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Open AccessArticle

Assessing an Improved Bayesian Model for Directional Motion Based Wave Inference

1
Naval Arch. & Ocean Eng. Department, Escola Politécnica, University of São Paulo (USP), São Paulo-SP 05508-030, Brazil
2
CEHINAV, ETSIN, Universidad Politécnica de Madrid (UPM), 28006 Madrid, Spain
3
CEHINAV, DACSON, ETSIN, UPM, 28006 Madrid, Spain
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
J. Mar. Sci. Eng. 2020, 8(4), 231; https://doi.org/10.3390/jmse8040231 (registering DOI)
Received: 15 February 2020 / Revised: 16 March 2020 / Accepted: 21 March 2020 / Published: 26 March 2020
An innovative Bayesian motion-based wave inference method is derived and assessed in this work. The evaluation of the accuracy of the proposed prior distribution has been carried out using the results obtained during a dedicated experimental campaign with a scale model an Oil and Gas (O&G) semisubmersible platform. As for the Bayesian statistical inference approaches, the features of the proposed novel prior distribution, as well as the hypotheses adopted, are discussed. It has been found that significant improvements can be obtained if the new approach is adopted to estimate the sea conditions from measured vessel motions. Finally, it is possible to highlight a substantial reduction of the computing time when the sea conditions are estimated by means of the improved Bayesian method, if compared with the conventional approaches for motion-based wave inference. View Full-Text
Keywords: directional motion-based wave inference; semisubmersible platform; Bayesian modelling; prior distribution directional motion-based wave inference; semisubmersible platform; Bayesian modelling; prior distribution
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Mas-Soler, J.; Souto-Iglesias, A.; Simos, A.N. Assessing an Improved Bayesian Model for Directional Motion Based Wave Inference. J. Mar. Sci. Eng. 2020, 8, 231.

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