Comments (1)
Just noting that (in case if you're in a hurry) rhoto5d
is not needed to generate alpha particles. You can sample markers directly from the fusion distribution and, if you need importance sampling for the wall loads, just pick ones that have rho > some_value. For practical purposes this is quite close to what rhoto5d
would provide.
In any case this segfault should be fixed. I'm fairly certain this is stellarator specific as it has not been tested for stellarators. My guess is that it is this line where the segfault is coming from (though this is the only part I'm fairly sure should work for stellarators):
ascot5/a5py/routines/markergen.py
Line 262 in 20656e3
Could you test that by replicating that function call in a separate script? Just replace self._ascot
with the Ascot object (a5
). You could also try running valgrind to locate the segfault, but that might mean you'd have to use smaller distribution grid resolution for it to complete within a reasonable time.
Can you confirm that the magnetic field data covers the entire (R,z) grid you are using in the distribution?
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Related Issues (20)
- BBNBI5 resulting markers and distribution weights don't match HOT 1
- Bug in atomic model HOT 1
- Distributions not properly updated when using adaptive timestep HOT 1
- Alternative definition for Coulomb logarithm
- Stellarator test case and tutorial
- Improve input error detection HOT 2
- ICRH operator
- Serpent-AFSI interface
- Bug in afsi.thermal HOT 9
- Some features to analyse 2D wall loads HOT 4
- No n_phi dependence in afsi_get_volume HOT 3
- Major cleanup of a5py (and some plans for ASCOT5's future) HOT 2
- Restart option for very time consuming jobs HOT 3
- Upgrade to numpy 2.0
- Check convergence of heat load on specific wall flag HOT 3
- Improved hybrid mode
- a5editoptions rejects float values for the distribution charge bin edges
- Recording GO results as GCs (RECORD_MODE=1) results in 1e4 times more particles in the fast ion distribution HOT 1
- Scale markergen to represent all particles
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