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Stochastic bivariate time series models of waves in the North Sea and their application in simulation-based design

Article by Sandvik et al. in Ocean Applied Research, November 2018

Stochastic bivariate time series models of waves in the North Sea and their application in simulation-based design

Article by Sandvik et al. in Ocean Applied Research, November 2018

A simulation-based ship design methodology for evaluating susceptibility to weather-induced delays during marine operations

Article by Sandvik et al. in Ship Technology Research, May 2018

Potential power setups, fuels and hull designs capable of satisfying future EEDI requirements

Publication by Elizabeth Lindstad and Torstein Ingebrigtsen Bø in Transportation Research Part D.

Control of the combustion process and emission formation in marine gas engines

Article by Krivopolianski et al. in Journal of Marine Science and Technology

Sulphur Abatement Globally in Maritime Shipping

Publication by H. Elizabeth Lindstad (SINTEFOcean AS), Carl Fredrik Rehn, NTNU, and Gunnar S. Eskeland (NHH and SNF), accepted for publication in Transportation Research Part D.

Machine Learning based Data Handling Framework for Ship Energy Efficiency

Study by L.P. Perera and B. Mo published in IEEE Transactions on Vehicular Technology.

State-of-the-art technologies, measures, and potential for reducing GHG emissions from shipping – A review

Review article by Bouman et al. of GHG reduction measures and their potential in shipping published in Transportation Research Part D: Transport and Environment.

Marine Engine-Centered Data Analytics for Ship Performance Monitoring

Article by Lokukaluge Prasad Perera and Brage Mo

Development of Data Analytics in Shipping - Prasad Perera

Modern vessels are monitored by Onboard Internet of Things (IoT), sensors and data acquisition (DAQ), to observe ship performance and navigation conditions. Such IoT may create various shipping industrial challenges under large-scale data handling situations. These large-scale data handling issues are often categorized as “Big Data” challenges and this chapter discusses various solutions to overcome such challenges.