A study on the dynamic response of deepwater top tension riser systems and LSTM model prediction

Peng Liu

doi:10.1117/12.3025471

28 February 2024 A study on the dynamic response of deepwater top tension riser systems and LSTM model prediction

Peng Liu

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 1307124 (2024) https://doi.org/10.1117/12.3025471
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

This study focuses on the nonlinear coupled dynamic analysis of deepwater top Tension riser systems. Using OrcaFlex software, we developed a model of a dual-casing top Tension riser equipped with centralizers. Sensitivity analyses of key parameters, such as centralizer height and top tension factor, revealed the coupling mechanisms and dynamic response characteristics of the dual-casing top-Tension riser. Additionally, the study examined variations in riser displacement amplitudes and pipe-to-pipe contact forces at different water depths. The model and methodologies proposed in this study provide crucial theoretical and practical guidance for the design and operation of deepwater top-Tension riser systems. At the same time, the LSTM neural network model was used to train a dynamic response model of a deep-water top Tension riser systems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Peng Liu "A study on the dynamic response of deepwater top tension riser systems and LSTM model prediction", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 1307124 (28 February 2024); https://doi.org/10.1117/12.3025471

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