MS1-05B Machine Learning in CFD

Wed, 26/04/2023
13:45 - 15:45
Auditorium J
Chaired by:
Prof. Wagdi Habashi (McGill University)

Contributions in this session:

  • A heterogeneous computing approach to coupled simulation and machine-learning deployment for high-speed flows
    C. Laurent*, K. Maeda, T. Teixeira, G. Iaccarino
  • A Model-Constrained Tangent Manifold Learning Approach for Dynamical Systems
    H. Nguyen, H. Li, T. Bui Thanh*
  • A proposed hybrid two-stage DL-HPC method for wind speed forecasting: using the first average forecast output for long-term forecasting
    R. Hassanian*, Á. Helgadóttir, M. Aach, A. Linteramnn, M. Riedel
  • Prediction of CFD analysis results using deep learning
    M. Masuda*, Y. Nakabayashi, Y. Tamura
  • Prediction of Flow Characteristics of the Three-Dimensional Wavy Wing using CNN and Encoder-Decoder Models
    M. Kim*, H. Yoon