D. Fernández-Fdz

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This article puts forward the results obtained when using a neural network as an alternative to classical methods (simulation and experimental testing) in the prediction of the behaviour of steel armours against high-speed impacts. In a first phase, a number of impact cases are randomly generated, varying the values of the parameters which define the impact(More)
A new tool based on artificial neural networks (ANNs) has been developed for the design of lightweight ceramic metal armours against high velocity impact of solids. The tool devel oped predicts, in real time, the response of the armour: impacting body arrest or target perforation are determined and, in the latter case, the residual mass and velocity of the(More)
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