2 citations · 2 across the 1 of their papers we have counts for
2 papers
physics.flu-dyn2021★ 2 cited
Data-Driven Modeling of Coarse Mesh Turbulence for Reactor Transient Analysis Using Convolutional Recurrent Neural Networks
Yang Liu, Rui Hu, Adam Kraus +2
Advanced nuclear reactors often exhibit complex thermal-fluid phenomena during transients. To accurately capture such phenomena, a coarse-mesh three-dimensional (3-D) modeling capa…
physics.flu-dyn2020
Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments
Yang Liu, Dewei Wang, Xiaodong Sun +2
In this paper, we develop a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of the two-fluid model-based multiphase computational fluid…