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.

The study showcases the added value of using structural response measurements in lifetime extension assessments within wind farms. In addition, it answers two of the common questions in different methods of assessment. First, it assesses the applicability of the Frandsen model for estimating conservative waked turbulence in the compact layout of wind farms. Second, it showcases probabilistic extrapolation of short- to mid-term data for long-term site-specific fatigue assessments. 

We studied how air flows around a rigid scale model of a soft kite wing 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 computer simulations. Results confirm key aerodynamic trends such as stall onset and spanwise lift variation, and highlight the influence of struts and recirculation zones on kite aerodynamics.

Kites can generate renewable energy by flying crosswind, but their motion is difficult to describe accurately and efficiently. This study develops a simplified model that captures how kites move through the air using a reduced number of parameters. The model was validated with flight data and provides a clearer understanding of kite motion, supporting the design of improved control strategies and energy generation.

This study demonstrates how kites used to generate wind energy can act as sensors to measure wind conditions and system behaviour. By combining data from existing sensors, such as those measuring position, speed, and forces on the tether, a sensor fusion technique accurately estimates wind conditions and kite performance. This approach can be integrated into control systems to help optimize energy generation and enhance the reliability of these systems under changing wind conditions.