Neural Network Based Identification of Material Model Parameters to Capture Experimental Load-deflection Curve

D. Novák, D. Lehký


A new approach is presented for identifying material model parameters. The approach is based on coupling stochastic nonlinear analysis and an artificial neural network. The model parameters play the role of random variables. The Monte Carlo type simulation method is used for training the neural network. The feasibility of the presented approach is demonstrated using examples of high performance concrete for prestressed railway sleepers and an example of a shear wall failure. 


Neural network; nonlinear fracture mechanics; Latin Hypercube Sampling; identification

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ISSN 1210-2709 (Print)
ISSN 1805-2363 (Online)
Published by the Czech Technical University in Prague