33 citations · 35 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2025★ 2 cited
Using Physics Informed Neural Network (PINN) and Neural Network (NN) to Improve a Turbulence Model
Lars Davidson
l flows and flat-plate boundary layers. However, it predicts too low a turbulent kinetic energy. This is a feature it shares with most other two-equation turbulence models. When co…
physics.flu-dyn2024
Physics informed data-driven near-wall modelling for lattice Boltzmann simulation of high Reynolds number turbulent flows
Xiao Xue, Shuo Wang, Hua-Dong Yao +2
Data-driven approaches offer novel opportunities for improving the performance of turbulent flow simulations, which are critical to wide-ranging applications from wind farms and ae…
physics.flu-dyn2021★ 33 cited
Tonal Noise of Voluteless Centrifugal Fan Generated by Turbulence Stemming from Upstream Inlet Gap
Martin Ottersten, Hua-Dong Yao, Lars Davidson
In this study, noise generation is investigated for a generic voluteless centrifugal HVAC fan at an off-design operation point where tonal noise increases. The simulations are perf…