Extreme large cargo ship panel stresses by bivariate ACER method

• Published in: Ocean engineering 2016-09, Vol.123, p.432-439
• Main Authors: Gaidai, Oleg, Storhaug, Gaute, Naess, Arvid
• Format: Article
• Language: English
• Subjects: Brackish; Cargo ships; Container ship; Extreme value statistics; Gumbel distribution; Marine; Mathematical models; Nonlinearity; Panels; Ship panel; Ships; Statistics; Stress; Stresses; Vessels; Whipping
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2016.06.048

Safety of crew, ship and cargo requires that ships are designed to endure wave load extreme events. Design values are often based on univariate statistical analysis, while actually multivariate statistics is more appropriate for modeling the whole structure. This paper studies extreme stresses simultaneously measured at two different deck locations of a container vessel operating in the North Atlantic between Europe and North America. The focus is placed on the hydroelastic structural response, particularly whipping, which refers to transient vibratory response of the hull girder due to wave impacts occurring mainly in the bow area. It must be noted however that since analysed in this paper vessel hydroelastic response is a on-board measured one, it includes all non-linear effects like both whipping and springing. Due to less than full correlation between stresses in the different ship panels, application of the multivariate, or bivariate in the simplest case, extreme value theory is of interest. Due to non-stationarity and complicated nonlinearities of the wave induced loads, as well as the human factor in the operation of ships, reliable numerical prediction of extreme hydroelastic vessel responses, including whipping, is challenging. Laboratory tests and numerical simulation tools may not fully reproduce all critical conditions that take place during real vessel operation. Therefore, measurements on-board of real ships provide a key insight into the structural responses when the vessel is at sea. This paper focuses on application of the ACER (average conditional exceedance rate) method for prediction of extreme value statistics extended to the case of bivariate time series. Application of bivariate version of ACER method is demonstrated for simultaneously measured stresses at mid and aft deck locations. •New state of art statistical method is applied to simultaneously measured ship panel stresses.•Practical and accurate prediction of extreme bimodal stresses is done.•Novel statistical tail extrapolation technique (bimodal) is used.