59 citations · 128 across the 7 of their papers we have counts for
7 papers
Wind-farm power prediction using a turbulence-optimized Gaussian wake model
Navid Zehtabiyan-Rezaie, Josephine Perto Justsen, Mahdi Abkar
In this study, we present an improved formulation for the wake-added turbulence to enhance the accuracy of intra-farm and farm-to-farm wake modeling through analytical frameworks.…
A progressive data-augmented RANS model for enhanced wind-farm simulations
Ali Amarloo, Navid Zehtabiyan-Rezaie, Mahdi Abkar
The development of advanced simulation tools is essential, both presently and in the future, for improving wind-energy design strategies, paving the way for a complete transition t…
An extended model for wake-flow simulation of wind farms
Navid Zehtabiyan-Rezaie, Mahdi Abkar
The Reynolds-averaged Navier-Stokes approach coupled with the standard model is widely utilized for wind-energy applications. However, it has been shown that the st…
A short note on turbulence characteristics in wind-turbine wakes
Navid Zehtabiyan-Rezaie, Mahdi Abkar
Analytical wake models need formulations to mimic the impact of wind turbines on turbulence level in the wake region. Several correlations can be found in the literature for this p…
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…