2 papers
cs.LG2025
Quantifying Out-of-Training Uncertainty of Neural-Network based Turbulence Closures
Cody Grogan, Som Dhulipala, Mauricio Tano +2
Neural-Network (NN) based turbulence closures have been developed for being used as pre-trained surrogates for traditional turbulence closures, with the aim to increase computation…
physics.flu-dyn2024
Quantifying Model Uncertainty of Neural Network-based Turbulence Closures
Cody Grogan, Som Dutta, Mauricio Tano +2
With increasing computational demand, Neural-Network (NN) based models are being developed as pre-trained surrogates for different thermohydraulics phenomena. An area where this ap…