Prediction of the response under impact of steel armours using a multilayer perceptron |
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Authors: | A. García-Crespo B. Ruiz-Mezcua D. Fernández-Fdz R. Zaera |
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Affiliation: | (1) Computer Science Department, University Carlos III of Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain;(2) Department of Continuum Mechanics and Structural Analysis, University Carlos III of Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain;(3) Research Institute “Pedro Juan de Lastanosa”, University Carlos III of Madrid, Avda. de la Universidad 30, 28911 Leganés, Madrid, Spain |
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Abstract: | 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 problem (radius, length and velocity of the projectile; thickness of the protection). After simulation of each case using a finite element code, the above-mentioned parameters and the results of the simulation (residual velocity and residual mass of the projectile) are used as input and output data to train and validate a neural network. In addition, the number of training cases needed to arrive at a given predictive error is studied. The results are satisfactory, this alternative providing a highly recommended option for armour design tasks, due to its simplicity of handling, low computational cost and efficiency. |
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Keywords: | Neural network Numerical simulation Steel armour Ballistic impact |
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