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@article{fu_monitoring_2020, title = {Monitoring and modeling of environmental load considering dependence and its impact on the failure probability}, volume = {199}, issn = {0029-8018}, url = {http://www.sciencedirect.com/science/article/pii/S0029801820300858}, doi = {10.1016/j.oceaneng.2020.107008}, abstract = {Extreme weather conditions put heavy environmental loads on systems and may cause catastrophic failure. Classification societies such as Lloyd's Register, DNV GL and the American Bureau of Shipping recommend methods for environmental load calculations. These methods do not consider dependencies among parameters when calculating environmental loads. This paper proposes a novel methodology to consider the copula-based bivariate failure function to evaluate the dependence structure of parameters and minimize uncertainty in load calculations. It also presents a robust operational failure assessment model that considers real-time environmental parameters along with their dependencies. The proposed methodology and models are tested on a semi-submersible mobile unit (SMU). The failure probability corresponding to the wind and wave loads imposed on the SMU is calculated using a physical reliability model and Bayesian network. The copula-based bivariate failure function defines the dependence using the parameters δ, which are estimated using maximum likelihood estimation. A detailed case study illustrates the advantage of the proposed methodology. The proposed method is of vital significance to developing a safe operating envelope for offshore assets likely to face extreme weather conditions.}, language = {en}, urldate = {2020-02-19}, journal = {Ocean Engineering}, author = {Fu, Jinjie and Khan, Faisal}, month = mar, year = {2020}, keywords = {Copula function, Dependence, Environmental loads, Maximum likelihood estimation, Operational failure}, pages = {107008}, }