1 citations · 1 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2026
A formal log(Re)-cost framework for the engineering turbulence problem
Jiaqi Li, Robert F. Kunz, George Huang +1
In fluid engineering, the turbulence problem is the longstanding challenge of obtaining accurate predictions of engineering quantities at affordable computational cost. Viewed thro…
physics.flu-dyn2023★ 1 cited
Incorporating basic calibrations in existing machine-learned turbulence modeling
Jiaqi J. L. Li, Yuanwei Bin, George P. Huang +1
This work aims to incorporate basic calibrations of Reynolds-averaged Navier-Stokes (RANS) models as part of machine learning (ML) frameworks. The ML frameworks considered are tens…
physics.flu-dyn2023
Constrained re-calibration of Reynolds-averaged Navier-Stokes models
Yuanwei Bin, George Huang, Robert Kunz +1
The constants and functions in Reynolds-averaged Navier Stokes (RANS) turbulence models are coupled. Consequently, modifications of a RANS model often negatively impact its basic c…