Cargo vessel coupled deck panel stresses reliability study. (15th January 2023) - Gaidai, Oleg; Xu, Jingxiang; Xing, Yihan; Hu, Qingsong; Storhaug, Gaute; Xu, Xiaosen; Sun, Jiayao
Abstract: Classic reliability methods, dealing with time series, do not have the advantage of dealing efficiently with system high dimensionality and cross-correlation between different dimensions. This study validates a novel structural reliability method suitable for multi-dimensional structural responses versus a well-established bivariate statistical method. An example of this reliability study was a chosen container ship subjected to large deck panel stresses during sailing. The risk of losing containers due to extreme motions is the primary concern for ship transport. Due to the non-stationarity and complicated nonlinearities of both waves and ship motions, it is challenging to model such a phenomenon. In the case of extreme motions, the role of nonlinearities dramatically increases, activating effects of second and higher order. Moreover, laboratory tests may also be questioned. Therefore, data measured on actual ships during their voyages in harsh weather provides a unique insight into statistics of ship motions. This work aims to benchmark and validate state of the art method, which makes it possible to extract the necessary information about the extreme response from onboard measured time histories. The method proposed in this paper opens up the possibility of predicting simply and efficiently failure probability for the nonlinear multi-dimensional dynamic system as a whole. Graphical abstract: Study validates novel structural reliability Gaidai-Fu-Xing method, suitable for multi-dimensional structural responses, versus well established bivariate statistical method. Classic reliability methods, dealing with time series do not have an advantage of dealing easily with system high dimensionality and cross-correlation between different dimensions.As an example for this reliability study was chosen container ship subjected to large deck panel stresses occurring during sailing. Risk of losing containers due to extreme motions is primary concern for ship transport. Due to non-stationarity and complicated nonlinearities of both waves and ship motions, it is challenging to model such a phenomenon. In case of extreme motions, the role of nonlinearities dramatically increases, activating effects of second and higher order. Moreover, laboratory tests may also be questioned. Therefore, data measured on actual ships during their voyages in harsh weather provides a unique insight into statistics of ship motions.The aim of this work is to benchmark and validate state of art method, which makes it possible to extract the necessary information about the extreme response from onboard measured time histories. The method proposed in this paper opens up the possibility to predict simply and efficiently failure probability for nonlinear multi-dimensional dynamic system as a whole. Image 1 Highlights: Novel reliability method for marine MDOF dynamic systems is introduced. Real measured onboard cargo vessel data was used.