Articles | Volume 11, issue 4
https://doi.org/10.5194/wes-11-1461-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-1461-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Flow field analysis of a leading-edge inflatable kite rigid-scale model using stereoscopic particle image velocimetry
Jelle Agatho Wilhelm Poland
CORRESPONDING AUTHOR
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, the Netherlands
Erik Fritz
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, the Netherlands
TNO, Kessler Park 1, 2288 GS Rijswijk, the Netherlands
Roland Schmehl
Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, the Netherlands
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We tested a small model of an energy-generating kite in a wind tunnel to study its aerodynamic behaviour. By comparing measurements to computer simulations, we validated the models and identified where they match the real performance and where they fall short. These insights will guide more accurate aerodynamic modelling and inform design choices for kites used in airborne wind energy systems.
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Cited articles
Anderson, J. D.: Fundamentals of aerodynamics, 5th edn., McGraw-Hill Inc., ISBN-10: 0077983467, 2016. a
Barlow, J. B., Rae, W. H., and Pope, A.: Low-Speed Wind Tunnel Testing, 3rd edn., John Wiley & Sons, New York, ISBN: 0471557749, 1999. a
Belloc, H.: Wind Tunnel Investigation of a Rigid Paraglider Reference Wing, J. Aircraft, 52, 703–708, https://doi.org/10.2514/1.C032513, 2015. a
Bensason, D., Sciacchitano, A., and Ferreira, C.: On the wake re-energization of the X-Rotor vertical-axis wind turbine via the vortex-generator strategy, Wind Energ. Sci., 10, 2137–2159, https://doi.org/10.5194/wes-10-2137-2025, 2025. a
Cayon, O., Gaunaa, M., and Schmehl, R.: Fast Aero-Structural Model of a Leading-Edge Inflatable Kite, Energies, 16, 3061, https://doi.org/10.3390/en16073061, 2023. a
Cayon, O., Watson, S., and Schmehl, R.: Kite as a sensor: wind and state estimation in tethered flying systems, Wind Energ. Sci., 10, 2161–2188, https://doi.org/10.5194/wes-10-2161-2025, 2025. a
Damiani, R., Wendt, F., Jonkman, J., and Sicard, J.: A Vortex Step Method for Nonlinear Airfoil Polar Data as Implemented in KiteAeroDyn, in: Proceedings of the AIAA Scitech 2019 Forum, San Diego, CA, USA, https://doi.org/10.2514/6.2019-0804, 2019. a
De Wachter, A.: Deformation and Aerodynamic Performance of a Ram-Air Wing, Master's thesis, Delft University of Technology, https://resolver.tudelft.nl/uuid:786e3395-4590-4755-829f-51283a8df3d2 (last access: 23 April 2026), 2008. a
Desai, S., Schetz, J. A., Kapania, R. K., and Gupta, R.: Wind Tunnel Testing of Tethered Inflatable Wings, J. Aircraft, 0, 1–18, https://doi.org/10.2514/1.C037437, 2024. a
Elfert, C., Göhlich, D., and Schmehl, R.: Measurement of the turning behaviour of tethered membrane wings using automated flight manoeuvres, Wind Energ. Sci., 9, 2261–2282, https://doi.org/10.5194/wes-9-2261-2024, 2024. a
Folkersma, M., Schmehl, R., and Viré, A.: Flow transition modeling on two-dimensional circular leading edge airfoils, Wind Energy, 22, 908–921, https://doi.org/10.1002/we.2329, 2019. a
Fritz, E., Boorsma, K., and Ferreira, C.: Experimental analysis of a horizontal-axis wind turbine with swept blades using PIV data, Wind Energ. Sci., 9, 1617–1629, https://doi.org/10.5194/wes-9-1617-2024, 2024a. a, b
Fritz, E., Ribeiro, A., Boorsma, K., and Ferreira, C.: Aerodynamic characterisation of a thrust-scaled IEA 15 MW wind turbine model: experimental insights using PIV data, Wind Energ. Sci., 9, 1173–1187, https://doi.org/10.5194/wes-9-1173-2024, 2024b. a
Grguric, J. and Quintero, Y.: CODECHECK Certificate 2026-001. CODECHECK Community, Zenodo, https://doi.org/10.5281/zenodo.18890103, 2026. a
Huang, M., Sciacchitano, A., and Ferreira, C.: On the wake deflection of vertical axis wind turbines by pitched blades, Wind Energy, 26, 365–387, https://doi.org/10.1002/we.2803, 2023. a
Hummel, J., Göhlich, D., and Schmehl, R.: Automatic measurement and characterization of the dynamic properties of tethered membrane wings, Wind Energ. Sci., 4, 41–55, https://doi.org/10.5194/wes-4-41-2019, 2019. a
Jeong, J. and Hussain, F.: On the identification of a vortex, J. Fluid Mech., 285, 69–94, https://doi.org/10.1017/S0022112095000462, 1995. a, b
LaVision GmbH: LaVision Imaging Solutions for Flow, Spray, Combustion, and Materials Testing, LaVision GmbH, https://www.lavision.de/en/ (last access: 23 April 2026), 2025. a
