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EKİCİ, BÜLENT

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EKİCİ

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BÜLENT

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    PublicationOpen Access
    Ballistic behavior of high hardness perforated armor plates against 7.62 mm armor piercing projectile
    (ELSEVIER SCI LTD, 2014-11) EKİCİ, BÜLENT; Kilic, Namik; Bedir, Said; Erdik, Atil; Ekici, Bulent; Tasdemirci, Alper; Guden, Mustafa
    In this paper, some of the important defeating mechanisms of the high hardness perforated plates against 7.62 x 54 armor piercing ammunition were investigated. The experimental and numerical results identified three defeating mechanisms effective on perforated armor plates which are the asymmetric forces deviates the bullet from its incident trajectory, the bullet core fracture and the bullet core nose erosion. The initial tests were performed on the monolithic armor plates of 9 and 20 mm thickness to verify the fidelity of the simulation and material model parameters. The stochastic nature of the ballistic tests on perforated armor plates was analyzed based on the bullet impact zone with respect to holes. Various scenarios including without and with bullet failure models were further investigated to determine the mechanisms of the bullet failure. The agreement between numerical and experimental results had significantly increased with including the bullet failure criterion and the bullet nose erosion threshold into the simulation. As shown in results, good agreement between Ls-Dyna simulations and experimental data was achieved and the defeating mechanism of perforated plates was clearly demonstrated. (C) 2014 Elsevier Ltd. All rights reserved.
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    PublicationOpen Access
    Determination of penetration depth at high velocity impact using finite element method and artificial neural network tools
    (ELSEVIER SCIENCE BV, 2015-06) EKİCİ, BÜLENT; Kilic, Namik; Ekici, Bulent; Hartomacioglu, Selim
    Determination of ballistic performance of an armor solution is a complicated task and evolved significantly with the application of finite element methods (FEM) in this research field. The traditional armor design studies performed with FEM requires sophisticated procedures and intensive computational effort, therefore simpler and accurate numerical approaches are always worthwhile to decrease armor development time. This study aims to apply a hybrid method using FEM simulation and artificial neural network (ANN) analysis to approximate ballistic limit thickness for armor steels. To achieve this objective, a predictive model based on the artificial neural networks is developed to determine ballistic resistance of high hardness armor steels against 7.62 mm armor piercing ammunition. In this methodology, the FEM simulations are used to create training cases for Multilayer Perceptron (MLP) three layer networks. In order to validate FE simulation methodology, ballistic shot tests on 20 mm thickness target were performed according to standard Stanag 4569. Afterwards, the successfully trained ANN(s) is used to predict the ballistic limit thickness of 500 HB high hardness steel armor. Results show that even with limited number of data, FEM-ANN approach can be used to predict ballistic penetration depth with adequate accuracy. Copyright (C) 2015, China Ordnance Society. Production and hosting by Elsevier B.V. All rights reserved.