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Leonardo da Vinci’s aerial screw finds application in wind power industry

26.12.2025
in News, Science and Technology
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Leonardo da Vinci’s aerial screw finds application in wind power industry
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Scientists from the Sapienza University of Rome jointly with the French engineering company Aircrafted have developed and experimentally tested a new vertical wind turbine design. This rotor is named RoDaVi, short for Rotor da Vinci, as its shape is inspired by Leonardo da Vinci’s aerial screw, which is considered the prototype for the modern helicopter. Unlike conventional installations, the new turbine was initially conceived as a hybrid aerodynamic design: it uses a lift characteristic of bladed propeller-type wind systems and a drag force found in Pelton designs. This hybrid is especially well-suited to urban environments and areas with a complex terrain, where wind is unstable, frequently changes direction and rarely reaches the speeds optimal for large horizontal turbines.

Conventional designs of vertical wind turbines have historically developed in two directions, each with its own limitations. Savonius turbines, which are highly reliable and can start even in light winds, have low efficiency, which results in a significant loss of flow energy. Darrieus turbines, on the other hand, can operate at higher efficiency but have poor self-starting properties and require more severe wind conditions. From its inception, the RoDaVi concept was always meant to combine RoDaVi concept was meant to combine these advantages: to ensure reliable starting at low wind speeds while also increasing efficiency in the operating range without complicating the design with additional rotors or auxiliary systems.

In order to test this concept, the researchers built a scale model of the turbine and conducted a series of wind tunnel tests. The experimental program was designed to evaluate not only the final energy indicators but also the physical causes of their fluctuations. On the one hand, the scientists measured the mechanical and electrical power, torque and rotor speed. On the other hand, they used particle image velocimetry (PIV), a modern optical flow visualization method, to record the air velocity field near the rotating turbine and analyze the structure of its wake. This approach allowed them to establish a direct link between the aerodynamic behavior of the turbine and its energy efficiency.

The experimental results showed that the key parameter for RoDaVi is the inclination angle of the rotation axis relative to the incoming flow. The turbine demonstrates its best performance in the inclination range of 30°C to 40°C. In these conditions, the power factor (the main indicator of wind turbine efficiency) reaches a value of about 0.34, which is roughly 25% higher than that of the reference Savonius turbine tested under the same conditions. Moreover, its useful operating range proved to be significantly wider: RoDaVi maintains efficiency at rotation speeds almost 2.5 times higher than those typical of classic Pelton rotors. Notably, the starting wind speed of the new design is 20% lower, which makes it more suitable for real-world operating conditions, where wind speeds remain near minimum operating values most of the time.

Analysis of the airflow behind the turbine revealed how this effect is achieved. With an optimal axis tilt, RoDaVi not only deflects the flow, but also captures its momentum more effectively, converting it into rotor rotation and reducing the amount of energy lost to useless vortices and turbulence. As a result, the new geometry works as a single three-dimensional aerodynamic object rather than as a collection of individual blades or buckets.

The researchers believe that the new turbines could give a strong impetus to the development of small-scale and distributed wind power generation, where operational stability and adaptability to challenging wind environments are often more important than record-breaking power levels, which are only achievable in ideal conditions.

Tags: AnalysisEnergy efficiencyEngineeringFlowPower generationShapeStabilityTurbulenceVisualizationWind

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