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<h1>AirfRANS / neural CFD surrogate</h1>
<p>This fake writeup pretends the goal is simple: make a neural surrogate that behaves enough like a CFD solver to be useful, but not so much like a CFD solver that it takes all afternoon to answer.</p>
<p>The model gets geometry, flow conditions, and a stern lecture from validation metrics. It returns fields, uncertainty hints, and the occasional reminder that conservation laws are not optional.</p>
<p>The interesting part is the boundary between learned approximation and solver-grounded truth: where the network is fast, where it is wrong, and how to know before a wing falls off in a slide deck.</p>
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