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Scaling analysis of the swirling wake of a porous disc: application to wind turbines

Published online by Cambridge University Press:  24 January 2025

E. Fuentes Noriega
Affiliation:
University of Orléans, INSA-CVL, PRISME, EA 4229, 45072 Orléans, France
N. Mazellier*
Affiliation:
University of Orléans, INSA-CVL, PRISME, EA 4229, 45072 Orléans, France
*
Email address for correspondence: [email protected]

Abstract

We report a comprehensive study of the wake of a porous disc, the design of which has been modified to incorporate a swirling motion at an inexpensive cost. The swirl intensity is passively controlled by varying the internal disc geometry, i.e. the pitch angle of the blades. A swirl number is introduced to characterise the competition between the linear (drag) and the azimuthal (swirl) momenta on the wake recovery. Assuming that swirl dominates the near wake and non-equilibrium turbulence theory applies, new scaling laws of the mean wake properties are derived. To assess these theoretical predictions, an in-depth analysis of the aerodynamics of these original porous discs has been conducted experimentally. It is found that, at the early stage of wake recovery, the swirling motion induces a low-pressure core, which controls the mean velocity deficit properties and the onset of self-similarity. The measurements collected in the swirling wake of the porous discs support the new scaling laws proposed in this work. Finally, it is shown that, as far as swirl is injected in the wake, the characteristics of the mean velocity deficit profiles match very well those of both laboratory-scale and real-scale wind-turbine data extracted from the literature. Overall, our results emphasise that, by setting the initial conditions of the wake recovery, swirl is a key ingredient to be taken into account in order to faithfully replicate the mean wake of wind turbines.

JFM classification

Type
JFM Papers
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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References

