Neural network evaluation of steel beam patch load capacity |
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Authors: | E. T. Fonseca P. C. G. da S. Vellasco S. A. L. de Andrade M. M. B. R. Vellasco |
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Affiliation: | 1. Universidad Nacional de Colombia, Facultad de Minas Sede Medellín, Departamento de Ingeniería Civil, A.A. 75267 Medellín, Colombia;2. Universidad del Bío-Bío, Departamento Ingeniería Civil y Ambiental, Avenida Collao 1202, Concepción, Código Postal 4051381, Concepción, Chile |
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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%. |
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Keywords: | Patch load Steel structures Neural networks Parametric analysis Web buckling Web crippling |
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