Tommaso Massai

Design and calibration of an innovative ultrasonic, arduino based anemometer

A precise estimation of wind intensity and direction is important for many applications. Authors, thanks to a consolidated experience in marine robotics, are building a sail propelled marine drone for a sustainable monitoring of wide sea areas. In particular, sail propulsion assures a near to infinite autonomy since limited energy demand of on board electronic can be assured by renewable sources such as solar cells. However, to correctly manage a sail system, a correct estimation of wind intensity and its direction is essential. Conventional anemometers make use of delicate mechanical moving parts, are therefore not suitable to work autonomously in difficult environments such as the marine one. Commercial ultrasonic anemometers represent a valid alternative but their cost, weight and size need to be optimized for the proposed application which is a cheap, light and relatively small drone. In this work the authors redesigned both acoustic and electronic system to meet the required specifications. Innovations have been suggested in terms of materials, components and introducing a smart measurement algorithm that allowed the authors to simplify the design, construction and calibration of the instrument. Finally, the system has been tested and calibrated in a wind tunnel, introducing a simple and effective calibration algorithm able to drastically reject disturbances arising from interference between mechanical system and the wind flow under measurement.

Combined experimental and numerical study on the near wake of a Darrieus VAWT under turbulent flows

Small Darrieus Vertical-Axis Wind Turbines (VAWTs) are presently seen as a relevant research topic for the wind energy community, since they are thought to perform better than horizontal-axis rotors in the complex and highly-turbulent flow typical of the urban environment. Indeed, a preliminary wind tunnel test campaign on a H-Darrieus VAWT showed a significant increase of the performance for high turbulence levels. The present study analyses in detail the near wake of the turbine in the same turbulent conditions, enabling a better insight on the reasons of this power increase, and on the means to take advantage of it. Near-wake measurements are also benchmarked with a CFD simulation of the entire wake, in order to match the experimental wake measurements with the detachment of flow structures observed in CFD simulations. By doing so, a deeper and useful insight on the reasons why VAWTs perform better in turbulent environments is gained. Nomenclature At = Turbine frontal area (m) b = Grid bar width (m) c = Turbine blade chord (m) CP = Power coefficient (-) Iu = Intensity of turbulence in wind direction (-) Iper = Periodic unsteadiness (-) Lux = Integral length scale of turbulence in wind direction (m) M = Grid mesh size (m) U = Wind speed (m/s) R = Rotor radius (m) P = Turbine mechanical power (W) Re = Reynolds number (-) x = Longitudinal distance from the rotor axis (m) y = Transversal distance from the rotor axis (m) y+ = Dimensionless wall distance (-) λ = Tip-speed ratio (-)