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From my memory of the code there should be no need to hard code 3 iterations? I would generalize it.
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Sergey - after looking at it a bit more I think we are going to need some help with this last piece.Just to give an idea of what's left to do for the porting to be completed, the createModel method generates this file at the moment (representing a scene with random particle of the same default type as in the old version of the SPH demo), so we need to update createModel to generate the same scene you are generating (worm elastic body splashing into a liquid, I am guessing).Any help you can give us with this would greatly accelerate completion of this task - because at the moment the only ways I have to replicate the scene are trying to understand how the scene is generated from the old code (quite hard) or parse the configurations files in the new refactored code (easier but time consuming). Maybe you can share the code you used to generate those files (position.txt, velocity.txt, elasticConnections.txt)? That would probably help a lot.Thanks!- Giovanni
On Friday, February 8, 2013 2:52:58 PM UTC, giovanni.idili wrote:
Hey Andrey, Sergey,after our last meeting, as discussed, I spent time trying to get a liquid only simulation (including boundary particles) on the ported version of PCI-SPH (while waiting for scripts/code to generate the scene including elastic connections). After some issues to get the kernels to compile on mac-os, I had some success getting something to run (see screenshot with some boundaries and only 2 particles) but there is still something wrong (crashes unexpectedly after a few steps if I add liquid particles or more boundaries) and I suspect it has to do with the initial conditions and/or parameters.I am creating the boundary particles and a layer of water on the bottom same as Andrey does in this code (IntegratedVersion branch), this is the file that I generate and this is the code I am using to do it (ported from C++ to Java).My 1st question: is there an assumed relationship between MIN/MAX X/Y/Z (defining the grid dimensions) and the number of particles that needs to be respected ( and could cause the simulation to do weird stuff if not respected)?We picked:X: 0-100Y: 0-40Z: 0-40PARTICLE_COUNT: 1024*42 / 4 = 10752.But I noticed that Andrey has the following in the Integrated branch (sph.h):X: 0-120.24Y: 0-80.16Z: 0-180.36
PARTICLE_COUNT: 1024*42 / 4 = 43008
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The exact same thing happened to me when I messed with the timesteps in the c++ implementation.
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That sounds plausible. The current implementation only returns every 3rd timestep to the gui afaik, the other two modify state.
Mmm now that you say that Mike, I think I might have an idea of what's going on - our implementation is basically stateless, runs one step and returns the results. I am guessing the current implementation relies on some buffer internally populated that i being wiped clean after every cycle in our implementation - maybe similar as you were doing when messing with the C++ version?
On Wed, Apr 24, 2013 at 5:53 PM, Mike Vella <vell...@gmail.com> wrote:
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Giovanni Idili - http://www.linkedin.com/in/giovanniidili
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I don't really understand what you mean Giovanni? What information do these internal buffers contain?
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Well things like velocity of each particle need to be preserved for the integrator to function correctly. If you are not maintaining this state between time steps it can't work.
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I am searching for a sample implementation of PCI-SPH and Google brought me here as one of the top search results. I looked through some of the comments and postings on Openworm but I couldn't find the source code that you guys mentioned.
in the wiki, the links for the source code is gone
http://code.google.com/p/openworm/wiki/GettingStartedWithPhysics
--> http://code.google.com/p/openworm/downloads/list?q=label:SoftBodySolver
and the descriptions in this page show it only has basic SPH implementations
https://github.com/openworm/Smoothed-Particle-Hydrodynamics/tree/IntegratedVersion
I tried reading through the PCI-SPH paper to understand it myself, but I was stuck on how the author corrected the pressure based. The prediction step of the algorithm was confusing too, so I am searching for some sample code and trying to understand it from there.
Thanks
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