Browsing by Subject "Explosives"

Now showing 1 - 3 of 3

Open Access
Comparison of terahertz technologies for detection and identification of explosives
(SPIE, 2014-05) Beigang, R.; Biedron, S. G.; Dyjak, S.; Ellrich, F.; Haakestad, M.W.; Hübsch, D.; Kartaloglu, Tolga; Özbay, Ekmel; Ospald, F.; Palka, N.; Puc, U.; Czerwiñska, E.; Sahin, A. B.; Sešek, A.; Trontelj, J.; Švigelj, A.; Altan, H.; Van Rheenen, A.D.; Walczakowski, M.
We present results on the comparison of different THz technologies for the detection and identification of a variety of explosives from our laboratory tests that were carried out in the framework of NATO SET-193 THz technology for stand-off detection of explosives: from laboratory spectroscopy to detection in the field under the same controlled conditions. Several laser-pumped pulsed broadband THz time-domain spectroscopy (TDS) systems as well as one electronic frequency-modulated continuous wave (FMCW) device recorded THz spectra in transmission and/or reflection. © 2014 SPIE.
Open Access
Development of an innovative sandwich composite material for protection of lower limb against landmine explosion: mechanical leg test results
(SAGE Publications Ltd, 2017) Karahan, M.; Karahan, E. A.
This paper includes results of the blast tests which were performed with the aim of comparing the energy absorption and protection efficiency of protective boots with different sole configurations. Tests were performed on a mechanical leg model vestured with protective boots. Load and three axis acceleration values were measured during the blast tests to determine the protection efficiency of boot samples. Herewith, it was understood that merely a monolithic composite layer used in a sole does not provide protection, whereas compressible metallic honeycomb material-based sandwich composites demonstrate better energy absorption. With the innovative sandwich composite material developed in this study, energy absorption was increased by 209% in comparison to monolithic composites. © 2016, © The Author(s) 2016.
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Identification of materials with magnetic characteristics by neural networks
(2012) Nazlibilek, S.; Ege, Y.; Kalender O.; Sensoy, M.G.; Karacor, D.; Sazli, M.H.
In industry, there is a need for remote sensing and autonomous method for the identification of the ferromagnetic materials used. The system is desired to have the characteristics of improved accuracy and low power consumption. It must also autonomous and fast enough for the decision. In this work, the details of inaccurate and low power remote sensing mechanism and autonomous identification system are given. The remote sensing mechanism utilizes KMZ51 anisotropic magneto-resistive sensor with high sensitivity and low power consumption. The images and most appropriate mathematical curves and formulas for the magnetic anomalies created by the magnetic materials are obtained by 2-D motion of the sensor over the material. The contribution of the paper is the use of the images obtained by the measurement of the perpendicular component of the Earth magnetic field that is a new method for the purpose of identification of an unknown magnetic material. The identification system is based on two kinds of neural network structures. The MultiLayer Perceptron (MLP) and the Radial Basis Function (RBF) network types are used for training of the neural networks. In this work, 23 different materials such as SAE/AISI 1030, 1035, 1040, 1060, 4140 and 8260 are identified. Besides the ferromagnetic materials, three objects are also successfully identified. Two of them are anti-personal and anti-tank mines and one is an empty can box. It is shown that the identification system can also be used as a buried mine identification system. The neural networks are trained with images which are originally obtained by the remote sensing system and the system is operated by images with added Gaussian white noises. © 2012 Elsevier Ltd. All rights reserved.