Near Real Time Prediction of Vibration in 3D Printed Flettner Rotor Demonstrator

This paper presents an investigation of the Flettner rotor, a wind propulsion system utilized in ships to decrease fuel consumption and reduce carbon emissions by leveraging the Magnus effect. Proper balancing and stability of the rotor are crucial to ensure high operational efficiency and low energy consumption. In the present work, a 3D printed rotor, which is a scaled-down version of the "Water Taxi", is developed to predict the unbalanced forces and vibrations of the rotor. Two methods are presented in this paper for the determination of the magnitude and direction of unbalanced forces by utilizing strain gauge readings. The force prediction model is implemented using machine learning algorithms. Furthermore, the paper discusses potential solutions for balancing the rotor once vibrations and unbalanced forces are detected. The results of this research could potentially contribute to the development of improved Flettner rotor designs, leading to more efficient and eco-friendly shipping.

I. Introduction

The contemporary shipping industry is faced with several challenges that demand solutions to reduce fuel consumption, ensure ocean sustainability, and minimize travel costs. Stricter environmental regulations and inflationary pressures have caused fuel prices to escalate, prompting ship owners to explore innovative ways to save fuel. Wind propulsion technology presents a promising solution to reduce fuel consumption, lower freight rates, and mitigate greenhouse gas emissions. [1]