Currently, I think we're solving for 7 variables... but we've seen
where we could have 9. It's currently something pretty close to what
John was solving a while ago: double diffusive convection in porous
media... except that we solve for a little more that just convection
for one of the terms.
They might not always be at the same order... even though they are
now. We might start solving it with incompressible flow equations...
and we'll need to have first order pressures. But yeah, currently
they're all the same order. But I'm not so worried about optimization
yet (probably not for another year).
Even my application is solving for 5 variables: Solid mechanics
displacement in 3D, heat condution and species diffusion. As we add
more species that number is going to continue to go up. My
application might have a region of compressible flow in it too... and
we'll be solving for all of that simultaneously.
We are truly doing multi-physics work around here... fully coupled and
fully implicit.
Derek
On Nov 5, 2008, at 6:01 PM, Kirk, Benjamin (JSC-EG) wrote:
BTW, without telling me so much that you have to kill me...
What are you solving with 9 variables? More importantly, are they
all the same FE type?
When I first started putting the DofMap together Taylor-Hood
elements were typical, with varying orders for dfferent variables.
But in *all* the applications since equal order for all variables
has worked fine.
The reason I ask is 'cus if you dig around in the DofMap,
especially the distribution part, there is a lot of code which could
be simplified if you knew a priori all variable types were
identical. This is especially the case when we build the graph of
the sparse matrix - it should instead be done for one prototypical
variable and the pattern for the rest of the matrix can be
inferred. That is an n_vars^2 savings on something that happens at
each adaptive step.
Similarly, constraints are calculated n_vars times too many...
I've been thinking about a derived specialization of the DofMap for
this special (but common) case.
-Ben
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