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RISS 인기검색어
- 검색키워드
- 저자 : A. Canakci (검색결과 3 건)
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A. Canakci,T. Varol,S. Ozsahin 대한금속·재료학회 2013 METALS AND MATERIALS International Vol.19 No.3
An artificial neural network (ANN) model was developed to predict the effect of volume fraction, compact pressure and milling time on green density, sintered density and hardness of Al-Al2O3 metal matrix composites (MMCs). Al-Al2O3 powder mixtures with various reinforcement volume fractions of 5, 10, 15%Al2O3 and milling times (0 h to 7 h) were prepared by mechanical milling process and composite powders were compacted at various pressure (300, 500 and 700 MPa). The three input parameters in the proposed ANN were the volume fraction, compact pressure and duration of the milling process. Green density, sintered density and hardness of the composites were the outputs obtained from the proposed ANN. As a result of this study the ANN was found to be successful for predicting the green density, sintered density and hardness of Al-Al2O3 MMCs. The mean absolute percentage error for the predicted values didn’t exceed 5.53%. This model can be used for predicting Al-Al2O3 MMCs properties produced with different reinforcement volume fractions, compact pressures and milling times.
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T. Varol,A. Canakci 대한금속·재료학회 2013 METALS AND MATERIALS International Vol.19 No.6
In this study, Al2024-B4C composites containing 0, 5, 10 and 20 wt% of B4C particles with two different particle sizes (d50=49 μm and d50=5 μm) as reinforcement material were produced by a mechanical alloying method. Two new particle distribution models based on the size of reinforcement materials was developed. The microstructure of the Al2024-B4C composites was investigated using a scanning electron microscope. The effects of reinforcement particle size and weight percentage (wt%) on the physical and mechanical properties of the Al2024-B4C composites were determined by measuring the density, hardness and tensile strength values. The results showed that more homogenous dispersion of B4C powders was obtained in the Al2024 matrix using the mechanical alloying technique according to the conventional powder metallurgy method. Measurement of the density and hardness properties of the composites showed that density values decreased and hardness values increased with an increase in the weight fraction of reinforcement. Moreover, it was found that the effect of reinforcement size and reinforcement content (wt%) on the homogeneous distribution of B4C particles is as important as the effect of milling time.
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T. Varol,A. Canakci 대한금속·재료학회 2015 METALS AND MATERIALS International Vol.21 No.4
In this study, the influence of multilayer graphene content on the green and sintered properties of the multilayer graphene/Copper nanocomposites was investigated. Flake powder metallurgy, as a new production method, was employed to prepare the multilayer graphene reinforced copper matrix nanocomposites. Results showed that the increase in agglomeration content inhibited particle-particle contact during the sintering process and therefore sintered density decreased with increasing the multilayer graphene content. The green density of 8.46 g/cm3 was found for the monolithic Cu sample, which was 16.4% higher than that of the 5 wt% MLG/ Copper nanocomposites. The high conductivity value (78.5 IACs) was obtained with 0.5 wt% the multilayer graphene reinforced nanocomposites. The electrical conductivity of sintered 5 wt% the multilayer graphene/Copper nanocomposites was 61.48 IACs. When the amount of the multilayer graphene particles as higher than 3 wt%, the decreasing rate in hardness significantly increased. The decreasing rate in the hardness of the multilayer graphene/Copper nanocomposites can be attributed to decrease in density and the non-homogeneous distribution of multilayer graphene particulates in Cu matrix.
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