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Giacomo Valerio Iungo
Giacomo Valerio Iungo
Associate Professor, WindFluX Lab, University of Texas at Dallas
Bestätigte E-Mail-Adresse bei utdallas.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Field measurements of wind turbine wakes with lidars
GV Iungo, YT Wu, F Porté-Agel
Journal of Atmospheric and Oceanic Technology 30 (2), 274-287, 2013
2172013
Linear stability analysis of wind turbine wakes performed on wind tunnel measurements
GV Iungo, F Viola, S Camarri, F Porté-Agel, F Gallaire
Journal of Fluid Mechanics 737, 499-526, 2013
1482013
Volumetric lidar scanning of wind turbine wakes under convective and neutral atmospheric stability regimes
GV Iungo, F Porté-Agel
Journal of Atmospheric and Oceanic Technology 31 (10), 2035-2048, 2014
1372014
Prediction of the hub vortex instability in a wind turbine wake: stability analysis with eddy-viscosity models calibrated on wind tunnel data
F Viola, GV Iungo, S Camarri, F Porté-Agel, F Gallaire
Journal of Fluid Mechanics 750, R1, 2014
1262014
Data-driven Reduced Order Model for prediction of wind turbine wakes
GV Iungo, C Santoni-Ortiz, M Abkar, F Porté-Agel, MA Rotea, S Leonardi
Journal of Physics: Conference Series 625 (1), 12009-12018, 2015
1062015
Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological and wind LiDAR data
S El‐Asha, L Zhan, GV Iungo
Wind Energy 20 (11), 1823-1839, 2017
1022017
3D turbulence measurements using three synchronous wind lidars: Validation against sonic anemometry
FC Fuertes, GV Iungo, F Porté-Agel
Journal of Atmospheric and Oceanic Technology 31 (7), 1549-1556, 2014
922014
Experimental characterization of wind turbine wakes: Wind tunnel tests and wind LiDAR measurements
GV Iungo
Journal of Wind Engineering and Industrial Aerodynamics 149, 35-39, 2016
852016
LiDAR measurements for an onshore wind farm: Wake variability for different incoming wind speeds and atmospheric stability regimes
L Zhan, S Letizia, GV Iungo
Wind Energy, 2019
812019
Experimental investigation on the aerodynamic loads and wake flow features of low aspect-ratio triangular prisms at different wind directions
GV Iungo, G Buresti
Journal of Fluids and Structures 25 (7), 1119-1135, 2009
762009
Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: the XPIA field campaign
JK Lundquist, JM Wilczak, R Ashton, L Bianco, WA Brewer, A Choukulkar, ...
Bulletin of the American Meteorological Society 98 (2), 289-314, 2017
732017
Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes
M Debnath, C Santoni, S Leonardi, GV Iungo
Phil. Trans. R. Soc. A 375 (2091), 20160108, 2017
692017
Performance optimization of a wind turbine column for different incoming wind turbulence
V Santhanagopalan, MA Rotea, GV Iungo
Renewable Energy 116, 232-243, 2018
542018
Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign
A Choukulkar, WA Brewer, SP Sandberg, A Weickmann, TA Bonin, ...
Atmospheric Measurement Techniques 10 (1), 2017
502017
Correction of wandering smoothing effects on static measurements of a wing-tip vortex
GV Iungo, P Skinner, G Buresti
Experiments in fluids 46, 435-452, 2009
492009
Experimental investigation on the aerodynamic loads and wake flow features of a low aspect-ratio circular cylinder
GV Iungo, LM Pii, G Buresti
Journal of Fluids and Structures 28, 279-291, 2012
472012
Optimal tuning of engineering wake models through lidar measurements
L Zhan, S Letizia, GV Iungo
Wind Energy Science 5 (4), 1601-1622, 2020
432020
Identification of tower-wake distortions using sonic anemometer and lidar measurements
K McCaffrey, PT Quelet, A Choukulkar, JM Wilczak, DE Wolfe, SP Oncley, ...
Atmospheric Measurement Techniques 10 (2), 393-407, 2017
432017
Parametric study of urban-like topographic statistical moments relevant to a priori modelling of bulk aerodynamic parameters
X Zhu, GV Iungo, S Leonardi, W Anderson
Boundary-Layer Meteorology 162 (2), 231-253, 2017
402017
Data-driven wind turbine wake modeling via probabilistic machine learning
S Ashwin Renganathan, R Maulik, S Letizia, GV Iungo
Neural Computing and Applications, 1-16, 2022
382022
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