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Giacomo Valerio Iungo

Assistant Professor

University of Texas at Dallas

United States

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Research Interests

Meteorology

70%

Climatology

30%

Wind Engineering

100%

Lidar Technology

90%

Large Eddy Simulation

60%

Atmospheric Science

60%

Atmospheric Dynamics

50%

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Articles21

Editorial for the collection “Preparatory Work for the American Wake Experiment (AWAKEN)”

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Year:

2025

Editorial for the collection “Wind tunnel research for renewable energies”

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Year:

2025

Realistic Noise Generation to Enhance Realism of Virtual Lidar Scans

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Year:

2025

Augmenting insights from wind turbine data through data-driven approaches

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Year:

2024

Effects of wind shear and thrust coefficient on the induction zone of a porous disk: A wind tunnel study

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Year:

2024

Stochastic modal velocity field in rough-wall turbulence

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Year:

2024

Quantification and assessment of the atmospheric boundary layer height measured during the AWAKEN experiment by a scanning LiDAR

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Year:

2024

Characterization of wind speed and directional shear at the AWAKEN field campaign site

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Year:

2023

Quantification of wind turbine energy loss due to leading‐edge erosion through infrared‐camera imaging, numerical simulations, and assessment against SCADA and meteorological data

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Year:

2023

Identification of the energy contributions associated with wall-attached eddies and very-large-scale motions in the near-neutral atmospheric surface layer through wind LiDAR measurements

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Year:

2023

Profiling wind LiDAR measurements to quantify blockage for onshore wind turbines

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Year:

2023

Predicting wind farm operations with machine learning and the P2D‐RANS model: A case study for an AWAKEN site

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Year:

2023

Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality

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Year:

2023

Blockage and speedup in the proximity of an onshore wind farm: A scanning wind LiDAR experiment

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Year:

2023

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

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Year:

2022

Design, steady performance and wake characterization of a scaled wind turbine with pitch, torque and yaw actuation

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Year:

2022

Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows

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Year:

2022

LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 1: Theoretical framework

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Year:

2021

LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 2: Applications to lidar measurements of wind turbine wakes

Article Link

Year:

2021

Spectral correction of turbulent energy damping on wind lidar measurements due to spatial averaging

Article Link

Year:

2021

Optimal tuning of engineering wake models through lidar measurements

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Year:

2020

Collaborators10

Jiarong Hong

University of Minnesota

UNITED STATES

michele guala

Professor

University of Minnesota

UNITED STATES

S. Ashwin Renganathan

Assistant Professor

The Pennsylvania State University - University Park Campus

UNITED STATES

JULIE LUNDQUIST

University of Colorado Boulder

UNITED STATES

Romit Maulik

Assistant Professr

Pennsylvania State University

UNITED STATES

S. Letizia

UNITED STATES

Petra Klein

UNITED STATES

Michael Heisel

University of Sydney

AUSTRALIA

Carlo Luigi Bottasso

Professor and Chair of Wind Energy

Technische Universität Kaiserslautern

GERMANY

Vaughan Voller

Professor

University of Minnesota

UNITED STATES

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