Ship Design with a Morphing Evolutionary Algorithm

Choo, Ciel Thaddeus; Ang, Joo Hock; Kuik, Simon; Hui, Louis Choo Ming; Li, Yun; Goh, Cindy

doi:10.1109/cec48606.2020.9185645

Cited by 4 publications

(1 citation statement)

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“…Many studies that use regression models for preliminary predictions and optimisations during the early design stage are carried out and presented in the literature. Some recent publications that have addressed and used statistical regression models in multi-criteria ship optimisations, parametric predictions of resistance and power, evolutionary algorithm and techniques for automation of hull form design, verifications with CFD and experimental data can be found in references [10,16,17,18,19,20,21]. A recent publication [22] provides helpful considerations on how to estimate Energy Efficiency Operational Indicator (EEOI), as part of Ship Energy Efficiency Management Plan (SEEMP) proposed by the International Maritime Organisation (IMO), based on the Automatic Identification System (AIS) data and application of Holtrop Mennen method.…”

Section: Introductionmentioning

confidence: 99%

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2022

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Preliminary prediction of resistance and power is a fundamental aspect of the ship design process since they directly influence the developments of the design process, fuel consumption and costs, and environmental impact from the early design stage. Parametric predictions of resistance and power, based mainly on statistical regression models that are also ideal for computer programming, are often performed during initial design stages, providing rapid predictions and optimisations for minimum resistance. The paper aims to present the results of the comparative analysis on some conventional hulls of the predictive accuracy of a computer program developed by the author for parametric predictions of resistance and power of ships. The program (entitled Ship Power V 1.0) is developed in the Visual Basic 6.0 environment based on two well-known regression models Holtrop and Van Oortmerssen. The program can perform detailed predictions of resistance and power, resistance coefficients, propeller thrust, hull efficiency, wake, and trust fractions, with no restriction on the number of velocities. In this study, only the analysis of the accuracy of resistance and power prediction is considered. Results of the comparative analysis of the computational procedures of Ship Power V 1.0 versus experimental data, and against results of another well-known commercial software, performed on three models of the Ridgely-Nevitt trawler series and KCS hull have shown a good level of accuracy and reliability as other well-known commercial software.

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