On Tue, 26 Jan 2010 13:23:19 -0600, "Vijay S. Mahadevan" <[email protected]> 
wrote:
> I know that Implicit Midpoint (IM2) is not L-stable either but it is
> my understanding that it has a lower truncation error because the
> coefficient in front of the error is smaller compared to that of CN.
> So I usually prefer IM2 to CN.

Hmm, it's easier to handle boundary conditions in IM2, but I thought the
truncation error was the same.

> I'm curious about the TSGL methods and will try out those integrators
> soon. It might be a stretch to do that in the current problem
> implementation but I have other coupled problems that could use
> adaptive, higher order temporal integration. If there are references
> explaining the properties of these methods, their butcher tableau and
> such, please do let me know. Also, are these implemented only in
> petsc-dev currently since I do not see it in the latest release of
> petsc.

These are only in petsc-dev, I added them in the fall.

  
http://www.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-dev/docs/manualpages/TS/TSGL.html

the primary reference is

  John Butcher and Z. Jackieweicz and W. Wright, On error propagation in 
general linear methods for ordinary differential equations, Journal of 
Complexity, Vol 23 (4-6), 2007

tables for many of the methods are here

  http://www.math.auckland.ac.nz/~hpod/atlas/

IIRC, somehow those tables have errors in error estimators, in TSGL they
are computed automatically according to the algorithms in the 2007 paper.

The implementation only uses the implicit form, and is also suitable for
DAEs (probably only index 1).  This implicit form is also better for
finite element methods because assembling the mass matrix separately is
a bad idea, see TSSetIFunction and TSSetIJacobian.

  
http://www.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-dev/docs/manualpages/TS/TSSetIFunction.html
  
http://www.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-dev/docs/manualpages/TS/TSSetIJacobian.html

Let me know if you have questions.  Suggestions about controllers would
also be appreciated, my controllers just try to maximise the effective
step size over the available schemes subject to a local truncation error
tolerance, with a very naive smoothing procedure to (hopefully) keep it
from bouncing between schemes too often.  But there is a plugin
architecture so hopefully we'll accumulate a library of controllers.
Starting procedures are also a bit naive, just starting with a small
implicit Euler step and moving to higher order schemes as smoothness of
the solution indicates.  The usual alternative is to start with a singly
implicit Runge-Kutta scheme, but they suffer from reduced stage order
and I haven't gotten around to writing one.

Jed

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