Lebesque, G.: Steady-State RANS Simulation of a Leading Edge Inflatable Wing with Chordwise Struts, Master's thesis, Delft University of Technology, https://resolver.tudelft.nl/uuid:f0bc8a1e-088d-49c5-9b77-ebf9e31cf58b (last access: 23 April 2026), 2020. a
LeBlanc, B. and Ferreira, C.: Estimation of blade loads for a variable pitch vertical axis wind turbine from particle image velocimetry, Wind Energy, 25, 313–332, https://doi.org/10.1002/we.2674, 2022. a, b
Leloup, R., Roncin, K., Bles, G., Leroux, J. B., Jochum, C., and Parlier, Y.: Estimation of the lift-to-drag ratio using the lifting line method: Application to a leading edge inflatable kite, chap. 19, in: Airborne Wind Energy, edited by: Ahrens, U., Schmehl, R., and Diehl, M., Springer, 339–355, https://doi.org/10.1007/978-3-642-39965-7_19, 2013. a
Lignarolo, L., Ragni, D., Krishnaswami, C., Chen, Q., Ferreira, C. S., and van Bussel, G.: Experimental Analysis of the Wake of a Horizontal-Axis Wind-Turbine Model, Renew. Energ., 70, 31–46, https://doi.org/10.1016/j.renene.2014.01.020, 2014. a, b
Liu, L. Q., Zhu, J. Y., and Wu, J. Z.: Lift and drag in two-dimensional steady viscous and compressible flow, J. Fluid Mech., 784, 304–341, https://doi.org/10.1017/jfm.2015.584, 2015. a
Noca, F., Shiels, D., and Jeon, D.: A comparison of methods for evaluating time-dependant fluid dynamic forces on bodies, using only velocity fields and their derivatives, J. Fluid. Struct., 13, 551–578, https://doi.org/10.1006/jfls.1999.0219, 1999. a, b, c
Nüst, D. and Eglen, S. J.: CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility, F1000Research, 10, 253, https://doi.org/10.12688/f1000research.51738.2, 2021. a
Oehler, J. and Schmehl, R.: Aerodynamic characterization of a soft kite by in situ flow measurement, Wind Energ. Sci., 4, 1–21, https://doi.org/10.5194/wes-4-1-2019, 2019. a
Poland, J.: Software for the paper: Flow Field Analysis of a Leading-Edge Inflatable Kite Rigid Scale Model Using Stereoscopic Particle Image Velocimetry, Version v0.0.3, Zenodo [code], https://doi.org/10.5281/zenodo.17396075, 2025. a
Poland, J., Fritz, E., and Schmehl, R.: Supporting data set for paper: Flow Field Analysis of a Leading-Edge Inflatable Kite Rigid Scale Model Using Stereoscopic Particle Image Velocimetry, Version 0.0.1, Zenodo [data set], https://doi.org/10.5281/zenodo.17395913, 2025a. a
Poland, J., Schmehl, R., Viré, A., Folkersma, M., and Lebesque, G.: RANS CFD simulations of the TU Delft V3 Kite, Version 0.0.1, Zenodo [data set], https://doi.org/10.5281/zenodo.17395314, 2025b. a
Poland, J. A. W., Lebesque, G., Schmehl, R., and Viré, A.: Surface mesh of the TUDELFT_V3_KITE CAD with edge fillets, Version 0.0.1, Zenodo [data set], https://doi.org/10.5281/zenodo.15316036, 2025c. a
Prasad, A. K.: Stereoscopic particle image velocimetry, Exp. Fluids, 29, 103–116, https://doi.org/10.1007/s003480000143, 2000. a, b
Prasad, A. K. and Adrian, R. J.: Stereoscopic particle image velocimetry applied to liquid flows, Exp. Fluids, 15, 49–60, https://doi.org/10.1007/BF00195595, 1993. a
Raffel, M., Willert, C. E., Scarano, F., Kähler, C. J., Wereley, S. T., and Kompenhans, J.: Particle Image Velocimetry: A Practical Guide, Springer, Berlin, Germany, https://doi.org/10.1007/978-3-319-68852-7, 2018. a, b
Sciacchitano, A. and Wieneke, B.: PIV uncertainty propagation, Meas. Sci. Technol., 27, 084006, https://doi.org/10.1088/0957-0233/27/8/084006, 2016. a, b
Viré, A., Demkowicz, P., Folkersma, M., Roullier, A., and Schmehl, R.: Reynolds-averaged Navier-Stokes simulations of the flow past a leading edge inflatable wing for airborne wind energy applications, J. Phys. Conf. Ser., 1618, 032007, https://doi.org/10.1088/1742-6596/1618/3/032007, 2020. a, b, c
Short summary
We studied how air flows around a rigid-scale model of a soft-wing kite used for harvesting airborne wind energy and wind-assisted ship propulsion. Using a wind tunnel and a laser-based imaging method, we measured the airflow at different angles to compare with simulations. Measured flow field results confirm numerical predictions.
For the measurements with low uncertainty, the derived lift force quantities also correspond well with numerical predictions.
For the measurements with low uncertainty, the derived lift force quantities also correspond well with numerical predictions.
We studied how air flows around a rigid-scale model of a soft-wing kite used for harvesting...
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