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Coherent dynamics in the rotor tip shear layer of utility-scale wind turbines

Published online by Cambridge University Press:  08 September 2016

Xiaolei Yang ,
Jiarong Hong ,
Matthew Barone  and
Fotis Sotiropoulos
Xiaolei Yang
Affiliation:
St. Anthony Falls Laboratory, University of Minnesota, 2 Third Avenue SE, Minneapolis, MN 55414, USA
Jiarong Hong
Affiliation:
St. Anthony Falls Laboratory, University of Minnesota, 2 Third Avenue SE, Minneapolis, MN 55414, USA Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, MN 55455, USA
Matthew Barone
Affiliation:
Sandia National Laboratories, Albuquerque, NM 87185 and Livermore, CA 94550, USA
Fotis Sotiropoulos*
Affiliation:
Department of Civil Engineering, College of Engineering and Applied Sciences, Stony Brook University, Stony Brook, NY 11794, USA
*
†Email address for correspondence: fotis.sotiropoulos@stonybrook.edu
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Abstract

Recent field experiments conducted in the near wake (up to 0.5 rotor diameters downwind of the rotor) of a Clipper Liberty C96 2.5 MW wind turbine using snow-based super-large-scale particle image velocimetry (SLPIV) (Hong et al., Nat. Commun., vol. 5, 2014, 4216) were successful in visualizing tip vortex cores as areas devoid of snowflakes. The so-visualized snow voids, however, suggested tip vortex cores of complex shape consisting of circular cores with distinct elongated comet-like tails. We employ large-eddy simulation (LES) to elucidate the structure and dynamics of the complex tip vortices identified experimentally. We show that the LES, with inflow conditions representing as closely as possible the state of the flow approaching the turbine when the SLPIV experiments were carried out, reproduce vortex cores in good qualitative agreement with the SLPIV results, essentially capturing all vortex core patterns observed in the field in the tip shear layer. The computed results show that the visualized vortex patterns are formed by the tip vortices and a second set of counter-rotating spiral vortices intertwined with the tip vortices. To probe the dependence of these newly uncovered coherent flow structures on turbine design, size and approach flow conditions, we carry out LES for three additional turbines: (i) the Scaled Wind Farm Technology (SWiFT) turbine developed by Sandia National Laboratories in Lubbock, TX, USA; (ii) the wind turbine developed for the European collaborative MEXICO (Model Experiments in Controlled Conditions) project; and (iii) the model turbine presented in the paper by Lignarolo et al. (J. Fluid Mech., vol. 781, 2015, pp. 467–493), and the Clipper turbine under varying inflow turbulence conditions. We show that similar counter-rotating vortex structures as those observed for the Clipper turbine are also observed for the SWiFT, MEXICO and model wind turbines. However, the strength of the counter-rotating vortices relative to that of the tip vortices from the model turbine is significantly weaker. We also show that incoming flows with low level turbulence attenuate the elongation of the tip and counter-rotating vortices. Sufficiently high turbulence levels in the incoming flow, on the other hand, tend to break up the coherence of spiral vortices in the near wake. To elucidate the physical mechanism that gives rise to such rich coherent dynamics we examine the stability of the turbine tip shear layer using the theory proposed by Leibovich & Stewartson (J. Fluid Mech., vol. 126, 1983, pp. 335–356). We show that for all simulated cases the theory consistently indicates the flow to be unstable exactly in the region where counter-rotating spirals emerge. We thus postulate that centrifugal instability of the rotating turbine tip shear layer is a possible mechanism for explaining the phenomena we have uncovered herein.

JFM classification

Turbulent Flows: Shear layer turbulence Vortex Flows: Vortex instability Wakes/Jets: Wakes
Type
Papers
Information
Journal of Fluid Mechanics , Volume 804 , 10 October 2016 , pp. 90 - 115
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Copyright
© 2016 Cambridge University Press 

