System reliability analysis of a stiffened panel under combined uniaxial compression and lateral pressure loads

A system reliability analysis of an oil tanker bottom component which consists of a stiffened panel under combined uniaxial compression and lateral sea pressure loads is presented in this paper. The stiffened panel is idealized as a structural system composed by several stiffeners with attached plating in parallel. The structural capacity of each stiffener with attached plating or system component is described by a nonlinear finite element model, considering as failure criterion the buckling collapse under the combined uniaxial compression and lateral sea pressure loads. These load components are defined considering a typical seagoing operational condition of the oil tanker in ballast load. The uncertainty in the relevant design basic variables is quantified using stochastic models proposed in the literature. To efficiently solve the structural system reliability problem a Monte Carlo based reliability estimation method recently proposed is combined with a response surface method. The combination of these two methods has been shown to be an efficient technique to solve structural system reliability problems that involve computationally demanding numerical models to describe the structural capacity of the system components. Annual probabilities of buckling collapse failure of the stiffened panel are estimated using this solution technique. The effect of corrosion on the stiffened panel reliability is quantified. The importance of considering the lateral sea pressure and correlation between the local and global wave-induced loads in the reliability problem are evaluated.

► A system reliability analysis of a stiffened panel under combined loads is presented.
► Local failure of the stiffened panel due to buckling collapse is considered.
► The structural capacity is assessed through nonlinear finite element analysis.
► A new Monte Carlo based simulation method is combined with a response surface method.
► The combination of the two methods has shown to be an efficient solution technique.