Neural network evaluation of steel beam patch load capacity

This work presents a neural network modelling to forecast steel beam patch load resistance. In preceding studies, the results of a neural network system composed of four neural networks, have been compared and calibrated with experimental data and existing design formulae, showing a good agreement....

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Bibliographic Details
Published in:Advances in engineering software (1992) 2003-12, Vol.34 (11), p.763-772
Main Authors: Fonseca, E.T., Vellasco, P.C.G.da S., Andrade, S.A.L.de, Vellasco, M.M.B.R.
Format: Article
Language:English
Subjects:
Neural networks
Parametric analysis
Patch load
Steel structures
Web buckling
Web crippling
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Summary:This work presents a neural network modelling to forecast steel beam patch load resistance. In preceding studies, the results of a neural network system composed of four neural networks, have been compared and calibrated with experimental data and existing design formulae, showing a good agreement. Despite these results, the adopted system did not properly consider the differences in behaviour of slender, intermediate and compact beams. This paper introduces a new strategy based on a single neural network, which is trained with a different normalisation parameter. The neural network presented a maximum error value lower than 30%, while existing formulas presented errors greater than 40%.
ISSN:0965-9978
DOI:10.1016/S0965-9978(03)00104-2