Preprints
https://doi.org/10.5194/wes-2026-46
https://doi.org/10.5194/wes-2026-46
26 Feb 2026
 | 26 Feb 2026
Status: this preprint is currently under review for the journal WES.

Computational aerodynamics for soft-wing kite design

Jelle Agatho Wilhelm Poland, Kasper Raphaël G. Masure, Oriol Cayon, and Roland Schmehl

Abstract. Soft-wing kites are morphing, bridled, tensile lifting surfaces used for wind-assisted ship propulsion and airborne wind energy applications. Their swept-back planform, pronounced anhedral, and unconventional leading-edge geometry induce complex aerodynamic behaviour that challenges conventional modelling approaches. For leading-edge inflatable (LEI) kites, pressure-side separation induced by the inflated tubular leading edge renders classical inviscid methods insufficient, thereby necessitating sectional input from higher-fidelity approaches. This study presents and applies a computationally efficient aerodynamic framework to an LEI kite by coupling a vortex step method (VSM) with RANS-derived airfoil polars validated against wind-tunnel measurements. The RANS simulations were used to train a machine-learning surrogate model to facilitate parametric design studies. Applying machine learning to LEI kite aerodynamics is novel, and it achieves R2 > 0.98 across the considered parameter space. Three-dimensional load predictions for the TU Delft V3 LEI kite were evaluated against wind-tunnel data and reference three-dimensional RANS simulations. Within the operational incidence range α ∈ [−1,10]°, the predicted lift and drag agree with measurements to within 9 % and 13 %, respectively. Across this range, the framework reproduces the measured aerodynamic trends more consistently than the reference three-dimensional RANS results, while reducing the computational cost by several orders of magnitude. A rigid-body stability analysis indicated static stability in roll, pitch, and yaw, but limited aerodynamic damping within the quasi-steady model. Parametric analyses revealed inherent trade-offs between aerodynamic efficiency and stability, motivating the adoption of multi-objective optimisation strategies. The validated framework provides high predictive accuracy at low computational cost and forms a foundation for rapid aerodynamic analysis, stability assessment, design optimisation, and aero-structural coupling in the conceptual and preliminary design phases.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share
Jelle Agatho Wilhelm Poland, Kasper Raphaël G. Masure, Oriol Cayon, and Roland Schmehl

Status: open (until 26 Mar 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Jelle Agatho Wilhelm Poland, Kasper Raphaël G. Masure, Oriol Cayon, and Roland Schmehl
Jelle Agatho Wilhelm Poland, Kasper Raphaël G. Masure, Oriol Cayon, and Roland Schmehl
Metrics will be available soon.
Latest update: 26 Feb 2026
Download
Short summary
Soft inflatable kites are promising tools for renewable applications, but their unusual shape makes them difficult to analyse with conventional aerodynamic methods. A fast, accurate computer model is presented based on detailed airflow simulations and wind-tunnel measurements. Aerodynamic forces are predicted within about 10 % of experimental values while requiring far less computing time. It also helps designers balance efficiency and stability, enabling faster, more reliable kite development.
Share
Altmetrics