Oceanbird initiates more research
Oceanbird, founded by Wallenius Wilhelmsen, launched a land-based prototype last august. Meanwhile, the company puts out five research proposal for further development.
The research proposals are all concerning the technical optimisation of rigid wing sails. The Oceanbird protoype features telescopic retractable rigid sails. The proposals are open for PhD students who want to write their thesis about the proposed subject.
The company states in its invitation:
Wind helped us discover our planet, and now it can help us preserve it. Would you like to contribute to the development of our wing during your studies? We are excited to bring in curious minds to help us deepen knowledge together.
The proposals are:
Development of a Vision-Based System for Angle-of-Attack Detection and Anemometer Calibration on a Rigid Wing Sail
This thesis aims to develop a hardware and software suite to capture and process images from multiple cameras, of tell-tales on the wing, ideally in real time. By correlating the observed tell-tale behavior with the wing’s operational data, the project will develop a methodology to detect the AoA and derive a calibration factor for the anemometer’s apparent wind angle measurements.
Development of a Vision-Based System for Stall Detection on a Rigid Wing Sail
The efficiency of the wing sails is critically dependent on them operating consistently near their optimum lift-to-drag ratio. Tell-tales, which are short yarn or fabric strips that respond to local airflow conditions, have been utilized in sailing for centuries as visual indicators of flow attachment. Recent academic work has demonstrated the feasibility of computer vision-based tell-tale detection systems for automated sail trimming applications. So, we would like to explore the practicality of using these low-cost devices, combined with other hardware and software tools for quantitative measurements as well, this project being one example of such an approach.
Extremum seeking feedback control of wing-sail during motor-sailing
Oceanbird’s current trimming strategy uses a feed-forward approach based on measured wind conditions. The drawback with the feed forward approach described above is that it relies heavily on models describing the reaction forces based on measurements on the inflow (wind). It is not certain that those models are accurate enough to actually find the trim angles that maximizes the thrust in any given situation. Further, those models needs to be adapted for each installation since the wind interactions with the ship affect both wind sensor readings as well as the aerodynamic performance of the wing. Therefore we want to explore the possibilities to use more feedback into the trimming control. Feedback parameters could be measured thrust force, measured ship speed, engine torque, engine power etc.
Feasibility and cost-benefit analysis of a wing-sail structure with alternative material combinations
The objective of this thesis is to perform a comparative analysis of three different material configurations for the load-bearing structure of the Oceanbird wing-sail:
• Steel mast with glass-fibre composite panels
• Fully glass-fibre composite structure (mast and profile)
• Fully carbon-fibre composite structure (mast and profile)
The analysis will focus on:
• Structural performance: including fibre strain evaluation and buckling capacity under defined load cases.
• Weight comparison: estimating the total structural weight for each configuration.
• Cost estimation: including raw material costs and basic production cost assumptions. Manufacturability should be considered.
Hybrid Vision-AI Framework for Deflection Measurement of a Land-Based Rigid Wing Sail
Our rigid wing sail is made with steel and composite parts, which move but also bend and deflect in foreseeable and unforeseeable ways. Accurately quantifying bending and twisting of moving structures is critical for structural integrity models, yet most vision-based deflection studies target static bridges or buildings. This project explores whether a hybrid machine-vision and AI approach can supplement traditional point-sensor techniques when the monitored component is a land-mounted rigid wing sail that rotates during testing. The study will benchmark state-of-the-art depth-estimation neural networks, stereo/monocular vision pipelines, and classic photogrammetry against high-accuracy reference sensors to determine achievable precision, repeatability, and long-term stability.
More information can be found here.
Source: Oceanbird.
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