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

Thu, 27/04/2023
10:00 - 12:00
Auditorium C

Contributions in this session:

  • (Keynote) Uncertainty Quantification with Surrogate Models for Plastics Flow in Manufacturing Engineering
    F. Key*, S. Elgeti
  • Cognitive digital twins for physically sound active learning in fluid dynamics
    B. Moya*, A. Badias, D. Gonzalez, F. Chinesta, E. Cueto
  • Wall Modeling in LES of Turbulent Flows Using Reinforcement Learning
    A. Vadrot*, X. Yang, M. Abkar
  • Artificial Neural Networks Based Closure Models for Reduced Order Models in Computational Fluid Mechanics
    Z. DAR*, R. Codina, J. Baiges
  • Community Analysis of Bifurcation Maps for the Data Based Analysis of Combustion in WSFRs Applied to Diluted Hydrogen Mixtures
    J. He*, Y. Li, L. Ji, L. Acampora, F. Marra