Iungo, Giacomo V.

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Giacomo Iungo is currently an Associate 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.

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Now showing 1 - 12 of 12
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    Wandering Corrections from PIV Measurements of Tornado-Like Vortices
    (Elsevier B.V.) Ashton, Ryan; Refan, M.; Iungo, Giacomo V.; Hangan, H.; Ashton, Ryan; Iungo, Giacomo V.
    Wandering of tornado-like vortices consists in random oscillations of the vortex core from its time-averaged position, which complicates efforts to characterize vortex characteristics. A procedure is then necessary to retrieve characteristics of tornado-like vortices not affected by wandering smoothing effects. This study explores two procedures to correct wandering effects on Particle Image Velocimetry data obtained from a down-scaled model of the WindEEE Dome simulator. The first procedure re-centers the velocity data as a function of the instantaneous location of the vortex center. The second procedure treats the time-averaged vortex velocity field as the convolution of a bi-variate normal probability density function, which represents the distribution of vortex center locations over horizontal planes orthogonal to the vortex axis and the instantaneous tornado velocity field. Depending on swirl ratio and vortex height, wandering amplitude was generally from 5% to 9% of the updraft radius. The re-centering procedure was found to be more accurate than the deconvolution procedure. When applied to the turbulence statistics of the velocity field, the correction revealed that a higher level of turbulence at the center of low swirl tornadoes is a result of wandering. Also, the corrected shear stresses revealed a spiral pattern for cases of higher swirl. Wandering effects increases with reducing swirl ratio. For this experiment, swirl ratio is reduced from 0.96 down to 0.22 and errors on the vortex core radius as high as 50% and reduction of the maximum tangential velocity of 13% were observed. © 2019 Elsevier Ltd
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    Quantification of the Axial Induction Exerted by Utility-Scale Wind Turbines by Coupling LiDAR Measurements and RANS Simulations
    (Institute of Physics Publishing) Iungo, Giacomo V.; Letizia, Stefano; Zhan, Lu; 0000-0002-0990-8133 (Iungo, GV); Iungo, Giacomo V.; Letizia, Stefano; Zhan, Lu
    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 post-processed in order to average the wake velocity fields by using as common reference frame their respective wake directions and the turbine hub location. The various LiDAR scans are clustered according to their incoming wind speed at hub height and atmospheric stability regime, namely Bulk Richardson number. Time-averaged velocity fields are then calculated as ensemble averages of the scans belonging to the same cluster. The LiDAR measurements are coupled with RANS simulations in order to estimate the rotor axial induction for each cluster of the LiDAR data. First, a control volume analysis of the streamwise momentum is applied to the time-averaged LiDAR velocity fields to obtain an initial estimate of the axial induction over the rotor disk. The calculated thrust force is imposed as forcing of an axisymmetric RANS simulation in order to estimate pressure, radial velocity and momentum fluxes. The latter are combined with the LiDAR streamwise velocity field in order to refine the estimate of the rotor axial induction through the control volume approach. This process is repeated iteratively until achieving convergence on the rotor axial induction while minimizing difference between LiDAR and RANS streamwise velocity fields. This procedure allows to single out the reduction in thrust load while the blade pitch angle is increased transitioning from region 2 to 3 of the power curve. Furthermore, an enhanced thrust force is observed for a fixed incoming wind speed and transitioning from stable to convective stability regimes. The presented technique is proposed as a data-driven alternative to the blade element momentum theory typically used with current actuator disk models in order to quantify rotor aerodynamic thrust for different operative and atmospheric conditions. © Published under licence by IOP Publishing Ltd.
