Session: 02-12-01 Digital Twins of Marine Structures 1
Submission Number: 175983
Research on Applying Artifical Intelligence and Digital Twin Technology to FPSO Riser Support TSUDL for Safety Assessment
Yantai CIMC Raffles has delivered several FPSO riser bellmouth in past few years for Brazil. Safety monitoring and early warning systems are critical for the operation and maintenance of FPSO riser bellmouth, particularly in terms of accurately and promptly predicting their extreme load responses. To address this challenge, applying artificial intelligence and digital twin technology to Diverless Unified Support Tube (Portuguese acronym: TSUDL) for safety assessment has also been developed in order to provide operation and maintenance surveillance.
This paper proposes a model order reduction method based on Long Short-Term Memory networks (LSTM) for FPSO riser support systems, aiming to significantly enhance computational efficiency while maintaining model accuracy. By extracting dynamic features from finite element simulation data, the LSTM neural network algorithm effectively captures the nonlinear response characteristics of riser supports under irregular wave induced loads and integrates learning of long-term dependencies within the database.
For demonstration, a test case employs 10-minute transient simulation data to train the LSTM model and validates it under set of simulation data without pre-knowledge of sea conditions. The results demonstrate that the reduced-order model achieves an average absolute percentage error (MAPE) of less than 5% across multiple output parameters, significantly reduces computational time, and exhibits strong generalization capability and real-time prediction potential.
Our approach gives promising application prospects of the LSTM reduced-order model in health monitoring and operational decision support for riser support structures. offering a feasible pathway for efficient simulation and intelligent operation and maintenance of complex systems in FPSO riser equipment.
Presenting Author: Wenping Wang CIMC Raffles Offshore Engineering Limited
Presenting Author Biography: I was born in China in 1970. I come to Singapore as a research scholar of National university of Singapore in 1994. After graduation with master's degree (civil Engineering Department), I start to work in Singapore marine and offshore industry.
I have been focused on marine and offshore basic design with over 20 years working experience in Singapore. I have proven track records in leading a structural group for complete semisubmersible and drillship hull and topside structural design. Hand-on experience for TLP basic design in US Huston design office.
Familiar with various FEM tools for global/local strength/fatigue/vibration analysis for various kinds of ships with proven yard records in both engineering and production team. Experienced in liaising with client, class, and design groups for dealing with diverse requirements. Also contribute in knowledge sharing to research and development for both university and institutes. Now, I work for Yantai CIMC raffles as principal engineer, majoring as foreign expert in engineering consultants.
Major Work History and Title are shortlisted as below.
CIMC RAFFLES Offshore Engineering, Principal Engineer Foreign Expert, 2021- current
Keppel Marine & Deepwater Technology P L, Keppel, Technical Manager, 2012 – 2020
Sembcorp Marine Technology P L, Jurong Shipyard, Executive Engineer, 2009 – 2012
Keppel Deepwater Technology P L, Keppel, Senior Engineer, 2006 – 2009
Singapore ANSYS ASD, Technical Consultant Manager, 1999 – 2006
Authors:
Qiang Fu CIMC Raffles Offshore LimitedWenping Wang CIMC Raffles Offshore Engineering Limited
Haodong Zhang CIMC Raffles Offshore Engineering Limited
Yunquan Zhang CIMC Raffles Offshore Engineering Limited
Bo Wang CIMC Raffles Offshore Engineering Limited
Lijuan Guo CIMC Raffles Offshore Engineering Limited
Chunping Geng CIMC Raffles Offshore Engineering Limited
Langjun Xu CIMC Raffles Offshore Engineering Limited
Shumin Li CIMC Raffles Offshore Engineering Limited
Research on Applying Artifical Intelligence and Digital Twin Technology to FPSO Riser Support TSUDL for Safety Assessment
Submission Type
Technical Paper Publication