Due to their motion, floating wind lidars overestimate turbulence intensity ( $TI$ ) compared to fixed lidars. We show how the motion of a floating continuous-wave velocity–azimuth display (VAD) scanning lidar in all six degrees of freedom influences the $TI$ estimates, and present a method to compensate for it. The approach presented here uses line-of-sight measurements of the lidar and high-frequency motion data. The compensation algorithm takes into account the changing radial velocity, scanning geometry, and measurement height of the lidar beam as the lidar moves and rotates. It also incorporates a strategy to synchronize lidar and motion data. We test this method with measurement data from a ZX300 mounted on a Fugro SEAWATCH Wind LiDAR Buoy deployed offshore and compare its $TI$ estimates with and without motion compensation to measurements taken by a fixed land-based reference wind lidar of the same type located nearby. Results show that the $TI$ values of the floating lidar without motion compensation are around $50\%$ higher than the reference values. The motion compensation algorithm detects the amount of motion-induced $TI$ and removes it from the measurement data successfully. Motion compensation leads to good agreement between the $TI$ estimates of floating and fixed lidar under all investigated wind conditions and sea states.

Most icing research focuses on the high Reynolds number regime and manned aviation. Information on icing at low Reynolds numbers, as it is encountered by wind turbines and unmanned aerial vehicles, is less available, and few experimental datasets exist that can be used for validation of numerical tools. This study investigated the aerodynamic performance degradation on an S826 airfoil with 3D-printed ice shapes at Reynolds numbers Re = 2 × 10⁵, 4 × 10⁵, and 6 × 10⁵. Three ice geometries were obtained from icing wind tunnel experiments, and an additional three geometries were generated with LEWICE. Experimental measurements of lift, drag, and pressure on the clean and iced airfoils have been conducted in the low-speed wind tunnel at the Norwegian University of Science and Technology. The results showed that the icing performance penalty correlated to the complexity of the ice geometry. The experimental data were compared to computational fluid dynamics (CFD) simulations with the RANS solver FENSAP. Simulations were performed with two turbulence models (Spalart Allmaras and Menter’s k-ω SST). The simulation data showed good fidelity for the clean and streamlined icing cases but had limitations for complex ice shapes and stall.

The spatial development of a turbulent boundary layer (TBL) subjected to freestream turbulence (FST) is investigated experimentally in a water channel for friction Reynolds numbers up to , but that the level of FST and the evolution of the two flows must also be considered.

Electrothermal de-icing systems are a popular approach to protect unmanned aerial vehicles (UAVs) from the performance degradation caused by in-cloud icing. However, their power and energy requirements must be minimized to make these systems viable for small and medium-sized fixed-wing UAVs. Thermal de-icing systems allow intercycle ice accretions and can result in runback icing. Intercycle and runback ice increase the aircraft’s drag, requiring more engine thrust and energy. This study investigates the aerodynamic influence of intercycle and runback ice on a typical UAV wing. Lift and drag coefficients from a wind tunnel campaign and Ansys FENSAP-ICE simulations are compared. Intercycle ice shapes result in a drag increase of approx. 50% for a realistic cruise angle of attack. While dispersed runback ice increases the drag by 30% compared to the clean wing, a spanwise ice ridge can increase the drag by more than 170%. The results highlight that runback ice can significantly influence the drag coefficient. Therefore, it is important to design the de-icing system and its operation sequence to minimize runback ice. Understanding the need to minimize runback ice helps in designing viable de-icing systems for UAVs.

The demand for wind power is rapidly increasing, creating opportunities for wind farm installations in more challenging climates. Cold climate areas, where ice accretion can be an issue, are often sparsely populated and have high wind energy potential. Icing may lead to severely reduced aerodynamic performance and thereby reduced power output. To reach a greater understanding of how icing affects the aerodynamics of a wind turbine blade, three representative icing cases; rime ice, glaze ice and a mixed ice, were defined and investigated experimentally and computationally. Experiments at Re = 1.0 × 10⁵–4.0 × 10⁵ were conducted in the low-speed wind tunnel at NTNU on a two dimensional wing with applied 3D-printed ice shapes, determining lift, drag and surface pressure distributions. Computational results, obtained from the Reynolds Averaged Navier–Stokes fluid dynamics code FENSAP, complement the experiments. Measured and predicted data show a reduction in lift for all icing cases. Most severe is the mixed ice case, with a lift reduction of up to 30 % in the linear lift area, compared to a clean reference airfoil. Computational results show an under-prediction in maximum lift of 7–18 % compared to experimental values. Curvature and tendencies for both lift and drag show good agreement between simulations and experiment.

The placement of a scaled-down Savonius (drag) vertical-axis wind turbine on model buildings is analysed experimentally by the use of turbine performance and flow field measurements in a wind tunnel. The set-up consists of two surface mounted cubes aligned in the flow direction. The turbine is tested at six different streamwise positions – three on each cube. Velocity field measurements are performed with particle image velocimetry along the centreline of the cubes with and without the turbine. The performance at each position is evaluated based on measurements of the produced torque and the rotational speed of the turbine. It is demonstrated that the common practice of estimating wind resources based on the urban flow field without the turbine present is insufficient. The turbine has a substantial influence on the flow field and thus also on the available power. The performance is found to be optimal in the front and centre of the first building with a significant drop-off to the back. This trend is reversed for the downstream building. Holistically, for more generic geometries and varying wind directions, the results suggest the central position on a building is a good compromise.