60 citations · 178 across the 14 of their papers we have counts for
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physics.flu-dyn2024★ 1 cited
Toward ultra-efficient high-fidelity prediction of bed morphodynamics of large-scale meandering rivers using a novel LES-trained machine learning approach
Zexia Zhang, Mehrshad Gholami Anjiraki, Hossein Seyedzadeh +2
Flood-induced deformation of the bed topography of fluvial meandering rivers could lead to river bank displacement, structural failure of the infrastructures, and the propagation o…
physics.flu-dyn2024
Toward ultra-efficient high fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models via LES-trained machine learning
Christian Santoni, Dichang Zhang, Zexia Zhang +3
This study proposes a novel machine learning (ML) methodology for the efficient and cost-effective prediction of high-fidelity three-dimensional velocity fields in the wake of util…