The estimation of rare, extreme environments from a relatively short oceanographic database is crucial to the calculation of loads and responses of offshore structures. A novel and consistent approach has been developed that makes use of a number of asymptotic properties of extremes. A storm can be adequately characterised by its most probable extreme wave or the resultant structural response. This allows us to treat storms, rather than sea states, as the essential random, independent events; to account correctly for uncertainty in the largest wave and structural response within a storm; and to deal with the uncertainty in the seventy of randomly arriving storms, including the rare storms that are more severe than those in the database. The method provides the long term load statistics essential to reliability analysis and to the calibration of environmental Ioad factors in design codes.We demonstrate the application of the method to the prediction of extreme waves, loads and "response based" environmental design conditions for a drag dominated structure in the North Sea.
The Wave Crest Sensor Intercomparison Study (WACSIS) was designed as a thorough investigation of the statistical distribution of crest heights. Measurements were made in the southern North Sea during the winter of 1997–1998 from the Meetpost Noordwijk in 18 m water depth. The platform was outfitted with several popular wave sensors, including Saab and Marex radars, an EMI laser, a Baylor wave staff and a Vlissingen step gauge. Buoys were moored nearby to obtain directional spectra. Two video cameras viewed the ocean under the wave sensors and their signals were recorded digitally. The data analysis focused on comparisons of the crest height measurements from the various sensors and comparisons of the crest height distributions derived from the sensors and from theories. Some of the sensors had greater than expected energy at high frequencies. Once the measurements were filtered at 0.64 Hz, the Baylor, EMI and Vlissingen crest height distributions matched quite closely, while those from the other sensors were a few percent higher. The Baylor and EMI crest distributions agreed very well with the statistics from second order simulations, while previous parameterizations of the crest height distribution were generally too high. We conclude that crest height distributions derived from second order simulations can be used with confidence in engineering calculations. The data were also used in investigations of crest and trough shapes and the joint height/period distribution.
The key issue addressed in this paper is the accuracy of structural reliability models for the case of fixed steel offshore structures under extreme storm loading. The emphasis is on engineering accuracy for the purpose of use in decision-making, and more specifically to achieve sufficient accuracy to enable the use of reliability models in deriving design criteria for fixed offshore platforms. These reliability models are used to derive partial load factors for use in conjunction with API LRFD to achieve a target reliability level appropriate for permanently manned installations. These load factors are location-dependent. Further load factors are proposed for the design of new, not normally manned installations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.