Saint Anthony Falls Laboratory

Minneapolis, MN, United States

Saint Anthony Falls Laboratory

Minneapolis, MN, United States
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Kumar S.S.,Saint Anthony Falls Laboratory | Kumar S.S.,University of Minnesota | Karn A.,Saint Anthony Falls Laboratory | Arndt R.E.A.,Saint Anthony Falls Laboratory | And 2 more authors.
Experiments in Fluids | Year: 2017

Understanding the fundamental physical process involved in drop impacts is important for a variety of engineering and scientific applications. Despite exhaustive research efforts on the dynamics of drop morphology upon impact, very few studies investigate the fluid dynamics induced within a drop upon impact. This study employs planar particle image velocimetry (PIV) with fluorescent particles to quantify the internal flow field of a drop impact on a solid surface. The image distortion caused by the curved liquid–air interface at the drop boundary is corrected using a ray-tracing algorithm. PIV analysis using the corrected images has yielded interesting insights into the flow initiated within a drop upon impact. Depending on the pre-impact conditions, characterized by impact number, different vortex modes are observed in the recoil phase of the drop impact. Further, the strength of these vortices and the kinetic energy of the internal flow field have been quantified. Our studies show a consistent negative power law correlation between vortex strength, internal kinetic energy and the impact number. © 2017, Springer-Verlag Berlin Heidelberg.


Toloui M.,Saint Anthony Falls Laboratory | Toloui M.,University of Minnesota | Riley S.,Saint Anthony Falls Laboratory | Riley S.,University of Minnesota | And 9 more authors.
Experiments in Fluids | Year: 2014

We present an implementation of super-large-scale particle image velocimetry (SLPIV) to characterize spatially the turbulent atmospheric boundary layer using natural snowfall as flow tracers. The SLPIV technique achieves a measurement area of ~22 m × 52 m, up to 56 m above the ground, with a spatial resolution of ~0.34 m. The traceability of snow particles is estimated based on their settling velocity obtained from the wall-normal component of SLPIV velocity measurements. The results are validated using coincident measurements from sonic anemometers on a meteorological tower situated in close proximity to the SLPIV sampling area. A contrast of the mean velocity and the streamwise Reynolds stress component obtained from the two techniques shows less than 3 and 12 % difference, respectively. Additionally, the turbulent energy spectra measured by SLPIV show a similar inertial subrange and trends when compared to those measured by the sonic anemometers. © 2014 Springer-Verlag Berlin Heidelberg.


Hong J.,Saint Anthony Falls Laboratory | Hong J.,University of Minnesota | Guala M.,Saint Anthony Falls Laboratory | Guala M.,University of Minnesota | And 4 more authors.
Journal of Physics: Conference Series | Year: 2014

Despite major research efforts, the interaction of the atmospheric boundary layer with turbines and multi-turbine arrays at utility scale remains poorly understood today. This lack of knowledge stems from the limited number of utility-scale research facilities and a number of technical challenges associated with obtaining high-resolution measurements at field scale. We review recent results obtained at the University of Minnesota utility-scale wind energy research station (the EOLOS facility), which is comprised of a 130 m tall meteorological tower and a fully instrumented 2.5MW Clipper Liberty C96 wind turbine. The results address three major areas: 1) The detailed characterization of the wake structures at a scale of 36×36 m2 using a novel super-large-scale particle image velocimetry based on natural snowflakes, including the rich tip vortex dynamics and their correlation with turbine operations, control, and performance; 2) The use of a WindCube Lidar profiler to investigate how wind at various elevations influences turbine power fluctuation and elucidate the role of wind gusts on individual blade loading; and 3) The systematic quantification of the interaction between the turbine instantaneous power output and tower foundation strain with the incoming flow turbulence, which is measured from the meteorological tower. © Published under licence by IOP Publishing Ltd.


Hong J.,Saint Anthony Falls Laboratory | Hong J.,University of Minnesota | Toloui M.,Saint Anthony Falls Laboratory | Toloui M.,University of Minnesota | And 10 more authors.
Nature Communications | Year: 2014

To improve power production and structural reliability of wind turbines, there is a pressing need to understand how turbines interact with the atmospheric boundary layer. However, experimental techniques capable of quantifying or even qualitatively visualizing the large-scale turbulent flow structures around full-scale turbines do not exist today. Here we use snowflakes from a winter snowstorm as flow tracers to obtain velocity fields downwind of a 2.5-MW wind turbine in a sampling area of ∼n36 × 36 m 2. The spatial and temporal resolutions of the measurements are sufficiently high to quantify the evolution of blade-generated coherent motions, such as the tip and trailing sheet vortices, identify their instability mechanisms and correlate them with turbine operation, control and performance. Our experiment provides an unprecedented in situ characterization of flow structures around utility-scale turbines, and yields significant insights into the Reynolds number similarity issues presented in wind energy applications. © 2014 Macmillan Publishers Limited. All rights reserved.


Annoni J.,University of Minnesota | Howardy K.,University of Minnesota | Howardy K.,Saint Anthony Falls Laboratory | Seilerz P.,University of Minnesota | Gualax M.,University of Minnesota
33rd Wind Energy Symposium | Year: 2015

Individual wind turbines, whether stand alone or in a wind farms, typically operate to maximize their own production without considering the impact of wake effects on nearby turbines. Investigation into wind turbine interaction within a wind farm has the potential to increase total power and reduce structural loads by properly coordinating the individual turbines that comprise the wind farm. To effectively design and analyze such coordinated controllers requires turbine wake models of sufficient accuracy. This paper develops a dynamic model, derived from experiments, to describe the aerodynamic interactions between two model turbines in a wind tunnel. Experiments were conducted in the atmospheric boundary layer wind tunnel at the Saint Anthony Falls Laboratory at the University of Minnesota and were performed by varying the voltage input to the upwind turbine. Particle Image Velocimetry (PIV) and voltage measurements were used to capture the physical evolution of the interactions of the turbines as well as measure the response of the turbines, respectively. A transfer function model relating the upwind turbine input to downwind turbine output was identified from the experimental data. Following a few modifications to the current setup, future work will include performing wind farm control using the dynamic model presented in this paper. © 2015, American Institute of Aeronautics and Astronautics Inc. All rights reserved.

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