Enhancing computational fluid dynamics with machine learning
Abstract Machine learning is rapidly becoming a core technology for scientific computing,
with numerous opportunities to advance the field of computational fluid dynamics. Here we …
with numerous opportunities to advance the field of computational fluid dynamics. Here we …
Turbulence modeling in the age of data
K Duraisamy, G Iaccarino, H **ement cooling solution for high-power devices
A high-efficiency three-dimensionally (3-D) shaped polymer multi-jet im**ement cooler
based on cost-efficient fabrication techniques is introduced for the cooling of high-power …
based on cost-efficient fabrication techniques is introduced for the cooling of high-power …
Model-form uncertainty quantification of Reynolds-averaged Navier–Stokes modeling of flows over a SD7003 airfoil
Reynolds-averaged Navier–Stokes (RANS) models are known to be inaccurate in complex
flows, for instance, laminar-turbulent transition, and RANS uncertainty quantification (UQ) is …
flows, for instance, laminar-turbulent transition, and RANS uncertainty quantification (UQ) is …
Quantification of Reynolds-averaged-Navier–Stokes model-form uncertainty in transitional boundary layer and airfoil flows
It is well known that the Boussinesq turbulent-viscosity hypothesis can introduce uncertainty
in predictions for complex flow features such as separation, reattachment, and laminar …
in predictions for complex flow features such as separation, reattachment, and laminar …