Novel SEConv1D framework for real-time hydrodynamics prediction of the unidentified underwater vehicle

• Main Authors: Hou, Yuqing, Li, Hui, Chen, Hong, Shen, Shengnan, Duan, Fei, Wei, Wei, Wang, Jiayue, Huang, Yicang, Guan, Xiawei, Liao, Yinghao
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Mechanical engineering; Computational Fluid Dynamics; Resistance Coefficient
• Online Access: https://hdl.handle.net/10356/172033
• Institution: Nanyang Technological University

The accurate and rapid prediction of hydrodynamic characteristics greatly affects the monitoring of the manoeuvring performance of unidentified underwater vehicles. This work proposes a novel SEConv1D framework for the hydrodynamics prediction of the unidentified underwater vehicle. Firstly, a novel...