A tool that predicts ice amount and distribution on marine structures
About the technology
Due to climate changes the Arctic marine territories are opening up for new and widespread industry activities such as aquaculture, new shipping pathways, offshore wind-energy harness and so on. However, icing of marine structures is a big challenge affecting operations. SPICE is a machine learning model that can predict the amount and distribution of ice on different structures including those on marine vessels, due to freezing sea spray in cold conditions. Leveraging novel sea spray flux algorithms and models developed at UiT, SPICE represent a leap forward in state of the art of ice prediction from sea spray.
User of Technology
- Marine vessel designers
- Shipping companies
- Off-shore companies operating in cold climates
- Certification companies such as the DNV Group AS
Value proposition
- Fully automated
- Predicts ice distribution depending on specific structures
- Predicts both amount and distribution of ice
- Based on 108k datapoints from more than 30 climate controlled experiments ensures high accuracy
- Validated in lab scale
Resources and partners
- Department of Building, Energy and Material Technology, UiT
- Demo of tool available
Collaboration partners
Opportunities for Collaboration
We are currently looking for industry partners who finds interest in our technology. We are open for working together on the development of SPICE to accommodate your needs.
Contact information
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