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    Coupling of Mesoscale Weather Research and Forecasting Model to a High Fidelity Large Eddy Simulation
    (Institute of Physics Publishing) Santoni-Ortiz, Christian; Garcia-Cartagena, Edgardo Javier; Ciri, Umberto; Iungo, Giacomo V.; Leonardi, Stefano; 0000-0002-0990-8133 (Iungo, GV); 0000-0002-9809-7191 (Leonardi, S); Santoni-Ortiz, Christian; Garcia-Cartagena, Edgardo Javier; Ciri, Umberto; Iungo, Giacomo V.; Leonardi, Stefano
    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 variability while retaining a resolution of 50 meters in the wind farm region. The computational domain of our in-house LES code is nested into the inner most domain of the WRF simulation from where we get the inlet boundary conditions. The outlet boundary conditions are radiative and at this stage the coupling between the two codes is one-way. The turbines in WRF are mimicked using a modified Fitch approach, while in our in-house LES we have used a rotating actuator disk combined with immersed boundaries for tower and nacelle. Numerical results agree well with meteorological data from the met tower. The power production obtained numerically on each turbine compares well with SCADA data with an index of agreement ranging between 80% to 90%. The power production from the numerical results of our in-house LES code is slightly closer to SCADA data than that of WRF.
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    Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign
    (Amer Meteorological Soc) Lundquist, Julie K.; Wilczak, James M.; Ashton, Ryan; Bianco, Laura; Brewer, W. Alan; Choukulkar, Aditya; Clifton, Andrew; Debnath, Mithu; Hamidi, Armita; Iungo, Giacomo V.; Ashton, Ryan; Debnath, Mithu; Hamidi, Armita; Iungo, Giacomo V.
    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 Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment, highlight novel measurement approaches, and quantify uncertainties associated with these measurement methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes from scanning lidars and radars are in close agreement, enabling the assessment of spatial variability. Strengths of the radar systems used here include high scan rates, large domain coverage, and availability during most precipitation events, but they struggle at times to provide data during periods with limited atmospheric scatterers. In contrast, for the deployment geometry tested here, the lidars have slower scan rates and less range but provide more data during nonprecipitating atmospheric conditions. Microwave radiometers provide temperature profiles with approximately the same uncertainty as radio acoustic sounding systems (RASS). Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. Finally, we highlight cases for validation of mesoscale or large-eddy simulations, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling the resolution of finescale processes critical to understanding inhomogeneous boundary layer flows.
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    Identification of Tower-Wake Distortions Using Sonic Anemometer and Lidar Measurements
    (Copernicus GmbH, 2018-08-31) McCaffrey, K.; Quelet, P. T.; Choukulkar, A.; Wilczak, J. M.; Wolfe, D. E.; Oncley, S. P.; Alan Brewer, W.; Debnath, Mithu; Ashton, Ryan; Iungo, Giacomo V.; Lundquist, J. K.; 0000-0002-0990-8133 (Iungo, GV); Debnath, Mithu; Ashton, Ryan; Iungo, Giacomo V.
    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 with two sonic anemometers mounted on opposite sides of the tower at six heights. This allowed for at least one sonic anemometer at each level to be upstream of the tower at all times and for identification of the times when a sonic anemometer is in the wake of the tower frame. Other instrumentation, including profiling and scanning lidars aided in the identification of the tower wake. Here we compare pairs of sonic anemometers at the same heights to identify the range of directions that are affected by the tower for each of the opposing booms. The mean velocity and turbulent kinetic energy are used to quantify the wake impact on these first-and second-order wind measurements, showing up to a 50 % reduction in wind speed and an order of magnitude increase in turbulent kinetic energy. Comparisons of wind speeds from profiling and scanning lidars confirmed the extent of the tower wake, with the same reduction in wind speed observed in the tower wake, and a speed-up effect around the wake boundaries. Wind direction differences between pairs of sonic anemometers and between sonic anemometers and lidars can also be significant, as the flow is deflected by the tower structure. Comparisons of lengths of averaging intervals showed a decrease in wind speed deficit with longer averages, but the flow deflection remains constant over longer averages. Furthermore, asymmetry exists in the tower effects due to the geometry and placement of the booms on the triangular tower. An analysis of the percentage of observations in the wake that must be removed from 2 min mean wind speed and 20 min turbulent values showed that removing even small portions of the time interval due to wakes impacts these two quantities. However, a vast majority of intervals have no observations in the tower wake, so removing the full 2 or 20 min intervals does not diminish the XPIA dataset. © 2017 Author(s).
