Hybrid Monte Carlo method in the reliability analysis of structures

  • Joanna Kaliszuk University of Zielona Góra


The paper develops the idea of [8], i.e., the application of Artificial Neural Networks (ANNs) in probabilistic reliability analysis of structures achieved by means of Monte Carlo (MC) simulation. In this method, a feed-forward neural network is used for generating samples in the MC simulation. The patterns for network training and testing are computed by a Finite Element Method (FEM) program. A high numerical efficiency of this Hybrid Monte Carlo Method (HMC) is illustrated by two examples of the reliability analysis that refer to a steel girder [4] and a cylindrical steel shell [2].


reliability, Artificial Neural Networks (ANNs), Finite Element Method (FEM), Hybrid Monte Carlo Method (HMC), steel girder, cylindrical steel shell,


Jan 25, 2017
How to Cite
KALISZUK, Joanna. Hybrid Monte Carlo method in the reliability analysis of structures. Computer Assisted Methods in Engineering and Science, [S.l.], v. 18, n. 3, p. 205–216, jan. 2017. ISSN 2299-3649. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/115>. Date accessed: 26 jan. 2022.