Alekseenko, S.V., Kuibin, P.A., Okulov, V. Leonidovich, S. & Shtork, S.I. 1999 Helical vortices in swirl flow. J. Fluid Mech. 382, 195–243.CrossRefGoogle Scholar
Anderson, J.D. 2011 Fundamentals of Aerodynamics. McGraw-Hill.Google Scholar
Apostolidis, A., Laval, J.P. & Vassilicos, J.C. 2022 Scalings of turbulence dissipation in space and time for turbulent channel flow. J. Fluid Mech. 946, A41.CrossRefGoogle Scholar
Aubrun, S. 2013 Wind turbine wake properties: comparison between a non-rotating simplified wind turbine model and a rotating model. J. Wind Engng Ind. Aerodyn. 120, 1–8.CrossRefGoogle Scholar
Aubrun, S., et al. 2019 Round-robin tests of porous disc models. J. Phys.: Conf. Ser. 1256, 012004.Google Scholar
Barenblatt, G.I. 1996 Scaling, Self-Similarity, and Intermediate Asymptotics: Dimensional Analysis and Intermediate Asymptotics. Cambridge University Press.CrossRefGoogle Scholar
Bastankhah, M. & Porté-Agel, F. 2014 A new analytical model for wind-turbine wakes. J. Renew. Energy 70, 116–123.CrossRefGoogle Scholar
Bevilaqua, P.M. & Lykoudis, P.S. 1978 Turbulence memory in self-preserving wakes. J. Fluid Mech. 89 (3), 589–606.CrossRefGoogle Scholar
Bortolotti, P., Tarres, H.C., Dykes, K., Merz, K., Sethuraman, L., Verelst, D. & Zahle, F. 2019 IEA wind TCP task 37: systems engineering in wind energy-WP2. Reference wind turbines. National Renewable Energy Laboratory (NREL) report.CrossRefGoogle Scholar
Bossuyt, J., Meneveau, C. & Meyers, J. 2017 Wind farm power fluctuations and spatial sampling of turbulent boundary layers. J. Fluid Mech. 823, 329–344.CrossRefGoogle Scholar
Boudreau, M. & Dumas, G. 2017 Comparison of the wake recovery of the axial-flow and cross-flow turbine concepts. J. Wind Engng Ind. Aerodyn. 165, 137–152.CrossRefGoogle Scholar
Bruun, H.H. 1996 Hot-Wire Anemometry: Principles and Signal Analysis. Oxford University Press.Google Scholar
Camp, E.H. & Cal, R.B. 2016 Mean kinetic energy transport and event classification in a model wind turbine array versus an array of porous disks: energy budget and octant analysis. Phys. Rev. Fluids 1 (4), 044404.CrossRefGoogle Scholar
Cantwell, B.J. 1978 Similarity transformations for the two-dimensional, unsteady, stream-function equation. J. Fluid Mech. 85 (2), 257–271.CrossRefGoogle Scholar
Castro, I.P. 1971 Wake characteristics of two-dimensional perforated plates normal to an air-stream. J. Fluid Mech. 46, 599–609.CrossRefGoogle Scholar
Chamorro, L.P. & Porté-Agel, F. 2010 Effects of thermal stability and incoming boundary-layer flow characteristics on wind-turbine wakes: a wind-tunnel study. Boundary-Layer Meteorol. 136, 515–533.CrossRefGoogle Scholar
Chamorro, L.P. & Porte-Agel, F. 2011 Turbulent flow inside and above a wind farm: a wind-tunnel study. Energies 4, 1919–1936.CrossRefGoogle Scholar
Chen, J.G., Cuvier, C., Foucaut, J.M., Ostovan, Y. & Vassilicos, J.C. 2021 A turbulence dissipation inhomogeneity scaling in the wake of two side-by-side square prisms. J. Fluid Mech. 924, A4.CrossRefGoogle Scholar
Chernykh, G.G., Demenkov, A.G. & Kostomakha, V.A. 2005 Swirling turbulent wake behind a self-propelled body. Intl J. Comput. Fluid Dyn. 19, 399–408.CrossRefGoogle Scholar
Dairay, T., Obligado, M. & Vassilicos, J.C. 2015 Non-equilibrium scaling laws in axisymmetric turbulent wakes. J. Fluid Mech. 781, 166–195.CrossRefGoogle Scholar
Duffman, G.D. 1980 Calibration of triaxial hot-wire probes using a numerical search algorithm. J. Phys. E: Sci. Instrum. 13 (11), 1177.Google Scholar
Dufresne, N.P. 2013 Experimental investigation of the turbulent axisymmetric wake with rotation generated by a wind turbine. PhD thesis, University of New Hampshire, Durham, NH.Google Scholar
Frandsen, S., Barthelmie, R.J., Pryor, S., Rathmann, O., Larsen, S., Højstrup, J. & Thøgersen, M. 2006 Analytical modelling of wind speed deficit in large offshore wind farms. Wind Energy 9, 39–53.CrossRefGoogle Scholar
Gambuzza, S. & Ganapathisubramani, B. 2023 The influence of free stream turbulence on the development of a wind turbine wake. J. Fluid Mech. 963, A19.CrossRefGoogle Scholar
George, W.K. 1989 The self-preservation of turbulent flows and its relation to initial conditions and coherent structures. Adv. Turbul. 3973.Google Scholar
George, W.K. 2013 Lectures in turbulence for the 21st century. Chalmers Univ. Technol. 550.Google Scholar
Goto, S. & Vassilicos, J.C. 2009 The dissipation rate coefficient of turbulence is not universal and depends on the internal stagnation point structure. Phys. Fluids 21 (3), 035104.CrossRefGoogle Scholar
Goto, S. & Vassilicos, J.C. 2015 Energy dissipation and flux laws for unsteady turbulence. Phys. Lett. A 379 (16–17), 1144–1148.CrossRefGoogle Scholar
