[pdf]

Note:

Abstract: Since mankind put to sea, the seakeeping capabilities of its vessels has been the decisive factor on the save voyage of their seafarers. In modern times the analysis of vessel responses to seaway by numerical calculations has developed to be the industry standard alongside model tests. At the Institute of Ship Design and Ship Safety of the Hamburg University of Technology the Software E4-ROLLS is used to perform such kind of analyses. Originating in the 1980s this piece of software has been validated through plentiful research as well as accident investigations. While sufficiently accurate and fast in its predictions on the roll motion of ocean-going ships, such calculations are currently performed only for specific loading conditions and seaways due to its requirement of some preceding calculations and manual user interaction. Recent research is set out to widen the scope onto the entire operational profile of ships and all necessary seaway situations. This target has already been achieved by research at the institute. First a large number of loading conditions is generated using a Monte-Carlo-based approach. Second automated calculations with E4-ROLLS result in a large quantity of accurate training data. Third polynomial regression, a method of machine learning and artificial intelligence, is utilized to find a fitting mathematical model of the training data, resulting in a mean quadratic prediction error below 0.5 meters of limiting significant wave height for an exemplary ultra large container vessel. This paper is set out to use these prediction models for long term evaluations of specific voyages concerning the likelihood of dangerous vessel motions based on environmental data gathered from Copernicus datasets. This process is applied to a comparison of three instances of a neo-panamax-size container vessel design.