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Mehrshad Gholami Anjiraki

3 papers hereh-index 224 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • physics.flu-dyn3
same name
  • Mehrshad Gholami Anjiraki — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

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

collaborators

3 papers

physics.flu-dyn2025

Computational study of vertical-axis MHK turbines using a coupled flow-sediment-turbine modeling approach

Mehrshad Gholami Anjiraki, Mustafa Meriç Aksen, Samin Shapourmiandouab +2

We present a coupled large-eddy simulation (LES) and bed morphodynamics study to investigate the influence of sediment dynamics on the performance of a utility-scale marine hydroki…

physics.flu-dyn2025

On the interaction of fish and marine hydrokinetic turbines: Insights gained through experimental and computational observations

Hossein Seyedzadeh, Mehrshad Gholami Anjiraki, Guglielmo Sonnino Sorisio +3

Tidal and riverine hydrokinetic turbines offer promising solutions for renewable energy generation in aquatic environments. However, their ecological impact, especially on fish beh…

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…

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