Elucidating families of ship designs using clustering algorithms

Conference paper (2017)

Authors

A. A. Kana Ship Design, Production and Operations - Mechanical, Maritime and Materials Engineering
Research Group
Ship Design, Production and Operations (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2017

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Marine and Transport Technology

Research Group

Ship Design, Production and Operations

Abstract

This paper proposes a method to elucidate families of ship designs generated by the TU Delft packing approach using data clustering algorithms. The authors explore whether commonly used data science techniques can extract new information from the existing data. To test this hypothesis this paper applies data clustering algorithms to a test case of layouts of a Mine Counter Measures Vessel (MCMV) generated by the packing approach. Results look to improve the understanding of the multidimensional structure of the data, as well as to improve the comprehension and visualization of the complex interactions between the design and performance space.

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