Abstract

This study presents novel reliability-based technique, being especially useful for lifetime assessment of multi-dimensional dynamic systems, consisting of cross-correlated components, that have been either measured, or numerically simulated over representative time span. This study has potential applications within wide range of marine structural systems design, where reliability analysis is required. As demonstrated in this study, it is possible to accurately forecast risks of a system failure due to excessive structural responses. Furthermore, time series-based traditional reliability techniques do not always manage system's high-dimensionality, along with complex cross-correlations between different system components. When sailing in harsh weather, cargo ships are exposed to structural damage risks, this study used operating cargo vessel as an underlying example. Another serious safety concern for modern ship trans-Atlantic navigation is the potential loss of cargo, due to the ship's violent movements. Simulating such a situation is quite challenging, due to waves and ship motions being both non-stationary and highly nYar. Validity of laboratory tests may also be questioned, hence, on-board data, gathered from actual cargo ships during their trans-Atlantic voyages, under realistic storms gives a unique research opportunity.Novel Monte Carlo based multi-dimensional reliability method, based on-board measurements is presented in this study. Advocated methodology can be applied to a large variety of complex sustainable marine systems, that are designed to endure environmental loadings for the entire length of their planned service life. This study's approach offers the opportunity to robustly and accurately evaluate operational risks of an entire nonlinear multidimensional dynamic system.

Full Text
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