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The University of Southampton

Maritime engineers to deliver fuel savings at sea in new engineering partnership

Published: 8 July 2020
The Silverstream system
The Silverstream system uses air lubrication reducing resistance between a vessel’s hull and water

Researchers from the University of Southampton will apply machine learning techniques to a fuel-saving air lubrication system in a new partnership with Silverstream Technologies.

The two-year partnership will optimise the performance of the company’s Silverstream System, which reduces frictional resistance between a vessel’s hull and the water to currently deliver fuel savings of between five and 10 per cent.

Dr Adam Sobey, Associate Professor in the Maritime Engineering Group and co-lead of the marine and maritime group in the Data-Centric Engineering programme at The Alan Turing Institute, will lead the project, supported by Professor Dominic Hudson, Shell Professor of Ship Safety and Efficiency.

Under the Innovate UK Knowledge Transfer Partnership (KTP), the University will embed an Associate into Silverstream’s operations with the goal to advance intelligence within the system’s control and automation module.

“The potential for machine learning and artificial intelligence technologies to improve the performance and efficiency of the maritime sector is truly staggering,” Adam says. “That is why this Knowledge Transfer Partnership with Silverstream is so important: it will allow us to build on fundamental research on machine learning, that was supported by our ongoing relationship with Shell Shipping and Maritime, and to test these exciting new technologies with the maritime industry’s clean technology leaders, ultimately accelerating the push for efficiency that the sector so desperately needs to meet its decarbonisation goals.”

The KTP will aim to increase savings by analysing operational data taken from installed systems. This data, when combined with cutting edge machine learning techniques, will help to further increase System performance during a voyage, with the goal of gaining the theoretical maximum savings associated with the technology every time it is operating.

Ultimately, the project will serve as a testbed for advancing machine learning and artificial intelligence within maritime. With decarbonisation targets looming for the sector, optimising clean technologies will form a core part of the industry’s strategy to meet its obligations as they have been laid out by the International Maritime Organisation.

Noah Silberschmidt, CEO, Silverstream Technologies, says: “Today, there is an increasing amount of data coming from in-operation installations of the Silverstream® System that can be used for performance prediction and optimisation, requiring us as clean technology leaders to develop new expertise to master and understand this vast source of potential improvement.

“Previous work to understand how AI and machine learning can benefit the performance of our technology has aided us both in optimising each Silverstream System and in validating our performance claims to the market.

“This KTP grant marks the next step on this journey, allowing us to work with the world’s leading researchers at the University of Southampton and The Alan Turing Institute to accelerate machine learning within shipping, ultimately enabling us to bring about a more efficient and more sustainable maritime sector.”

KTPs are funded by UKRI through Innovate UK with the support of co-funders, including the Scottish Funding Council, Welsh Government, Invest Northern Ireland, Defra and BEIS. Innovate UK manages the KTP programme and facilitates its delivery through a range of partners including the Knowledge Transfer Network (KTN), Knowledge Bases and Businesses. Each partner plays a specific role in the support and delivery of the programme.

Terry Corner, Knowledge Transfer Adviser, Knowledge Transfer Network, says: “This is an exciting KTP project that will greatly aid the international shipping industry to meet ambitious emission-reduction targets of 40% and 70% by 2030 and 2050 respectively. Few technology offerings can offer savings like those generated by the Silverstream System at a similar cost per tonne of CO2 abated.”

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