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)
Publication statusPublished - 2020
EventInternational Conference on Noise and Vibration Engineering 2020 - Leuven, Belgium
Duration: 7 Sep 20209 Sep 2020


ConferenceInternational Conference on Noise and Vibration Engineering 2020
Abbreviated titleISMA2020

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