FLOWFarm.jl Integration#182
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Apr 2, 2026
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overall, this looks pretty good! let's fight through some of the architecture stuff and try to clean up. one thing I was noticing fairly consistently is that there is a lot of complex and potentially over-engineered (possibly AI produced?) code and we should make sure to keep it as simple and clean as possible. FWIW, I'm fine w/ AI-supported code but I do demand a tight leash with it: a human somewhere needs to know what every single line does and why it's necessary.
distance_point_to_polygon_ray_casting and distance_multi_point_to_multi_polygon_ray_casting hardcoded jnp.float32 for turbine points and polygon vertices, despite jax_enable_x64=True being set in boundary.py. At km-scale site coordinates, float32 quantization noise gets amplified through the s=700 smooth_max/ smooth_min sharpness, producing O(0.1-1) errors in boundary_distances gradients vs FD. Switch both casts to float64.
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Added FLOWFarm.jl as an aero model. Added integration tests. Added a README specific to FLOWFarm.jl and Julia setup. I attempted to keep the integration as noninvasive as possible, focusing on the fact that Ard should still run without Julia as long as the FLOWFarm model is not being used.
I created a working example that imitates example 01 but just uses the FLOWFarm model.