Bivariate extreme value statistics of offshore jacket support stresses in Bohai bay

[+] Author and Article Information
Zhang Jian

Jiangsu University of Science and Technology, Zhenjiang, China

Oleg Gaidai

Jiangsu University of Science and Technology, Zhenjiang, China

Junliang Gao

Jiangsu University of Science and Technology, Zhenjiang, China

1Corresponding author.

ASME doi:10.1115/1.4039564 History: Received May 23, 2017; Revised February 21, 2018


This paper presents a generic Monte Carlo based approach for bivariate extreme response prediction for fixed offshore structures, particularly Jacket type. The bivariate analysis of extremes is often poorly understood and generally not adequately considered in most practical measurements/situations, that is why it is an important to utilize the recently developed bivariate ACER (average conditional exceedance rate) method. According to the current literature study, there is not yet a direct application of the bivariate ACER method to coupled offshore jacket stresses. This study aims at being first to apply bivariate ACER method to jacket critical stresses, aiming at contributing to safety and reliability studies for a wide class of fixed offshore structures. An operating Jacket located in the Bohai bay was taken as an example to demonstrate the proposed methodology. Satellite measured global wave statistics was used to obtain realistic wave scatter diagram in the Jacket location area. Second order wave load effects were taken into account, while simulating Jacket structural response. An accurate finite element ANSYS model was used to model Jacket response dynamics, subject to non-linear hydrodynamic wave and sea current loads. Offshore structure 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, that are simultaneously measured/simulated at two different Jacket locations. Due to less than full correlation between stresses in different critical Jacket locations, application of the multivariate (or at least bivariate) extreme value theory is of practical engineering interest.

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