Predicting ice-induced load amplitudes on ship bow conditional on ice thickness and ship speed in the Baltic Sea

Mikko Kotilainen, Jarno Vanhatalo, Mikko Suominen, Pentti Kujala

Research output: Contribution to journalArticleScientificpeer-review

55 Citations (Scopus)

Abstract

Transportation in ice prone waters is a timely topic due to the pursuit for arctic natural resources and sea routes. One important safety aspect in designing ships that enter ice prone waters is to determine the ice-induced loads on ships. However, ice is a particularly inconsistent material; therefore it is difficult to predict the occurring loads when the ship hull breaks the ice. We propose a novel probabilistic, Bayesian, method for modeling and predicting ice load distributions in different ice and operational conditions. We assume the ice loads to be generated from a random process whose parameters change as a function of ice thickness and ship speed. We test four alternative hierarchical Gaussian Process models. The best model shows good performance in predictive validation tests. According to the results the probability of high ice loads increases with increasing ice thickness and increasing speed. The model can be used to predict continuously ice loads in different ice thickness and speed conditions and, with further development, has potential to be utilized in determining the safe way to operate ships in different conditions.
Original languageEnglish
Pages (from-to)116-126
JournalCold Regions Science and Technology
Volume135
Early online date11 Dec 2016
DOIs
Publication statusPublished - 2017
MoE publication typeA1 Journal article-refereed

Keywords

  • Ice loads
  • ice conditions
  • ice thickness
  • prediction
  • Bayesian statistics
  • Gaussian process

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