Vis enkel innførsel

dc.contributor.authorchoi, ju-hyuck
dc.contributor.authorJensen, Jørgen Juncher
dc.contributor.authorNielsen, Ulrik Dam
dc.date.accessioned2022-06-29T11:10:19Z
dc.date.available2022-06-29T11:10:19Z
dc.date.created2020-12-17T20:35:28Z
dc.date.issued2021
dc.identifier.isbn978-981-15-4671-6
dc.identifier.urihttps://hdl.handle.net/11250/3001543
dc.description.abstractExtreme value statistics can often be based on the assumption that exceedance events of a high threshold level are statistically independent and identically distributed (i.i.d. process), which further implies the Poisson assumption to be valid. This makes it possible to express the extreme response statistics through the mean up-crossing rate. For non-linear processes, analytic expressions of the mean up-crossing rate do not in general exist. Reliable statistics of mean up-crossing rate based on the brute-force approach, e.g. Monte Carlo simulation (MCS) require long time domain simulations considering a number of different ensemble input. The associated computations can be very time consuming especially when a detailed physical (e.g. hydrodynamic) model is applied. The First Order Reliability Method (FORM) has previously been found efficient for estimation of extreme value prediction of stationary stochastic time domain processes, However, if the non-linearity in a response is significant, the accuracy of the FORM linearized mean up-crossing rate can be limited. The present work attempts to improve the extreme value prediction for non-linear parametric roll motions of ships based on applications of the FORM approach and suggests a model for the mean up-crossing rate for strong non-linear response, validated by comparing with MCS results.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofPractical Design of Ships and Other Floating Structures. Proceedings of the 14th International Symposium, PRADS 2019, September 22-26, 2019, Yokohama, Japan- Volume II
dc.titleEstimation of Extreme Roll Motion Using the First Order Reliability Methoden_US
dc.typeChapteren_US
dc.description.versionacceptedVersionen_US
dc.rights.holderThis is the authors' accepted manuscript to an article published by Springer.en_US
dc.source.pagenumber682-690en_US
dc.identifier.cristin1861312
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel