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20222025
most citedQuantification of Reynolds-averaged-Navier-Stokes model form uncertainty in transitional boundary layer and airfoil flows

9 citations · 13 across the 14 of their papers we have counts for

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cs.LG2025

Physics-Guided Machine Learning for Uncertainty Quantification in Turbulence Models

Minghan Chu, Weicheng Qian

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications intr…

physics.flu-dyn2025

Towards Physics Constrained Deep Learning Based Turbulence Model Uncertainty Quantification

Minghan Chu, Weicheng Qian

Turbulence Models represent the workhorse for simulations used in engineering design and analysis. Despite their low computational cost and robustness, these models suffer from sub…