MS1-01B Data-based technologies for modelling, informing and augmenting learning about fluids and flow simulations

Thu, 27/04/2023
13:45 - 15:45
Auditorium C

Contributions in this session:

  • (Keynote) Temperature field inference using physics-informed neural networks in turbulent natural convection
    K. Doria, A. Sergent*, D. Lucor
  • Physics-constrained Deep Learning for the k-epsilon Turbulence Model Calibration
    L. Cotteleer*, A. Parente
  • Active flow control on 3D cylinders through deep reinforcement learning
    P. Suárez*, F. Alcántara-Ávila, A. Miró, J. Rabault, B. Font, O. Lehmkhul, R. Vinuesa
  • Dealing with faulty sensors: a physics-informed convolutional neural network approach for recovering solutions to governing equations
    D. Kelshaw*, L. Magri