Abstract
Nonlinear time-domain simulations are often used to predict the structural response at the design stage to ensure the acceptable operation and/or survival of floating structures under extreme conditions. An environmental contour (EC) is commonly employed to identify critical sea states that serve as the input for numerical simulations to assess the safety and performance of marine structures. In many studies, marginal and conditional distributions are defined to construct bivariate joint probability distributions for variables, such as significant wave height and zero-crossing period. Then, ECs can be constructed using the inverse first-order reliability method (IFORM). This study adopts alternative models to describe the generalized dependence structure between environmental variables using copulas and discusses the Nataf transformation as a special case. ECs are constructed using measured wave data from moored buoys. Derived design loads are applied on a semisubmersible platform to assess possible differences. In addition, a linear interpolation scheme is utilized to establish a parametric model using short-term extreme tension distribution parameters and wave data, and the long-term tension response is estimated using Monte Carlo simulation. A 3D IFORM-based approach, in which the short-term extreme response that is ignored in the EC approach is used as the third variable, is proposed to help establish accurate design loads with increased accuracy. Results offer a clear illustration of the extreme responses of floating structures based on different models.
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Supported by the National Natural Science Foundation of China under Grant No. 52171284.
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Article Highlights
• In order to identify critical sea states, ECs using various models are constructed.
• A 3D IFORM-based approach considering short-term extreme response is proposed.
• A parametric model to describe the relationship between response and wave data is constructed.
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Liao, Z., Zhao, Y. & Dong, S. Estimating Design Loads for Floating Structures Using Environmental Contours. J. Marine. Sci. Appl. 21, 114–127 (2022). https://doi.org/10.1007/s11804-022-00282-x
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DOI: https://doi.org/10.1007/s11804-022-00282-x