Prediction of the superiority of the hydrodynamic performance of hull forms using deep learning

Prediction of the superiority of the hydrodynamic performance of hull forms using deep learning

When designing a ship's hull form, a designer creates various candidate hull forms and performs a Computational Fluid Dynamics (CFD) analysis to evaluate the performance of each candidate. Designers consider quantitative indicators, such as the total resistance and wake coefficient, and qualita...

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Bibliographic Details
Main Authors: Jin-Hyeok Kim, Myung-Il Roh, Ki-Su Kim, In-Chang Yeo, Min-Jae Oh, Jung-Woo Nam, Sahng-Hyon Lee, Young-Hun Jang
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:International Journal of Naval Architecture and Ocean Engineering
Subjects:
Hull form design
Hydrodynamic performance
Superiority prediction
Deep learning
Convolutional Neural Network (CNN)
Computational Fluid Dynamics (CFD)
Online Access:http://www.sciencedirect.com/science/article/pii/S2092678222000565

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http://www.sciencedirect.com/science/article/pii/S2092678222000565

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