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  1. Enabling Resolvent Analysis Through Assimilation of Experimental Mean Flows with Physics-Informed Neural Networks: A Case Study on the Boeing Gaussian Bump
  2. Surrogate-based modeling for investigating and controlling the response of an axisymmetric jet to harmonic forcing
  3. Publisher's Note: “Mean flow data assimilation based on physics-informed neural networks” [Phys. Fluids 34, 115129 (2022)]
  4. Neural networks allow detecting physical quantities that go beyond lab measurements.