Publications

Chojaczyk, A.A., Teixeira, A.P., Neves, L.C., Cardoso, J.B. and Guedes Soares, C. (2015), Review and application of Artificial Neural Networks models in reliability analysis of steel structures, Structural Safety, Vol. 52, pp. 78-89

This paper aims at presenting a survey on the development and use of Artificial Neural Networks (ANN) models in structural reliability analysis. The survey identifies the different types of ANNs, the methods of structural reliability assessment that are typically used, the techniques proposed for ANN training set improvement and also some applications of ANN approximations to structural design and optimization problems. ANN models are then used in the reliability analysis of a ship stiffened panel subjected to uniaxial compression loads induced by hull girder vertical bending moment, for which the collapse strength is obtained by means of nonlinear Finite Element Analysis (FEA). The approaches adopted combine the use of ANN models, to predict the collapse strength of the panel or to approximate directly the limit state function, with Monte Carlo simulation (MCS), First Order Reliability Methods (FORM) and MCS with Importance Sampling (IS), for reliability assessment. A comprehensive comparison of the predictions of the different reliability methods with ANN based LSFs and classical LSF evaluation linked to the FEA is provided.

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