59 citations · 128 across the 7 of their papers we have counts for
3 papers · 1 filter
Physics-guided machine learning for wind-farm power prediction: Toward interpretability and generalizability
Navid Zehtabiyan-Rezaie, Alexandros Iosifidis, Mahdi Abkar
With the increasing amount of available data from simulations and experiments, research for the development of data-driven models for wind-farm power prediction has increased signi…
Data-driven quantification of model-form uncertainty in Reynolds-averaged simulations of wind farms
Ali Eidi, Navid Zehtabiyan-Rezaie, Reza Ghiassi +2
Computational fluid dynamics using the Reynolds-averaged Navier-Stokes (RANS) remains the most cost-effective approach to study wake flows and power losses in wind farms. The under…
Data-driven fluid mechanics of wind farms: A review
Navid Zehtabiyan-Rezaie, Alexandros Iosifidis, Mahdi Abkar
With the growing number of wind farms over the last decades and the availability of large datasets, research in wind-farm flow modeling - one of the key components in optimizing th…