A Data-Driven Framework for Fatigue Monitoring of Operating Flexible Risers

Rasoul Hejazi, Andrew Grime, Ian Milne, Phil Watson, Elizabeth White, Alessio Mariani, Max Lanoёllё

Research output: Chapter in Book/Conference paperConference paperpeer-review

Abstract

An accurate estimation of riser fatigue life plays a critical role in the efficient structural integrity management of operating flexible risers. A more reliable fatigue life estimate could, for example, enable life extension for aging flexible risers or facilitate the use of a more targeted intervention program. This paper introduces a data-centric paradigm for the fatigue monitoring of flexible risers which uses measured host vessel motion data as part of the riser global response analysis. The performance of this method is assessed by comparison with the conventional analysis method, which uses a condensed wave scatter diagram combined with vessel motion transfer functions to assess global response. In the study, Python packages Scipy and Pandas are used to process raw wave and motion data obtained from wave measuring buoys and sensors located on the host vessel, respectively, to obtain the input load data, and non-linear time-domain analysis is used to calculate the global riser response due to both irregular waves and the measured motions. Tensions and curvatures obtained from the global riser response analysis form the input to a local stress analysis, which uses a proprietary software tool to estimate the stress response at the tensile and pressure armours. The output is then combined with a rainflow cycle counting technique and an S-N curve approach to perform the local fatigue assessment at the riser critical points. This paper compares the predicted and measured key input parameters (such as vessel heading, motions etc.) that affect the estimated fatigue life of a representative flexible riser connected to an operating Floating, Process, Storage and Offloading (FPSO) host vessel. Finally, the paper provides practical recommendations for using measured host-vessel motion data as part of a rigorous fatigue monitoring of connected flexible risers.

Original languageEnglish
Title of host publicationProceedings of the ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering
Subtitle of host publicationMaterials Technology; Pipelines, Risers, and Subsea Systems
PublisherASME International
Volume3
ISBN (Electronic)9780791885871
DOIs
Publication statusPublished - 2022
EventASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2022 - Hamburg, Germany
Duration: 5 Jun 202210 Jun 2022

Conference

ConferenceASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2022
Country/TerritoryGermany
CityHamburg
Period5/06/2210/06/22

Fingerprint

Dive into the research topics of 'A Data-Driven Framework for Fatigue Monitoring of Operating Flexible Risers'. Together they form a unique fingerprint.

Cite this