CFC2023

MS1-08C Equation- and Data-driven Reduced-order Modeling for Fluid Flows

Wed, 26/04/2023
16:00 - 18:00
Auditorium K
MS1-08C

Contributions in this session:


  • (Keynote) A Blended Projection-Based Reduced-Order Model-Artificial NeuralNetwork Concept for Addressing the Kolmogorov Barrier to the Reducibility of CFD Models
    C. Farhat*, J. Barnett, Y. Maday
  • Reduced-Order Modeling of Turbulent Combustion Without Offline Training Using Time-Dependent Bases
    H. Babaee*
  • Fast and accurate reduced order modelling for the simulation of blood flow dynamics
    P. Siena*, C. Balzotti, M. Girfoglio, A. Quaini, G. Rozza
  • Inferring Models for the Pressure Gradient in an Idealized Stenosis
    E. Livingston*, A. Figueroa, K. Garikipati
  • Reduced Order Models on a Variational Multi-Scale Model of Navier--Stokes
    D. Torlo*, S. Rubino, G. Stabile