotting the error +e=|u(xh)-uh(x0)| for the two +refinement criteria yields the following picture: +

+ +

+ error +

+ + +

+What is disturbing about this picture is that not only is the +adaptive mesh refinement not better than global refinement as one +would usually expect, it is even significantly worse since its +convergence is irregular, preventing all extrapolation techniques when +using the values of subsequent meshes! On the other hand, global +refinement provides a perfect 1/N or h-2 +convergence history and provides every opportunity to even improve on +the point values by extrapolation. Global mesh refinement must +therefore be considered superior in this example! This is even more +surprising as the evaluation point is not somewhere in the left part +where the mesh is coarse, but rather to the right and the adaptive +refinement should refine the mesh around the evaluation point as well. +

+ +

+We thus close the discussion of this example program with a question: +

+

+ What is wrong with adaptivity if it is not better than + global refinement? +

+ + +

+Exercise at the end of this example: There is a simple reason +for the bad and irregular behavior of the adapted mesh solutions. It +is simple to find out by looking at the mesh around the evaluation +point in each of the steps - the data for this is in the output files +of the program. An exercise would therefore be to modify the mesh +refinement routine such that the problem (once you remark it) is +avoided. The second exercise is to check whether the results are then +better than global refinement, and if so if even a better order of +convergence (in terms of the number of degrees of freedom) is +achieved, or only by a better constant. +

+ +

+(Very brief answers for the impatient: at steps with larger +errors, the mesh is not regular at the point of evaluation, i.e. some +of the adjacent cells have hanging nodes; this destroys some +superapproximation effects of which the globally refined mesh can +profit. Answer 2: this quick hack +

+    bool refinement_indicated = false;
+    typename Triangulation::active_cell_iterator cell;
+    for (cell=triangulation->begin_active();
+	 cell!=triangulation->end(); ++cell)
+      for (unsigned int v=0; v::vertices_per_cell; ++v)
+	if (cell->vertex(v) == Point(.5,.5))
+	  {
+	    cell->clear_coarsen_flag();
+	    refinement_indicated |= cell->refine_flag_set();
+	  };
+    if (refinement_indicated)
+      for (cell=triangulation->begin_active();
+	   cell!=triangulation->end(); ++cell)
+	for (unsigned int v=0; v::vertices_per_cell; ++v)
+	  if (cell->vertex(v) == Point(.5,.5))
+	    cell->set_refine_flag ();
+
+in the refinement function of the Kelly refinement class right before +executing refinement would improve the results (exercise: what does +the code do?), making them consistently better than global +refinement. Behavior is still irregular, though, so no results about +an order of convergence are possible.) +