J.G.S. da Silva

An evaluation of the dynamical performance of composite slabs

Abstract The competitive trends of the world market have long been forcing structural engineers to develop minimum weight and labour cost solutions. A direct consequence of this new design trend is a considerable increase in problems related to unwanted floor vibrations. This phenomenon is very frequent in a wide range of structures subjected to rhythmic dynamical load actions. These load actions are generally caused by human rhythmic activities such as: musical and or sporting events, dance or even gymnastics. The main objective of this paper is to investigate the structural behaviour of commonly used composite floors subjected to rhythmic dynamical load actions identifying the occurrence of unwanted vibrations that could cause human discomfort or, in extreme cases, structural failure.

Neural networks assessment of beam-to-column joints

This paper proposes the use of artificial neural networks to predict the flexural resistance and initial stiffness of beam-to-column steel joints using the back propagation supervised learning algorithm. Three types of steel beam-to-column joints were investigated: welded, endplate and bolted with top, seat and double web angles, respectively. The neural networks results proved to be consistent with experimental and design code reference values.

Editorial of - Special Issue

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