activity
20242026
most citedToward ultra-efficient high-fidelity prediction of bed morphodynamics of large-scale meandering rivers using a novel LES-trained machine learning approach

1 citations · 1 across the 3 of their papers we have counts for

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physics.flu-dyn2026

A novel machine learning framework based on proper orthogonal decomposition for turbine wake flow predictions in natural waterways

Mustafa Meriç Aksen, Hossein Seyedzadeh, Mehrshad Gholami Anjiraki +1

We developed a machine learning (ML) surrogate trained on instantaneous large eddy simulation (LES) data filtered using proper orthogonal decomposition (POD) to predict mean flow f…

physics.flu-dyn2026

Computational and experimental study of multi-grain-size sediment transport and sorting process

Mehrshad Gholami Anjiraki, Gabriel Narh, Jonathan Craig +5

Successful prediction of the interaction between turbulent flows and river ecosystems is essential for flood management, development of mitigation strategies, and infrastructure pr…