2 papers
physics.flu-dyn2026
Accelerating Bayesian inverse design in computational fluid dynamics using neural operators
Bipin Tiwari, Omer San
Bayesian inverse design provides a principled framework for inferring aerodynamic geometries from sparse flow observations while quantifying uncertainty. However, its practical use…
physics.flu-dyn2024
Bridging Large Eddy Simulation and Reduced Order Modeling of Convection-Dominated Flows through Spatial Filtering: Review and Perspectives
Annalisa Quaini, Omer San, Alessandro Veneziani +1
Reduced order models (ROMs) have achieved a lot of success in reducing the computational cost of traditional numerical methods across many disciplines. For convection-dominated (e.…