Improving the Safety of Hydrofoil- A Dynamic Stress Prediction of Hydrofoil and Fatigue Analysis Method
Year: 2024
Type: conference-paper
Abstract: In the field of ocean engineering, the performance of ship propellers plays a crucial role in ship navigation, and accurately predicting the fatigue life of the structure is of great significance for ensuring the safety of ship operation. This article proposes a deep learning based model for predicting the fatigue life of ship propellers, which is used to predict the dynamic stress of twisted airfoils and subsequently predict the fatigue life of structures. Using LSTM and WNN as comparative models to verify the superiority of the Informer model. The results show that the dynamic stress prediction model based on the Informer model has the highest accuracy, and the hydrofoil structure can achieve 1.21 × 108 cycles in 20 years, ensuring the safe and stable operation of the structure. The research results can provide new methods and ideas for predicting the dynamic stress signals of ship propellers and evaluating their fatigue life.
Authors: Houyu Zhang, Yingbo Guan, Jinfu Lin, Yunshui Peng, Mingkun Fang, Xu Han, Ran Tao, Ruofu Xiao
Language: English
Subfield: Mechanics of Materials
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410739787