Polar vessel hullform design based on the multi-objective optimization NSGA II

[Objectives] With the increasing exploitation of the Arctic abundant oil and gas resources, a large number of ships which meet the polar navigational requirements are needed. [Methods] In this paper, the fast elitist Non-Dominated Sorting Genetic Algorithm (NSGA Ⅱ) is applied to the hull optimizatio...

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Bibliographic Details
Main Authors: DUAN Fei, ZHANG Lijun, CHEN Ge, JIANG Haining, ZHANG Qi
Format: Article in Journal/Newspaper
Language:English
Chinese
Published: Editorial Office of Chinese Journal of Ship Research 2017
Subjects:
Online Access:https://doi.org/10.3969/j.issn.1673-3185.2017.06.010
https://doaj.org/article/0ea57e1cd73f49c3af59521d21e61c67
Description
Summary:[Objectives] With the increasing exploitation of the Arctic abundant oil and gas resources, a large number of ships which meet the polar navigational requirements are needed. [Methods] In this paper, the fast elitist Non-Dominated Sorting Genetic Algorithm (NSGA Ⅱ) is applied to the hull optimization, and the multi-objective optimization method of polar vessel design is proposed. With the optimization goal of resistance and icebreaking resistance, filtering hull forms through the standard of polar vessel displacement and EEDI, fast ship hull optimization that satisfy the ice-ship dead weight and EEDI requirements has been achieved. Taking a 65 000 t shuttle tanker as an example, full parametric modeling method is adopted, the hull optimization of three different bow forms is conducted through the polar vessel multi-objective optimization method. [Results] The ship hull after optimization can satisfy the IA class navigation require, where the resistance in calm water decreases up to 12.94%, and the minimum propulsion power in ice field has a 27.36% reduction. [Conclusions] The feasibility and validity of the NSGA Ⅱ applying in polar vessel design is verified.