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Original scientific paper
https://doi.org/10.21278/brod68206

AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS

Francesco Mauro   ORCID icon orcid.org/0000-0003-3471-9411 ; Università degli Studi di Trieste
Radoslav Nabergoj ; NASDIS PDS, Industrijska Cesta 2E, 6310 Izola, Slovenija

Fulltext: english, pdf (1 MB) pages 79-92 downloads: 555* cite
APA 6th Edition
Mauro, F. & Nabergoj, R. (2017). AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS. Brodogradnja, 68 (2), 79-92. https://doi.org/10.21278/brod68206
MLA 8th Edition
Mauro, Francesco and Radoslav Nabergoj. "AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS." Brodogradnja, vol. 68, no. 2, 2017, pp. 79-92. https://doi.org/10.21278/brod68206. Accessed 3 Dec. 2021.
Chicago 17th Edition
Mauro, Francesco and Radoslav Nabergoj. "AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS." Brodogradnja 68, no. 2 (2017): 79-92. https://doi.org/10.21278/brod68206
Harvard
Mauro, F., and Nabergoj, R. (2017). 'AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS', Brodogradnja, 68(2), pp. 79-92. https://doi.org/10.21278/brod68206
Vancouver
Mauro F, Nabergoj R. AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS. Brodogradnja [Internet]. 2017 [cited 2021 December 03];68(2):79-92. https://doi.org/10.21278/brod68206
IEEE
F. Mauro and R. Nabergoj, "AN ENHANCED METHOD FOR EXTREME LOADS ANALYSIS", Brodogradnja, vol.68, no. 2, pp. 79-92, 2017. [Online]. https://doi.org/10.21278/brod68206

Abstracts
The analysis of time records, coming from seakeeping experiments in irregular waves, is used to determine the occurrence of extreme events. The common procedure used for data analysis is to assume that the statistics of record’s peaks is following two or three parameters Weibull distribution. For particularly severe sea states it can happen that the peaks assume a multi-modal distribution. In this case, a Weibull distribution is not suitable, also in the three parameters form, to reproduce the peaks population. That means some errors in the estimate of the extreme loads may occur, affecting consequently the vessel/structure design process. To overcome this source of error it is possible to use multi-modal distributions, or to change the peaks extraction technique, adopting a certain threshold. By using this second approach data should be fitted according to a Generalised Pareto distribution. Based on this theory, a data analysis procedure including the threshold selection is here proposed and tested on a set of time records coming from seakeeping model-scale experiments. The results are then compared with the standard Weibull approach.

Keywords
Generalised Pareto Distribution; Weibull Distribution; Extreme Value Theory

Hrčak ID: 177415

URI
https://hrcak.srce.hr/177415

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