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References

Barone, M. & White, J.2011 DOE/SNL-TTU scaled wind farm technology facility: Research opportunities for study of turbine-turbine interaction. SANDIA Rep. SAND2011-6522. Sandia National Laboratories.CrossRefGoogle Scholar
Berg, J., Bryant, J., LeBlanc, B., Maniaci, D., Naughton, B., Paquette, J., Resor, B., White, J. & Kroeker, D.2014 Scaled wind farm technology facility overview. In 32nd ASME Wind Energy Symposium, AIAA Paper 2014-1088. American Institute of Aeronautics and Astronautics.Google Scholar
Chamorro, L. P., Hill, C., Morton, S., Ellis, C., Arndt, R. E. A. & Sotiropoulos, F. 2013a On the interaction between a turbulent open channel flow and an axial-flow turbine. J. Fluid Mech. 716, 658–670.CrossRefGoogle Scholar
Chamorro, L. P., Hill, C., Neary, V. S., Gunawan, B., Arndt, R. E. A. & Sotiropoulos, F. 2015a Effects of energetic coherent motions on the power and wake of an axial-flow turbine. Phys. Fluids 27 (5), 055104.CrossRefGoogle Scholar
Chamorro, L. P., Lee, S.-J., Olsen, D., Milliren, C., Marr, J., Arndt, R. E. A. & Sotiropoulos, F. 2015b Turbulence effects on a full-scale 2.5 mw horizontal-axis wind turbine under neutrally stratified conditions. Wind Energy 18 (2), 339–349.CrossRefGoogle Scholar
Chamorro, L. P., Troolin, D. R., Lee, S.-J., Arndt, R. E. A. & Sotiropoulos, F. 2013b Three-dimensional flow visualization in the wake of a miniature axial-flow hydrokinetic turbine. Exp. Fluids 54 (2), 1–12.Google Scholar
Gallaire, F. & Chomaz, J. 2003 Mode selection in swirling jet experiments: a linear stability analysis. J. Fluid Mech. 494, 223–253.Google Scholar
Germano, M., Piomelli, U., Moin, P. & Cabot, W. H. 1991 A dynamic subgrid-scale eddy viscosity model. Phys. Fluids A 3 (7), 1760–1765.CrossRefGoogle Scholar
Hong, J., Toloui, M., Chamorro, L. P., Guala, M., Howard, K., Riley, S., Tucker, J. & Sotiropoulos, F. 2014 Natural snowfall reveals large-scale flow structures in the wake of a 25-mw wind turbine. Nat. Commun. 5, 4216.Google Scholar
Howard, K. B., Hu, J. S., Chamorro, L. P. & Guala, M. 2015 Characterizing the response of a wind turbine model under complex inflow conditions. Wind Energy 18 (4), 729–743.Google Scholar
Howard, K. B. & Guala, M. 2016 Upwind preview to a horizontal axis wind turbine: a wind tunnel and field-scale study. Wind Energy 19, 1371–1389.Google Scholar
Hu, H., Yang, Z. & Sarkar, P. 2012 Dynamic wind loads and wake characteristics of a wind turbine model in an atmospheric boundary layer wind. Exp. Fluids 52 (5), 1277–1294.CrossRefGoogle Scholar
Hussain, A. K. M. 1986 Coherent structures and turbulence. J. Fluid Mech. 173, 303–356.Google Scholar
Iungo, G. V., Viola, F., Camarri, S., Porté-Agel, F. & Gallaire, F. 2013 Linear stability analysis of wind turbine wakes performed on wind tunnel measurements. J. Fluid Mech. 737, 499–526.Google Scholar
Ivanell, S., Mikkelsen, R., Sørensen, J. N. & Henningson, D. 2010 Stability analysis of the tip vortices of a wind turbine. Wind Energy 13 (8), 705–715.CrossRefGoogle Scholar
Jeong, J. & Hussain, F. 1995 On the identification of a vortex. J. Fluid Mech. 285, 69–94.Google Scholar
Kang, S., Lightbody, A., Hill, C. & Sotiropoulos, F. 2011 High-resolution numerical simulation of turbulence in natural waterways. Adv. Water Resour. 34, 98–113.Google Scholar
Kelley, C. L., Maniaci, D. C. & Resor, B. R.2015 Horizontal-axis wind turbine wake sensitivity to different blade load distributions. In AIAA SciTech, 33rd Wind Energy Symposium, AIAA Paper 2015-0490. American Institute of Aeronautics and Astronautics.Google Scholar
Leibovich, S. & Stewartson, K. 1983 A sufficient condition for the instability of columnar vortices. J. Fluid Mech. 126, 335–356.CrossRefGoogle Scholar
Lignarolo, L. E. M., Ragni, D., Krishnaswami, C., Chen, Q., Ferreira, C. J. S. & Van Bussel, G. J. W. 2014 Experimental analysis of the wake of a horizontal-axis wind-turbine model. Renew. Energy 70, 31–46.Google Scholar
Lignarolo, L. E. M., Ragni, D., Scarano, F., Ferreira, C. J. S. & van Bussel, G. J. W. 2015 Tip-vortex instability and turbulent mixing in wind-turbine wakes. J. Fluid Mech. 781, 467–493.CrossRefGoogle Scholar
