Abstract

Recently, a new issue in the design of spot-welded structures has been economical prediction of a fatigue design criterion without additional fatigue tests. In general, the most typical and traditional method is the use of a Δ P- Nf curve. However, since the fatigue data on the curve vary according to welding conditions, materials, geometry and fatigue loading conditions, it is necessary to perform an additional fatigue test in order to determine a new fatigue design criterion for a spot-welded lap joint of different dimensions and geometry. This is, of course, a very time consuming and costly task. Thus, in this paper, an economical and advanced design method is proposed, the reliability and performance of which have been verified with the theory of the Weibull probability distribution. As a mechanical parameter to predict the fatigue design criterion, a maximum stress equation has been defined using artificial neural networks. By using the maximum stress equation and the fatigue data previously obtained from fatigue tests, a reasonable fatigue design criterion for a spot-welded lap joint could be predicted without any additional fatigue tests. The results predicted by this method showed very good agreement with actual fatigue data

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