Exploring market uncertainty in early ship design

Jesper Zwaginga*, Ko Stroo, Austin Kana

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
24 Downloads (Pure)

Abstract

To decrease Europe's harmful emissions, the European Union aims to substantially increase its offshore wind energy capacity. To further develop offshore wind energy, investment in ever-larger construction vessels is necessary. However, this market is characterised by seemingly unpredictable growth of market demand, turbine capacity and distance from shore. Currently it is difficult to deal with such market uncertainty within the ship design process. This research aims to develop a method that is able to deal with market uncertainty in early ship design by increasing knowledge when design freedom is still high. The method uses uncertainty modelling prior to the requirement definition stage by performing global research into the market, and during the concept design stage by iteratively co-evolving the vessel design and business case in parallel. The method consists of three parts; simulating an expected market from data, modelling multiple vessel designs, and an uncertainty model that evaluates the performance of the vessels in the market. The case study into offshore wind foundation installation vessels showed that the method can provide valuable insight into the effect of ship parameters like main dimensions, crane size and ship speed on the performance in an uncertain market. These results were used to create a value robust design, which is capable of handling uncertainty without changes to the vessel. The developed method thus provides a way to deal with market uncertainty in the early ship design process.

Original languageEnglish
Pages (from-to)352-366
JournalInternational Journal of Naval Architecture and Ocean Engineering
Volume13
DOIs
Publication statusPublished - 2021

Keywords

  • Complex design methodologies
  • Early stage design
  • Offshore wind foundation installation
  • Uncertainty modelling

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