Hi Peter,
Yes, I am using isotropic refinement. For some geometries, using
anisotropic refinement, I may be able to keep the problem size smaller. I
am also experimenting with using p::d::triangulation, and there is a
limitation that anisotropic refinement does not work with
p::d::triangulation.
Ideally, I would like to use anisotropic refinement with hp::FECollection
on p::d::triangulation. My problems sizes are often > 3M DOFs and they are
transient heat transfer problems that take 10s hr to a few days on 32
CPUs.
Thanks for the help.
Kaushik

On Sun, Nov 7, 2021 at 8:34 AM Peter Munch <peterrmue...@gmail.com> wrote:

> Hi Kaushik,
>
> > Is there a plan for relaxing this limitation in the future? Is there
> any other way to do this?
>
> Unfortunately, there are currently no active developments regarding
> anisotropic refinement. Would it be an option to refine isotropically?
> Latter works very well parllel::distributed::Triangulation in parallel.
>
> PM
>
> On Sunday, 7 November 2021 at 13:48:04 UTC+1 k.d...@gmail.com wrote:
>
>> Forgot to attach the figure. Here it is.
>>
>> On Sunday, November 7, 2021 at 7:45:02 AM UTC-5 Kaushik Das wrote:
>>
>>> Hi all,
>>> I am trying to mesh a complex geometry by first creating a triangulation
>>> of the bounding box of the geometry and then successively refining the
>>> cells that are within the geometry.  I use a hp::FECollection to assign  
>>> FE_Nothing<DIM>()
>>> to cells that are outside the boundary and FE_Q<DIM>(1) to cells inside
>>> the geometry. Please see the attached figure, which shows only FE_Q cells.
>>> A limitation that I am facing is I cannot use an anisotropic refinement
>>> case because make_hanging_node_constraints does not support
>>> hp::FECollection.
>>> Is there a plan for relaxing this limitation in the future? Is there any
>>> other way to do this?
>>> I want to keep the axis-aligned nature of cells that are generated this
>>> way. It is an additive manufacturing application. Therefore, using an
>>> external tet mesh generator is not a good option for me.
>>> Thanks,
>>> Kaushik
>>>
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