System Reliability Analysis by Monte Carlo Based Method and Finite Element Structural Models

Abstract

In principle, the reliability of complex structural systems can be accurately predicted by Monte Carlo simulation. This method has several attractive features for structural system reliability, the most important being that the system failure criterion is usually relatively easy to check almost irrespective of the complexity of the system. However, the computa tional cost involved in the simulation may be prohibitive for highly reliable structural systems. In this paper a new Monte Carlo based method recently proposed for system reliability estimation that aims at reducing the computational cost is applied. It has been shown that the method provides good estimates for the system failure probability with reduced computational cost. In a numerical example the usefulness and efficiency of the method to estimate the reliability of a system represented by a nonlinear finite element structural model is presented. To reduce the computational cost involved in the nonlinear finite element analysis the method is combined with a response surface model.

Review and application of Artificial Neural Networks models in reliability analysis of steel structures

“…The method is tested to predict failure probability of a stiffened steel panel using the ANN to directly approximate the LSF. This approach is very simple and easy to implement in standard software packages, including Matlab [21].…”

“…The ship was designed according to Common Structural Rules for Double Hull Oil Tankers [60]. The adopted model was previously considered by Hørte et al [61] in the development of codes for structural design of ships and later by Gaspar et al [62], [21] in structural reliability studies. Frequent studies of this type of elements are due to the fact that it is a basic element of a manifold of civil and marine structures.…”

“…The probabilistic models adopted for the geometrical and material properties of the structural element are well described in the literature [66] and were used in previous studies [21]. The design amplitudes of the welding induced imperfections correspond to the 95 th percentile and the coefficient of variation (COV) is assumed as equal 0.50.…”

“…The peak values over the reference time period (Tr) of 1 year are then described by the Gumbel distribution. Table 4 shows the stochastic models for load basic random variables, more details can be found in [61] and [21]. The compressive loading on the stiffened plate of the ship deck is calculated from the total vertical bending moment and the mid-ship section modulus at deck equal to Z = 41.1 m 3 , for the intact scantlings and Z = 37.3 m 3 , for the corroded scantlings.…”

“…Gaspar, et al [21] have combined a response surface approach with a Monte Carlo based simulation method to efficiently solve structural system reliability problems that involve nonlinear finite element analysis.…”