Loiseleux, T., Chomaz, J. M. & Huerre, P. 1998 The effect of swirl on jets and wakes: linear instability of the rankine vortex with axial flow. Phys. Fluids 10 (5), 1120–1134.CrossRefGoogle Scholar
Loiseleux, T., Delbende, I. & Huerre, P. 2000 Absolute and convective instabilities of a swirling jet/wake shear layer. Phys. Fluids 12 (2), 375–380.CrossRefGoogle Scholar
Mann, J. 1998 Wind field simulation. Probab. Engng Mech. 13 (4), 269–282.Google Scholar
Martin, J. E. & Meiburg, E. 1996 Nonlinear axisymmetric and three-dimensional vorticity dynamics in a swirling jet model. Phys. Fluids 8 (7), 1917–1928.Google Scholar
Nilsson, K., Shen, W. Z., Sørensen, J. N., Breton, S.-P. & Ivanell, S. 2015 Validation of the actuator line method using near wake measurements of the mexico rotor. Wind Energy 18 (3), 499–514.Google Scholar
Okulov, V. L. & Sørensen, J. N. 2007 Stability of helical tip vortices in a rotor far wake. J. Fluid Mech. 576, 1–25.Google Scholar
Peura, M. & Iivarinen, J. 1997 Efficiency of simple shape descriptors. In Advances in Visual Form Analysis: Proceedings of the Third International Workshop in Visual Form, Capri, Italy 28–30 May 1997 (ed. Arcelli, C., Cordella, L. P. & Di Di Baja, G. S.), pp. 443–451.Google Scholar
Rayleigh, Lord 1917 On the dynamics of revolving fluids. Proc. R. Soc. Lond. A 93 (648), 148–154.Google Scholar
Sarmast, S., Dadfar, R., Mikkelsen, R. F., Schlatter, P., Ivanell, S., Sørensen, J. N. & Henningson, D. S. 2014 Mutual inductance instability of the tip vortices behind a wind turbine. J. Fluid Mech. 755, 705–731.Google Scholar
Schepers, J. G. & Snel, H.2007 Model experiments in controlled conditions. ECN Report: ECN-E-07-042.Google Scholar
Shen, W. Z., Zhang, J. H. & Sørensen, J. N. 2009 The actuator surface model: a new Navier–Stokes based model for rotor computations. J. Sol. Energy Engng 131 (1), 011002.Google Scholar
Shen, W. Z., Zhu, W. J. & Sørensen, J. N. 2012 Actuator line/Navier–Stokes computations for the mexico rotor: comparison with detailed measurements. Wind Energy 15 (5), 811–825.CrossRefGoogle Scholar
Sherry, M., Nemes, A., Jacono, D. L., Blackburn, H. M. & Sheridan, J. 2013 The interaction of helical tip and root vortices in a wind turbine wake. Phys. Fluids 25 (11), 117102.Google Scholar
Snel, H., Schepers, J. G. & Montgomerie, B. 2007 The mexico project (model experiments in controlled conditions): the database and first results of data processing and interpretation. J. Phys. Conf. Ser. 75, 012014.Google Scholar
Sørensen, J. N. & Shen, W. Z. 2002 Numerical modeling of wind turbine wakes. J. Fluids Engng 124, 393–399.Google Scholar
Wang, Z., Ozbay, A., Tian, W., Sharma, A. & Hu, H.2015 An experimental investigation on the wake characteristics behind a novel twin-rotor wind turbine. In AIAA SciTech, 33rd Wind Energy Symposium, AIAA Paper 2015-1663. American Institute of Aeronautics and Astronautics.Google Scholar
Yang, X., Annoni, J., Seiler, P. & Sotiropoulos, F. 2014a Modeling the effect of control on the wake of a utility-scale turbine via large-eddy simulation. J. Phys. Conf. Ser. 524, f012180.CrossRefGoogle Scholar
Yang, X., Boomsma, A., Barone, M. & Sotiropoulos, F. 2014b Wind turbine wake interactions at field scale: an les study of the swift facility. J. Phys. Conf. Ser. 524, 012139.CrossRefGoogle Scholar
Yang, X., Boomsma, A., Sotiropoulos, F., Kelley, C. L., Maniaci, D. C. & Resor, B. R.2015a Effects of spanwise blade load distribution on wind turbine wake evolution. In AIAA SciTech, 33rd Wind Energy Symposium, AIAA Paper 2015-0492. American Institute of Aeronautics and Astronautics.Google Scholar
Yang, X., Sotiropoulos, F., Conzemius, R. J., Wachtler, J. N. & Strong, M. B. 2015b Large-eddy simulation of turbulent flow past wind turbines/farms: the virtual wind simulator (VWIS). Wind Energy 18 (12), 2025–2045.Google Scholar
Yang, X., Zhang, X., Li, Z. & He, G.-W. 2009 A smoothing technique for discrete delta functions with application to immersed boundary method in moving boundary simulations. J. Comput. Phys. 228, 7821–7836.Google Scholar
Zhang, W., Markfort, C. D. & Porté-Agel, F. 2013 Wind-turbine wakes in a convective boundary layer: a wind-tunnel study. Boundary-Layer Meteorol. 146 (2), 161–179.CrossRefGoogle Scholar