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

Author:

Gaspar Bruno1,Naess Arvid2,Leira Bernt J.3,Soares C. Guedes1

Affiliation:

1. Centre for Marine Technology and Engineering (CENTEC), Instituto Superior Técnico, Technical University of Lisbon, Lisboa 1049-001, Portugal e-mail:

2. Centre for Ships and Ocean Structures and Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim NO-7491, Norway e-mail:

3. Department of Marine Technology, Norwegian University of Science and Technology, Trondheim NO-7491, Norway e-mail:

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 computational 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.

Publisher

ASME International

Subject

Mechanical Engineering,Ocean Engineering

Reference23 articles.

1. System Reliability Analysis by Enhanced Monte Carlo Simulation;Struct. Safety,2009

2. Reliability Analysis of Large Structural Systems;Probab. Eng. Mech.,2012

3. Approximate Assessment of the Ultimate Longitudinal Strength of the Hull Girder;J. Ship Res.,1996

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