activity
20182026
most citedPhysics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data

1.1k citations · 1.1k across the 18 of their papers we have counts for

collaborators
Showing physics.flu-dynShow all

2 papers · 1 filter

physics.flu-dyn2023★ 1 cited

Physics-Informed Tensor Basis Neural Network for Turbulence Closure Modeling

Leon Riccius, Atul Agrawal, Phaedon-Stelios Koutsourelakis

Despite the increasing availability of high-performance computational resources, Reynolds-Averaged Navier-Stokes (RANS) simulations remain the workhorse for the analysis of turbule…

physics.flu-dyn2023

A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty

Atul Agrawal, Phaedon-Stelios Koutsourelakis

We propose a data-driven, closure model for Reynolds-averaged Navier-Stokes (RANS) simulations that incorporates aleatoric, model uncertainty. The proposed closure consists of two…