As the release is out, we can now think about how to allow for Cython in our
The current build system is rather schizophrenic (numpy distutils and
makefiles), so ideas which way to go are welcome. The process should be simple :o)
I have just implemented a term allowing to impose the non-penetration
condition in the weak sense via Lagrange multipliers. The multipliers
variable lives one a surface and as such uses the new SurfaceField class.
There is a new example (and test) examples/biot/biot_npbc_lagrange.py,
which you can compare with the "old" way used in
examples/biot/biot_npbc.py - the results are pretty similar which is good.
your assumptions (6)-(8) are correct.
I would not mix the new shape derivative term you propose with the
existing linear elastic term, but you are right that term it is a good
The key point is how you want to parametrize your domain, i.e. how the
derivatives dB/da and dJ/da will look like.
vg->bfGM are just gradients of the base functions w.r.t. the space
coordinates for each element - it's an "array" with shape (n_el, n_qp,
dim, n_ep), where n_el is the number of elements (of a group), n_qp number
of quadrature points, dim the space dimension and n_ep the number of
Sorry for not very deep answers, I am now finishing some work so I am
swamped with other things...
Feel free to ask more.
On Fri, 10 Sep 2010, Peter M. Clausen wrote:
> I've searched and found some stuff, but also raised a lot of new
> questions regarding Shape optimization with SfePy. I wrote some
> formulas and questions which are easier to read in the attached
> PDF-file. I've also pasted the tex-file here so people can search the
> text /mailing list.