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start-again-06/MSML---Optimal-Transport-PINNs-A-Data-Efficient-Approach-to-High-Fidelity-Turbulence-Modeling — AI/Bot Repository
Turbulence modelling in CFD is limited by the tradeoff between accuracy and cost. We propose OT PINNs, Physics Informed Neural Networks with an Optimal Transport based loss, to improve training stability and accuracy under noisy data. With SINDy for interpretability, our method rivals DNS on benchmark flows while cutting computational costs.
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