Modelling vortex-induced loads using machine learning

Research output: Chapter in Book/Report/Conference proceedingConference paper


Dynamic fluid loading is of major concern to the off shore industry. Impacted structures may exhibit accel- erated fatigue and even failure. Load monitoring has therefore become an integral part of structural health monitoring. Obtaining direct load measurements can be cumbersome, e.g. obtaining strain gauge or pres- sure taps measurements. In this work, an alternative indirect method is proposed. The method revolves around building a mapping between more easily accessible wake velocity measurements and the induced loads. Classical machine learning techniques are adopted and relatively compact models, able to be run in real-time, are obtained. The method is illustrated on vortex-induced loads on a submerged cylinder.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Noise and Vibration Engineering (ISMA)
EditorsW. Desmet, B. Pluymers, D. Moens, S. Vandemaele
Number of pages14
ISBN (Electronic)9789082893113
Publication statusPublished - 1 Jan 2020
EventInternational Conference on Noise and Vibration Engineering 2020 - Leuven, Belgium
Duration: 7 Sep 20209 Sep 2020

Publication series

NameProceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics


ConferenceInternational Conference on Noise and Vibration Engineering 2020
Abbreviated titleISMA2020


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