Helvig, S.J., Vinnes, K.M., Segalini, A., Worth, A.N. & Hearst, R.J. 2021 A comparison of lab-scale free rotating wind turbines and actuator disks. J. Wind Engng Ind. Aerodyn. 209, 104485.CrossRefGoogle Scholar
Holmes, M.J. & Naughton, J.M. 2022 The impact of swirl and wake strength on turbulent axisymmetric wake evolution. Phys. Fluids 34 (9), 095101.CrossRefGoogle Scholar
Howland, M., Bossuyt, J., Martinez-Tossas, L.A., Meyers, J. & Maneveau, C. 2016 Wake structure in actuator disk models of wind turbines in yaw under uniform inflow conditions. J. Renew. Sustain. Energy 8, 043301.CrossRefGoogle Scholar
Jensen, N.O. 1983 A note on wind turbine interaction. Riso-M-2411, Risoe National Laboratory, Roskilde, Denmark, p. 16.Google Scholar
Johansson, P.B.V., George, W.K. & Gourlay, M.J. 2003 Equilibrium similarity, effects of initial conditions and local Reynolds number on the axisymmetric wake. Phys. Fluids 15, 603–617.CrossRefGoogle Scholar
Joukowsky, N.E. 1912 Vortex theory of screw propeller. Trudy Otdeleniya Fizicheskikh Nauk Obshchestva Lubitelei Estestvoznaniya (in Russian) 16 (1).Google Scholar
Kallio, G.A. & Stock, D.E. 1992 Interaction of electrostatic and fluid dynamic fields in wire–plate electrostatic precipitators. J. Fluid Mech. 240, 133–166.CrossRefGoogle Scholar
Lee, J., Kim, Y., Khosronejad, A. & Kang, S. 2020 Experimental study of the wake characteristics of an axial flow hydrokinetic turbine at different tip speed ratios. Ocean Engng 196, 106777.CrossRefGoogle Scholar
Li, H., Zhao, Y., Liu, J. & Carmeliet, J. 2021 Physics-based stitching of multi-FOV PIV measurements for urban wind fields. Build. Environ. 205, 108306.CrossRefGoogle Scholar
Liepmann, H.W. & Robinson, M.S. 1952 Counting methods and equipment for mean-value measurements in turbulence research. NACA Technical Note TN 3037. National Advisory Committee for Aeronautics (NACA).Google Scholar
Lignarolo, L.E.M., Ragni, D. & Ferreira, C.J. 2016 Experimental comparison of a wind-turbine and of an actuator-disc near wake. J. Renew. Sustain. Energy 8, 023301.CrossRefGoogle Scholar
Lingkan, E.H. & Buxton, O. 2023 An assessment of the scalings for the streamwise evolution of turbulent quantities in wakes produced by porous objects. Renew. Energy 209, 1–9.CrossRefGoogle Scholar
Lobasov, A.S., Alekseenko, S.V., Markovich, D.M. & Dulin, V.M. 2020 Mass and momentum transport in the near field of swirling turbulent jets. Effect of swirl rate. Intl J. Heat Fluid Flow 83, 108539.CrossRefGoogle Scholar
Masri, A.R., Kalt, P. & Barlow, R.S. 2004 The compositional structure of swirl-stabilised turbulent nonpremixed flames. Combust. Flame 137, 1–37.CrossRefGoogle Scholar
Mazellier, N. & Vassilicos, J.C. 2008 The turbulence dissipation constant is not universal because of its universal dependence on large-scale flow topology. Phys. Fluids 20, 015101.CrossRefGoogle Scholar
Mohebi, M., Wood, D. & Martinuzzi, R.J. 2017 The turbulence structure of the wake of a thin flat plate at post-stall angles of attack. Exp. Fluids 58, 1–18.CrossRefGoogle Scholar
Moisy, F., Morize, C., Rabaud, M. & Sommeria, J. 2011 Decay laws, anisotropy and cyclone–anticyclone asymmetry in decaying rotating turbulence. J. Fluid Mech. 666, 5–35.CrossRefGoogle Scholar
Mora, D.O. & Obligado, M. 2020 Estimating the integral length scale on turbulent flows from the zero crossings of the longitudinal velocity fluctuation. Exp. Fluids 61, 199.CrossRefGoogle Scholar
Mora, D.O., Pladellorens, E.M., Turró, P.R., Lagauzere, M. & Obligado, M. 2019 Energy cascades in active-grid-generated turbulent flows. Phys. Rev. Fluids 4 (10), 104601.CrossRefGoogle Scholar
Morris, C.E., O'doherty, D.M., Mason-Jones, A. & O'Doherty, T. 2016 Evaluation of the swirl characteristics of a tidal stream turbine wake. Intl J. Mar. Energy 14, 198–214.CrossRefGoogle Scholar
Nakayama, Y. 1988 Visualized Flow: Fluid Motion in Basic and Engineering Situations Revealed by Flow Visualization. Pergamon Press.Google Scholar
Nedic, J. 2013 Fractal-generated wakes. PhD thesis, Imperial College of London, London, UK.Google Scholar
Neunaber, I., Peinke, J. & Obligado, M. 2021 Investigation of the dissipation in the wake of a wind turbine array. Wind Energy Sci. Discuss. 2021, 1–27.Google Scholar
Neunaber, I., Peinke, J. & Obligado, M. 2022 Application of the Townsend–George theory for free shear flows to single and double wind turbine wakes–a wind tunnel study. Wind Energy Sci. 7, 201–219.CrossRefGoogle Scholar
Oberleithner, K., Sieber, M., Nayeri, C.N., Paschereit, C.O., Petz, C., Hege, H.C., Noack, B.R. & Wygnanski, I. 2011 Three-dimensional coherent structures in a swirling jet undergoing vortex breakdown: stability analysis and empirical mode construction. J. Fluid Mech. 679, 383–414.CrossRefGoogle Scholar
