Design prognostics for 4400 TEU container vessel by multi-variate Gaidai reliability approach

Abstract

This case study introduces an innovative multivariate methodology for assessing the lifetime of marine engineering systems, specifically in cargo vessel transportation. The analysis focused on stress data collected onboard a 4400 TEU container vessel during multiple trans-Atlantic voyages. One of the major challenges in marine cargo transport lies in mitigating the risk of container loss due to excessive whipping loads. Accurate prediction of extreme stress levels on vessel deck panels remains difficult, primarily because of the nonlinear and non-stationary nature of wave and ship motion interactions. Higher-order dynamic effects, such as second- and third-order responses, often become significant when ships operate under adverse environmental conditions, amplifying nonlinear influences. Laboratory simulations, constrained by wave characteristics and scale similarity issues, may not always provide reliable results. Consequently, data collected from vessels navigating extreme weather conditions serves as a critical resource for comprehensive container ship risk assessment. The primary goal of this study was to validate and demonstrate the effectiveness of a novel multivariate risk evaluation approach, leveraging onboard measurements of dynamic areal pressure on cargo ship deck panels as the core dataset. The Gaidai methodology for multivariate risk evaluation proved to be a robust tool for assessing failure, hazard, and damage risks in complex, nonlinear vessel deck panel and ship hull stress systems.