2021/02/24: Congratulations to Coleman Moss for receiving a Jonsson School Undergraduate Research Award for his work on modeling wind farm performance with Machine Learning

2020/11/13: Dr. Iungo has received the CAREER Award from NSF CBET Fluid Dynamics!!! (link)

2020/08/26: New NSF MRI project in collaboration with the University of Minnesota-Twin Cities to develop a field-scale imaging system to investigate atmospheric turbulence and aerosol transport (link)

2018/08/20: The UTD BLAST Wind Tunnel is now Fully Operational!  G.V. Iungo design; AIOLOS Engineering; UTD-funded project (link)

 more news

Current Projects

Genesis and Dynamics of very-large-scale Motions in the Atmospheric Boundary Layer and their Interactions with Utility-scale Wind Turbines

Funding Agency: NSF CBET Fluid Dynamics, Program Manager Ronald Joslin

Award Number: 1705837

Project Period: September 1, 2017 – August 31, 2020


Abstract: In wind energy technology, predicting the evolution of wind turbine wakes under different atmospheric conditions is important for optimizing power production from a wind farm and mitigating damaging loads on the turbines due to detrimental wake interactions. This project aims to investigate the origin, evolution and regeneration of what are called very-large-scale motions (VLSMs) that evolve in the layer of air near the blade surface, termed the atmospheric boundary layer (ABL), and their interactions with utility-scale wind turbines. As the scale of wind farms continues to grow and as wind turbines increase in size, VLSMs are expected to profoundly influence wind power production and the downstream evolution of wind turbine wakes. However, the origin and dynamics of VLSMs are not well understood in some cases, and therefore their effects and interactions with utility-scale wind turbines are difficult to predict. This project advances numerical simulations and proof-of-concept laboratory experiments on this topic. Additionally, undergraduate students are being trained to measure wind velocities at the University of Texas Dallas mobile LIDAR (Light Imaging, Detection, And Ranging) station, which is a unique facility for education and outreach activities. This training impact students from a wide range of backgrounds and makes them aware of important topics, such as meteorology, extreme weather phenomena, anthropogenic effects on the environment and renewable energy.


Transport of Aerosolized Oil Droplets in Marine Atmospheric Boundary Layer: Coupling Wind LiDAR Measurements and Large-Eddy Simulations

Funding Agency: Gulf of Mexico Research Initiative, Year 8-10 Research Grant (RFP-VI)

Project Period: January 1, 2018 – December 31, 2019


Abstract: The proposed research aims to develop a numerical tool for thorough predictions of production of aerosolized oil droplets at the sea-air interface, their transport within the marine atmospheric boundary layer (ABL) and deposition over a coastal region. The scientific goals of the proposed project are to: 1) understand the role of ABL structure and wave motion on aerosol generation at the sea-air interface; 2) investigate effects of transitioning from the ocean to the coast on aerosol concentration and distribution; 3) develop eddy-diffusivity models for regional meteorology algorithms by avoiding the typical assumption of a flat and homogeneous ocean surface and including a realistic wave motion. This project will be conducted through two interrelated tasks: one LiDAR measurement campaign will be performed in the Galveston area, TX, to generate unprecedented simultaneous and co-located observations of wind speed and aerosol concentration, while high-fidelity wind-wave coupled large eddy simulations (LES) will be performed to investigate aerosol dynamics, and finally reproduce the LiDAR observations.


Wind Sensing Experiment

Funding Agency: Battelle Memorial Institute Pacific Northwest National Laboratory; sub-award UT Austin

Project Period: August 10, 2016 – September 30, 2018


Characterization of wind farm

Location: Panhandle, Amarillo.

Duration: July 2015- present

Campaign photo


Finished Project

XPIA (eXperimental Planetary boundary layer Instrumentation Assessment)

Location: Boulder Atmospheric Observatory, Boulder, Colorado.

Collaborators: NOAA, the University of Colorado at Boulder, Texas Tech University, the University of Maryland at Baltimore County, PNNL, NREL.

Duration: March 2015-May 2015

Campaign photo


Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment

Mithu Debnath, Giacomo Valerio Iungo, W. Alan Brewer, Aditya Choukulkar, Ruben Delgado, Scott Gunter, Julie K. Lundquist, John L. Schroeder, James M. Wilczak, and Daniel Wolfe, Atmos. Meas. Tech., 10, 1215-1227, doi:10.5194/amt-10-1215-2017, 2017.

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Vertical profiles of the 3-D wind velocity retrieved from multiple wind lidars performing triple range-height-indicator scans

Mithu Debnath, G. Valerio Iungo, Ryan Ashton, W. Alan Brewer, Aditya Choukulkar, Ruben Delgado, Julie K. Lundquist, William J. Shaw, James M. Wilczak, and Daniel Wolfe, Atmos. Meas. Tech., 10, 431-444, doi:10.5194/amt-10-431-2017, 2017.

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Identification of tower-wake distortions using sonic anemometer and lidar measurements

Katherine McCaffrey, Paul T. Quelet, Aditya Choukulkar, James M. Wilczak, Daniel E. Wolfe, Steven P. Oncley, W. Alan Brewer, Mithu Debnath, Ryan Ashton, G. Valerio Iungo, and Julie K. Lundquist, Atmos. Meas. Tech., 10, 393-407, doi:10.5194/amt-10-393-2017, 2017.

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Evaluation of single and multiple Doppler lidar techniques  to measure complex flow during the XPIA field campaign

Aditya Choukulkar , W. Alan Brewer, Scott P. Sandberg , Ann Weickmann , Timothy A. Bonin , R. Michael Hardesty1, Julie K. Lundquist, Ruben Delgado , G. Valerio Iungo , Ryan Ashton , Mithu Debnath , Laura Bianco,, James M. Wilczak , Steven Oncley , and Daniel Wolfe, Atmos. Meas. Tech., 10, 247-264, doi:10.5194/amt-10-247-2017, 2017.

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Assessing state-of-the-art capabilities for probing the atmospheric boundary layer: the XPIA field campaign.

Julie K. Lundquist et al., Bulletin of the American Meteorological Society, June 2016, doi: 10.1175/BAMS-D-15-00151.1

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