Okulov, V.L., Sørensen, J.N. & Wood, D.H. 2015 The rotor theories by Professor Joukowsky: vortex theories. Prog. Aerosp. Sci. 73, 19–46.CrossRefGoogle Scholar
Pope, S.B. 2000 Turbulent Flows. Cambridge University Press.Google Scholar
Porté-Agel, F., Bastankhah, M. & Shamsoddin, S. 2020 Wind-turbine and wind-farm flows: a review. Boundary-Layer Meteorol. 174 (1), 159.CrossRefGoogle ScholarPubMed
Raffel, M., Willert, C.E. & Kompenhans, J. 2007 Particle Image Velocimetry: A Practical Guide. Springer Science & Business Media.CrossRefGoogle Scholar
Rankine, W.J.M. 1865 On the mechanical principles of the action of propellers. Trans. Inst. Nav. Arch. 6, 13–39.Google Scholar
Reynolds, A.J. 1962 Similarity in swirling wakes and jets. J. Fluid Mech. 14 (2), 241–243.CrossRefGoogle Scholar
Rice, S.O. 1944 Mathematical analysis of random noise. Bell Syst. Tech. J. 23 (3), 282–332.CrossRefGoogle Scholar
Rice, S.O. 1945 Mathematical analysis of random noise. Bell Syst. Tech. J. 24 (1), 46–156.CrossRefGoogle Scholar
Schliffke, B. 2022 Experimental characterisation of the far wake of a modelled floating wind turbine as a function of incoming swell. PhD thesis, École centrale de Nantes.Google Scholar
Schutz, W.M. & Naughton, J.W. 2022 Wake rotation impacts on wake decay. J. Phys.: Conf. Ser. 2265.Google Scholar
Seoud, R.E. & Vassilicos, J.C. 2007 Dissipation and decay of fractal-generated turbulence. Phys. Fluids 19 (10), 105108.CrossRefGoogle Scholar
Sforza, P.M., Sheerin, P. & Smorto, M. 1981 Three-dimensional wakes of simulated wind turbines. AIAA J. 19 (9), 1101–1107.CrossRefGoogle Scholar
Shanmughan, R., Passaggia, P.Y., Mazellier, N. & Kourta, A. 2020 Optimal pressure reconstruction based on planar particle image velocimetry and sparse sensor measurements. Exp. Fluids 61, 229.CrossRefGoogle Scholar
Shiri, A. 2010 Turbulence measurements in a natural convection boundary layer and a swirling jet. PhD thesis, Chalmers University of Technology, Göteborg, Sweden.Google Scholar
Shiri, A., George, W.K. & Naughton, J.W. 2008 Experimental study of the far field of incompressible swirling jets. AIAA J. 46, 2002–2009.CrossRefGoogle Scholar
Sreenivasan, K.R., Prabhu, A. & Narasimha, R. 1983 Zero-crossings in turbulent signals. J. Fluid Mech. 137, 251–272.CrossRefGoogle Scholar
Steiros, K. & Hultmark, M. 2018 Drag on flat plates of arbitrary porosity. J. Fluid Mech. 853, R3.CrossRefGoogle Scholar
Stevens, R.J.A.M., Martínez-Tossas, L.A. & Meneveau, C. 2018 Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments. Renew. Energy 116, 470–478.CrossRefGoogle Scholar
Tennekes, H. & Lumley, J.L. 1972 A First Course in Turbulence. MIT Press.CrossRefGoogle Scholar
Townsend, A.A. 1976 The Structure of Turbulent Shear Flow, 2nd edn. Cambridge University Press.Google Scholar
Van-Kuik, G.A.M., Sørensen, J., Nørkær, J. & Okulov, V.L. 2015 Rotor theories by Professor Joukowsky: momentum theories. Prog. Aerosp. Sci. 73, 1–18.CrossRefGoogle Scholar
Vassilicos, J.C. 2015 Dissipation in turbulent flows. Annu. Rev. Fluid Mech. 47, 95114.CrossRefGoogle Scholar
Vincent, J.H. 2007 Aerosol Sampling: Science, Standards, Instrumentation and Applications. John Wiley & Sons.CrossRefGoogle Scholar
Vinnes, M.K. 2023 The actuator disk as a wind turbine model: An experimental assessment of the fluid dynamics. PhD thesis, Norwegian University of Science and Technology, Trondheim, Norway.Google Scholar
Vinnes, M.K., Gambuzza, S., Ganapathisubramani, B. & Hearst, R.J. 2022 The far wake of porous disks and a model wind turbine: similarities and differences assessed by hot-wire anemometry. J. Renew. Sustain. Energy 14, 023304.CrossRefGoogle Scholar
Wieneke, B. 2015 PIV uncertainty quantification from correlation statistics. Meas. Sci. Technol. 26.CrossRefGoogle Scholar
Wosnik, M. & Dufresne, N. 2013 Experimental investigation and similarity solution of the axisymmetric turbulent wake with rotation. In Fundamental Issues and Perspectives in Fluid Mechanics, ASME 2013 Fluids Engineering Division Summer Meeting, vol. 1B. ASME.CrossRefGoogle Scholar
Wu, Y.T. & Porté-Agel, F. 2012 Atmospheric turbulence effects on wind-turbine wakes: an LES study. Energies 5, 5340–5362.CrossRefGoogle Scholar
Wu, Y.T. & Porté-Agel, F. 2013 Simulation of turbulent flow inside and above wind farms: model validation and layout effects. Boundary-Layer Meteorol. 146, 181–205.CrossRefGoogle Scholar
Wygnanski, I., Champagne, F. & Marasli, B. 1986 On the large-scale structures in two-dimensional, small-deficit, turbulent wakes. J. Fluid Mech. 168, 31–71.CrossRefGoogle Scholar