Subsea storage tanks play a crucial role in the development of deep-sea oil and gas fields, yet their long-term operation is challenged by multiple risks such as corrosion, fatigue, and buckling. Traditional monitoring methods struggle to meet the demands for real-time performance and full coverage. This paper proposes a real-time simulation method based on a reduced-order model (ROM) to predict the mechanical response of subsea storage tanks. The method first extracts characteristic modes from design experiments through parametric modeling and principal component analysis (PCA) to construct the ROM. Subsequently, the ROM enables rapid computation while ensuring result reliability through error estimation. Numerical experiments demonstrate that the ROM achieves a 90-fold increase in computational speed while maintaining accuracy over 99%, thereby realizing real-time response prediction for subsea storage tanks. This research provides a preliminary approach for the structural health monitoring of subsea storage tanks under linear-elastic conditions, laying a foundation for future extensions to intelligent platforms in marine engineering.
Duan et al. (Sun,) studied this question.