Overview
Oceanbird is developing rigid wing sails to reduce fuel consumption on commercial vessels by harnessing wind energy. The efficiency of these 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.
Objective
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. End goal will be to develop a methodology to process the visual data to determine the state of the tell-tales and thereby detect when the wing sail stalls.
Research Platform
There is possibility to conduct actual measurements on Oceanbird’s 40 m tall land-based prototype in Landskrona, Sweden. But the important deliverable would be a technical feasibility study conducted on either simulation or a scaled model.
Skills
We are looking for a driven student with strong research mindset, with ability to design experiments, analyze results, document and iterate solutions. It is beneficial to have strong software skills, with focus on machine vision, and basic understanding of aerodynamics or a strong will to learn the above. It is possible to tweak the proposal and objectives to align with your interests and your degree requirements.
Contact
Akash Singh, Control System Engineer, akash.singh@theoceanbird.com