MS1-12B Data-driven closure models for RANS and LES

Fri, 28/04/2023
13:45 - 15:45
Auditorium E
Chaired by:
Prof. Heng Xiao ( University of Stuttgart)

Contributions in this session:

  • (Keynote) Neural-network-based mixed subgrid-scale model for turbulent flow
    Y. Jeon, M. Kang, D. You*
  • Using Machine Learning to Predict Reynolds Stress in Flows Over a Surface-Mounted Solid and Porous Block
    A. Man*, A. Keshmiri, H. Yin, Y. Mahmoudi Larimi
  • POD-mode-augmented Wall Model and its Applications to Flows at Non-equilibrium Conditions
    C. Hansen, X. Yang, M. Abkar*
  • Enhancement of Subgrid-Scale Turbulence-Chemistry Interaction Physics-Based Models: A Data-Driven Perspective
    R. da Silva Machado de Freitas*, A. Pequin, R. Malpica Galassi, A. Parente
  • Reconstruction of Turbulent Flows Using Generative Diffusion Models
    M. Sardar*, A. Skillen, M. J. Zimoń, S. Draycott, A. Revell