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    Assessment of Virtual Towers Performed with Scanning Wind Lidars and Ka-Band Radars during the XPIA Experiment
    (Copernicus GmbH) Debnath, Mithu; Iungo, Giacomo V. .; Brewer, W. Alan; Choukulkar, A.; Delgado, R.; Gunter, S.; Lundquist, J. K.; Schroeder, J. L.; Wilczak, J. M.; Wolfe, D.; Debnath, Mithu; Iungo, Giacomo V. .
    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 carried out with scanning wind lidars and Ka-band radars. Specifically, step-stare measurements were collected simultaneously with three scanning Doppler lidars, while two scanning Ka-band radars carried out simultaneous range height indicator (RHI) scans. The XPIA experiment provided the unique opportunity to compare directly virtual-tower measurements performed simultaneously with Ka-band radars and Doppler wind lidars. Furthermore, multiple-Doppler measurements were assessed against sonic anemometer data acquired from the meteorological tower (met-tower) present at the BAO site and a lidar wind profiler. This survey shows that-despite the different technologies, measurement volumes and sampling periods used for the lidar and radar measurements - a very good accuracy is achieved for both remote-sensing techniques for probing horizontal wind speed and wind direction with the virtual-tower scanning technique.
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    Vertical Profiles of the 3-D Wind Velocity Retrieved from Multiple Wind Lidars Performing Triple Range-Height-Indicator Scans
    (Copernicus GmbH, 2018-08-20) Debnath, Mithu; Iungo, Giacomo V.; Ashton, Ryan; Alan Brewer, W.; Choukulkar, A.; Delgado, R.; Lundquist, J. K.; Shaw, W. J.; Wilczak, J. M.; Wolfe, D.; 0000-0002-0990-8133 (Iungo, GV); Debnath, Mithu; Iungo, Giacomo V.; Ashton, Ryan
    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 layer Instrumentation Assessment (XPIA) campaign carried out at the Boulder Atmospheric Observatory. The three wind velocity components are retrieved and then compared with the data acquired through various profiling wind lidars and high-frequency wind data obtained from sonic anemometers installed on a 300 m meteorological tower. The results show that the magnitude of the horizontal wind velocity and the wind direction obtained from the triple RHI scans are generally retrieved with good accuracy. However, poor accuracy is obtained for the evaluation of the vertical velocity, which is mainly due to its typically smaller magnitude and to the error propagation connected with the data retrieval procedure and accuracy in the experimental setup.
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    Evaluation of Single and Multiple Doppler Lidar Techniques to Measure Complex Flow During the XPIA Field Campaign
    (Copernicus GmbH, 2018-08-20) Choukulkar, A.; Brewer, W. A.; Sandberg, S. P.; Weickmann, A.; Bonin, T. A.; Hardesty, R. M.; Lundquist, J. K.; Delgado, R.; Iungo, Giacomo V.; Ashton, Ryan; Debnath, Mithu; Bianco, L.; Wilczak, J. M.; Oncley, S.; Wolfe, D.; 0000-0002-0990-8133 (Iungo, GV); Iungo, Giacomo V.; Ashton, Ryan; Debnath, Mithu
    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 thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO, from 2 March to 31 May 2015 brought together a large suite of in situ and remote sensing measurement platforms to evaluate complex flow measurement strategies. In this paper, measurement uncertainties for different single and multi-Doppler strategies using simple scan geometries (conical, vertical plane and staring) are investigated. The tradeoffs (such as time-space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single-/multi-Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty. It was found that with an increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity along with horizontal homogeneity and less representative line-of-sight velocity statistics. It was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.
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    Instability of Wind Turbine Wakes Immersed in the Atmospheric Boundary Layer
    (Institute of Physics Publishing) Viola, F.; Iungo, Giacomo V.; Camarri, S.; Porté-Agel, F.; Gallaire, F.; Sorensen J.N.; Ivanell S.; Barney A.; Iungo, Giacomo V.
    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 in order to take into account typical flow features of real operating wind turbines, such as the presence of the atmospheric boundary layer and the turbulence heterogeneity of the oncoming wind. This stability analysis can be generally applied on either experimental measurements or numerical data. In this paper it was carried out on wind tunnel experiments, for which a downscaled wind turbine is immersed in a turbulent boundary layer. Through spatial stability analysis, the dominant mode in the near wake, i.e. the most amplified one, is characterized and its frequency matches the hub-vortex instability frequency measured in the wind tunnel. As in the case of 10], where an axisymmetric wake condition was investigated, the hub-vortex instability results in a single-helical mode.
