Modeling time varying and multivariate environmental conditions for extreme load prediction on offshore structures in a reliability perspective

Abstract

With the changing environmental conditions experienced over the last decade, design against failures of offshore structures has becomes even more challenging. In this study, the characterization of the time varying characteristics of variables associated with the environmental loads, the dependencies between these variables, and the impact of the uncertainties and dependencies on the long term assessment of a typical marine structure is investigated. In analyzing a time varying environment, a modified segmentation algorithm with specified fixed time interval is proposed to extract homogeneous data sets from non-stationary time series data to account the time varying effect. Two-dimensional Fast Fourier transform is employed to characterize the variations of extreme values with time. A collected group of data is selected to demonstrate such a discretized model. This approach of incorporating the time varying effect is examined through the reliability analysis of an existing offshore platform. In a multivariate environment, the dependencies between the load-related environmental parameters are studied. Extending beyond the linear correlation coefficient, the concept of copula is introduced to improve the quantification of the dependencies between variables as how the pairs of data are spread is considered. A further refinement is proposed through a discretized copula approach with a scheme to reduce the numerical efforts in deriving the long term response distribution of the offshore structure. A numerical example is presented to demonstrate that the proposed method produces more accurate results as the most critical sea states are identified.