Fix comment.

git-svn-id: https://svn.dealii.org/trunk@16167 0785d39b-7218-0410-832d-ea1e28bc413d

diff --git a/deal.II/examples/step-33/step-33.cc b/deal.II/examples/step-33/step-33.cc
index 1cfb7b7dd25752046d07bcd58fb58882de6162b8..3fcaa6f51efd5cfa5a04c040a45de71f9db4ec30 100644 (file)
--- a/deal.II/examples/step-33/step-33.cc
+++ b/deal.II/examples/step-33/step-33.cc
@@ -3124,23 +3124,33 @@ void ConservationLaw<dim>::run ()
                                       // do various post convergence tasks
                                       // here:
                                       //
-                                      // First, we update the time and
-                                      // produce graphical output if so
-                                      // desired. Then we update a predictor
-                                      // for the solution at the next time
-                                      // step by approximating $\mathbf
-                                      // w^{n+1}\approx \frac 32 \mathbf w^n
-                                      // -\frac 12 \mathbf w^{n-1}$ to try
-                                      // and make adaptivity work better.
-                                      // The idea is to try and refine ahead
-                                      // of a front, rather than stepping
-                                      // into a coarse set of elements and
-                                      // smearing the old_solution.  This
-                                      // simple time extrapolator does the
-                                      // job. With this, we then refine the
-                                      // mesh if so desired by the user, and
-                                      // finally continue on with the next
-                                      // time step:
+                                      // First, we update the time
+                                      // and produce graphical output
+                                      // if so desired. Then we
+                                      // update a predictor for the
+                                      // solution at the next time
+                                      // step by approximating
+                                      // $\mathbf w^{n+1}\approx
+                                      // \mathbf w^n + \delta t
+                                      // \frac{\partial \mathbf
+                                      // w}{\partial t} \approx
+                                      // \mathbf w^n + \delta t \;
+                                      // \frac{\mathbf w^n-\mathbf
+                                      // w^{n-1}}{\delta t} = 2
+                                      // \mathbf w^n - \mathbf
+                                      // w^{n-1}$ to try and make
+                                      // adaptivity work better.  The
+                                      // idea is to try and refine
+                                      // ahead of a front, rather
+                                      // than stepping into a coarse
+                                      // set of elements and smearing
+                                      // the old_solution.  This
+                                      // simple time extrapolator
+                                      // does the job. With this, we
+                                      // then refine the mesh if so
+                                      // desired by the user, and
+                                      // finally continue on with the
+                                      // next time step:
       time += parameters.time_step;
 
       if (parameters.output_step < 0)