Hi Dan,
Thanks for your reply, and for the tip to use Grid1D with variable dx. I was
able to deploy it right away.
There is a new complexity in this connection.
My problem models the solid diffusion in a spherical particle. Matter
diffuses from the centre of the particle and reacts
Dear Dr. Jonathan Guyer,
Thank you very much for your help. For the benefit of the community wishing to
use 1D meshes in gmsh format for any of their external applications, I am
bringing into your attention a nifty script available from the 'fluidity' CFD
project.
For my 1D case, I have be
Gmsh does do 1D meshes, and I've got experimental code that imports them, but
it's not ready to merge, yet.
In the meantime, this approach I've used for modeling semiconductor device
contacts in 1D is probably better:
n_thickness = 1e-6 # m
p_thickness = 149e-6 # m
grid_resolution = 5e-8
Thanks --
Once I have pounded on this a bit more, I will write the function. It
should be straightforward. I concentrated on making it simple and easy to
understand; since it is run only to make the grid, efficiency was not a
great issue for me.
Jamie
On Fri, Jun 17, 2016 at 10:03 AM, Daniel
James, this is awesome, thanks for posting. It would be a very good
idea to have a DelaunayMesh in FiPy that used Scipy for the
triangulation as it would give another way to make and test
unstructured meshes without the Gmsh dependency. Something like,
mesh = DelaunayMesh(points_in_2D)
In the
On Thu, Jun 16, 2016 at 12:35 PM, Gopalakrishnan, Krishnakumar
wrote:
> Thanks.
>
> Yes, this Is indeed only first order accurate. I verified this by
> successively cutting my dx by half, running your code, and comparing against
> the Mathematica generated result. Each time dx is cut by half, t
