59 citations · 271 across the 20 of their papers we have counts for
20 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…
A priori screening of data-enabled turbulence models
Peng E S Chen, Yuanwei Bin, Xiang I A Yang +3
Assessing the compliance of a white-box turbulence model with known turbulent knowledge is straightforward. It enables users to screen conventional turbulence models and identify a…
Progressive augmentation of Reynolds stress tensor models for secondary flow prediction by computational fluid dynamics driven surrogate optimisation
M. J. Rincón, A. Amarloo, M. Reclari +2
Generalisability and the consistency of the a posteriori results are the most critical points of view regarding data-driven turbulence models. This study presents a progressive imp…
Extension of the law of the wall exploiting weak similarity of velocity fluctuations in turbulent channels
Christoffer Hansen, Jens N. Sørensen, Xiang I. A. Yang +1
This paper explores the similarity of the streamwise velocity fluctuations in a channel. In the analysis, we employ a one-dimensional scalar variant of the proper orthogonal decomp…
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…
Log-law recovery through reinforcement-learning wall model for large-eddy simulation
Aurélien Vadrot, Xiang I. A. Yang, H. Jane Bae +1
This paper focuses on the use of reinforcement learning (RL) as a machine-learning (ML) modeling tool for near-wall turbulence. RL has demonstrated its effectiveness in solving hig…
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…
POD-mode-augmented wall model and its applications to flows at non-equilibrium conditions
Christoffer Hansen, Xiang IA Yang, Mahdi Abkar
Insights gained from modal analysis are invoked for predictive large-eddy simulation (LES) wall modeling. Specifically, we augment the law of the wall (LoW) by an additional mode b…
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…
Survey of machine learning wall models for large eddy simulation
Aurélien Vadrot, Xiang I. A. Yang, Mahdi Abkar
This survey investigates wall modeling in large eddy simulations (LES) using data-driven machine learning (ML) techniques. To this end, we implement three ML wall models in an open…
Frozen propagation of Reynolds force vector from high-fidelity data into Reynolds-averaged simulations of secondary flows
Ali Amarloo, Pourya Forooghi, Mahdi Abkar
Successful propagation of information from high-fidelity sources (i.e., direct numerical simulations and large-eddy simulations) into Reynolds-averaged Navier-Stokes (RANS) equatio…
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…
Constructing Neural Network-Based Models for Simulating Dynamical Systems
Christian Møldrup Legaard, Thomas Schranz, Gerald Schweiger +6
Dynamical systems see widespread use in natural sciences like physics, biology, chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics…
Model-form uncertainty quantification in RANS simulations of wakes and power losses in wind farms
Ali Eidi, Reza Ghiassi, Xiang Yang +1
Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient approaches to simulate wind-farm-atmosphere interactions. However, the applicability of RANS-based methods…
Determining a priori a RANS model's applicable range via global epistemic uncertainty quantification
Xinyi Huang, Naman Jain, Mahdi Abkar +2
Calibrating a Reynolds-averaged Navier-Stokes (RANS) model against data leads to an improvement. Determining {\it a priori} if such an improvement generalizes to flows outside the…
Wake steering of multirotor wind turbines
Gustav A. Speakman, Mahdi Abkar, Luis A. Martínez-Tossas +1
In this paper, wake steering is applied to multirotor turbines to determine whether it has the potential to reduce wind plant wake losses. Through application of rotor yaw to multi…
Improved energy production of multi-rotor wind farms
M. Paul van der Laan, Mahdi Abkar
The multi-rotor (MR) wind turbine concept can be used to upscale wind turbines without increasing the rotor diameter, which can be beneficial for transport, manufacture and design…
Reissner-Nordstrom Black Holes in Quartic Quasi-Topological Gravity Theory
M. Ghanaatian, F. Naeimipour, A. Bazrafshan +1
In this paper, we construct the exact solutions of Reissner-Nordstrom black holes in the presence of quartic quasi-topological gravity. we obtain the thermodynamics and conserved q…