Neural network evaluation of steel beam patch load capacity

Authors:
E. T. Fonseca;P. C. G. da S. Vellasco;S. A. L. de Andrade;M. M. B. R. Vellasco
Affiliations:
Department of Civil Engineering, PUC-RIO-Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil;Department of Structural Engineering, UERJ--State University of Rio de Janeiro, Rio de Janeiro, Brazil;Department of Civil Engineering, PUC-RIO--Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil and Department of Structural Engineering, UERJ--State University of Rio de Janeir ...;Department of Electrical Engineering, PUC-RIO--Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil and Department of Systems Engineering, UERJ--State University of Rio de Jane ...
Venue:
Advances in Engineering Software - Civil-comp 2001
Year:
2003

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Abstract

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%.