Iungo, Giacomo V.
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Giacomo Iungo is currently an Assistant Professor of Mechanical Engineering and head of the WindFluX (Wind, Fluids, and eXperiments) Lab. His research interests include wind energy, flow instability, bluff body aerodynamics; atmospheric boundary layer, reduced order models; signal processing; wind tunnel design; experimental fluid mechanics; and wind LiDAR technology.
Works in Treasures @ UT Dallas are made available exclusively for educational purposes such as research or instruction. Literary rights, including copyright for published works held by the creator(s) or their heirs, or other third parties may apply. All rights are reserved unless otherwise indicated by the copyright owner(s).
Recent Submissions
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Quantification of the Axial Induction Exerted by Utility-Scale Wind Turbines by Coupling LiDAR Measurements and RANS Simulations
The axial induction exerted by utility-scale wind turbines for different operative and atmospheric conditions is estimated by coupling ground-based LiDAR measurements and RANS simulations. The LiDAR data are thoroughly ... -
Coupling of Mesoscale Weather Research and Forecasting Model to a High Fidelity Large Eddy Simulation
Numerical simulations of the flow in a wind farm in north Texas have been performed with WRF (Weather Research and Forecasting model) and our in-house LES code. Five nested domains are solved with WRF to model the meso-scale ... -
Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign
To assess current capabilities for measuring flow within the atmospheric boundary layer, including within wind farms, the U.S. Department of Energy sponsored the eXperimental Planetary boundary layer Instrumentation ... -
Identification of Tower-Wake Distortions Using Sonic Anemometer and Lidar Measurements
(Copernicus GmbH, 2018-08-31)The eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) field campaign took place in March through May 2015 at the Boulder Atmospheric Observatory, utilizing its 300 m meteorological tower, instrumented ... -
Assessment of Virtual Towers Performed with Scanning Wind Lidars and Ka-Band Radars during the XPIA Experiment
During the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign, which was carried out at the Boulder Atmospheric Observatory (BAO) in spring 2015, multiple-Doppler scanning strategies were ... -
Evaluation of Single and Multiple Doppler Lidar Techniques to Measure Complex Flow During the XPIA Field Campaign
(Copernicus GmbH, 2018-08-20)Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow but also understanding the underlying physical processes and improving flow modeling. However, a ... -
Vertical Profiles of the 3-D Wind Velocity Retrieved from Multiple Wind Lidars Performing Triple Range-Height-Indicator Scans
(Copernicus GmbH, 2018-08-20)Vertical profiles of 3-D wind velocity are retrieved from triple range-height-indicator (RHI) scans performed with multiple simultaneous scanning Doppler wind lidars. This test is part of the eXperimental Planetary boundary ... -
Instability of Wind Turbine Wakes Immersed in the Atmospheric Boundary Layer
In this work a technique capable to investigate the near-wake stability properties of a wind turbine immersed in the atmospheric boundary layer is presented. Specifically, a 2D local spatial stability analysis is developed ... -
Effects of Incoming Wind Condition and Wind Turbine Aerodynamics on the Hub Vortex Instability
Dynamics and instabilities occurring in the near-wake of wind turbines have a crucial role for the wake downstream evolution, and for the onset of far-wake instabilities. Furthermore, wake dynamics significantly affect the ... -
Data-Driven RANS for Simulations of Large Wind Farms
In the wind energy industry there is a growing need for real-time predictions of wind turbine wake flows in order to optimize power plant control and inhibit detrimental wake interactions. To this aim, a data-driven RANS ... -
Data-Driven Reduced Order Model for Prediction of Wind Turbine Wakes
In this paper a new paradigm for prediction of wind turbine wakes is proposed, which is based on a reduced order model (ROM) embedded in a Kalman filter. The ROM is evaluated by means of dynamic mode decomposition performed ...
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