Structural reliability analyis of elastic-plastic structures using neural networks and Monte Carlo simulation

 
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1996 (EN)
Structural reliability analyis of elastic-plastic structures using neural networks and Monte Carlo simulation (EN)

Papadopoulos, V (EN)
Papadrakakis, M (EN)
Lagaros, ND (EN)

N/A (EN)

This paper examines the application of Neural Networks (NN) to the reliability analysis of complex structural systems in connection with Monte Carlo Simulation (MCS). The failure of the system is associated with the plastic collapse. The use of NN was motivated by the approximate concepts inherent in reliability analysis and the time consuming repeated analyses required for MCS. A Back Propagation algorithm is implemented for training the NN utilising available information generated from selected elasto-plastic analyses. The trained NN is then used to compute the critical load factor due to different sets of basic random variables leading to close prediction of the probability of failure. The use of MCS with Importance Sampling further improves the prediction of the probability of failure with Neural Networks. (EN)

journalArticle

Elastic plastic structures (EN)
Elasticity (EN)
Random processes (EN)
Monte Carlo Simulation (EN)
Monte Carlo methods (EN)
Plastic collapse (EN)
Importance Sampling (EN)
Probability of Failure (EN)
Reliability Analysis (EN)
Plasticity (EN)
Sampling (EN)
Computer aided analysis (EN)
Importance sampling (EN)
Backpropagation (EN)
Critical Loads (EN)
Critical load factor (EN)
Random Variable (EN)
Failure probability (EN)
Difference Set (EN)
Failure (mechanical) (EN)
Learning algorithms (EN)
Neural Network (EN)
Complex Structure (EN)
Neural networks (EN)
Reliability (EN)
Back Propagation Algorithm (EN)
Structural Reliability (EN)
Structural analysis (EN)

Εθνικό Μετσόβιο Πολυτεχνείο (EL)
National Technical University of Athens (EN)

Computer Methods in Applied Mechanics and Engineering (EN)

English

1996


ELSEVIER SCIENCE SA LAUSANNE (EN)



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