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    Effects of Incoming Wind Condition and Wind Turbine Aerodynamics on the Hub Vortex Instability
    (Institute of Physics Publishing) Ashton, Ryan; Viola, F.; Gallaire, F.; Iungo, Giacomo V.; 0000-0002-0990-8133 (Iungo, GV); Sorensen J.N.; Ivanell S.; Barney A.; Ashton, Ryan; Iungo, Giacomo V.
    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 intra-wind farm wake flow, wake interactions and potential power losses. Therefore, the physical understanding and predictability of wind turbine wake instabilities become a nodal point for prediction of wind power harvesting and optimization of wind farm layout. This study is focused on the prediction of the hub vortex instability encountered within wind turbine wakes under different operational conditions of the wind turbine. Linear stability analysis of the wake flow is performed by means of a novel approach that enables to take effects of turbulence on wake instabilities into account. Stability analysis is performed by using as base flow the time-averaged wake velocity field at a specific downstream location. The latter is modeled through Carton-McWilliams velocity profiles by mimicking the presence of the hub vortex and helicoidal tip vortices, and matching the wind turbine thrust coefficient predicted through the actuator disc model. The results show that hub vortex instability is promoted by increasing the turbine thrust coefficient. Indeed, a larger aerodynamic load produces an enhanced wake velocity deficit and axial shear, which are considered the main sources for the wake instability. Nonetheless, wake swirl also promotes hub vortex instability, and it can also affect the azimuthal wavenumber of the most unstable mode.
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    Data-Driven RANS for Simulations of Large Wind Farms
    (Institute of Physics Publishing) Iungo, Giacomo V.; Viola, F.; Ciri, Umberto; Rotea, Mario A.; Leonardi, Stefano; 0000-0002-0990-8133 (Iungo, GV); 0000-0002-9809-7191 (Leonardi, S); Sorensen J.N.; Ivanell S.; Barney A.; Iungo, Giacomo V.; Ciri, Umberto; Rotea, Mario A.; Leonardi, Stefano
    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 approach is proposed in order to achieve very low computational costs and adequate accuracy through the data assimilation procedure. The RANS simulations are implemented with a classical Boussinesq hypothesis and a mixing length turbulence closure model, which is calibrated through the available data. High-fidelity LES simulations of a utility-scale wind turbine operating with different tip speed ratios are used as database. It is shown that the mixing length model for the RANS simulations can be calibrated accurately through the Reynolds stress of the axial and radial velocity components, and the gradient of the axial velocity in the radial direction. It is found that the mixing length is roughly invariant in the very near wake, then it increases linearly with the downstream distance in the diffusive region. The variation rate of the mixing length in the downstream direction is proposed as a criterion to detect the transition between near wake and transition region of a wind turbine wake. Finally, RANS simulations were performed with the calibrated mixing length model, and a good agreement with the LES simulations is observed.
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    Data-Driven Reduced Order Model for Prediction of Wind Turbine Wakes
    (Institute of Physics Publishing) Iungo, Giacomo V.; Santoni-Ortiz, Christian; Abkar, M.; Porté-Agel, F.; Rotea, Mario A.; Leonardi, Stefano; Iungo, Giacomo V.; Santoni-Ortiz, Christian.; Rotea, Mario A.; Leonardi, Stefano
    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 on high fidelity LES numerical simulations of wind turbines operating under different operational regimes. The ROM enables to capture the main physical processes underpinning the downstream evolution and dynamics of wind turbine wakes. The ROM is then embedded within a Kalman filter in order to produce a time-marching algorithm for prediction of wind turbine wake flows. This data-driven algorithm enables data assimilation of new measurements simultaneously to the wake prediction, which leads to an improved accuracy and a dynamic update of the ROM in presence of emerging coherent wake dynamics observed from new available data. Thanks to its low computational cost, this numerical tool is particularly suitable for real-time applications, control and optimization of large wind farms.

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