Reverse-Mode Differentiable Ideal-Ballooning Stability Solver #1170
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f0uriest
reviewed
Aug 22, 2024
desc/compute/_stability.py
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| N_alpha = int(source_grid.num_alpha) | ||
| N_zeta = int(len(phi) / N_alpha) | ||
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| B = jnp.reshape(data["|B|"], (N_alpha, 1, N_zeta)) |
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I think you might have to change this after #1214 was merged, you can use
B = transforms['grid'].meshgrid_reshape(data['|B|'], "arz"), similar for the other places you reshape stuff to separate the fieldlines. I can do it tomorrow, let's see if the tests fail.
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Infinite-n ideal MHD ballooning modes are of significant interest to both the tokamak and the stellarator community.
These instabilities are also related to smaller-scale kinetic instabilities, which cause significant heat loss from fusion reactors.
This commit adds the ability to both analyze and optimize MHD equilibria against the ideal ballooning mode.
An adjoint implementation of an ideal ballooning solver has only been successfully demonstrated previously on a much smaller scale. If this commit works, it would be at least an order of magnitude faster than the linked code.
Here are the tasks: