On Mon, Mar 25, 2013 at 3:43 PM, Benny Malengier <[email protected]>wrote:
> You should read up on domain decomposition methods ( > http://en.wikipedia.org/wiki/Domain_decomposition_methods ). > Specifically: http://en.wikipedia.org/wiki/Schwarz_alternating_method > > So creating two models, each with their own mesh, and an overlap domain, > and apply upscaling/downscaling between the solution is the simplest start. > As FiPy is FVM, basing your scaling on a conserved quantity is the way to > go in my opinion. > I am familiar with domain decomposition methods. This seems a quite abstract way to tackle the problem. I don't want to artificially introduce iteration into a linear diffusion problem. It is really just a mesh-generation issue. I was thinking I could use a 2D mesh and a tensor with very low permeability in one direction, which would essentially enforce 1D flow in the branch region and then make the tensor low permeability in the other direction on the branches, to enforce 1D flow in the other direction along the trunk. Based on other threads, it appears FiPy can't have spatially dependent properties AND use tensors. Kris
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