In the present work, the surface characteristics of Electrical Discharge Machined (EDM) Al (6351)eSiC and Al (6351)eSiCeB4C composites are investigated. The composites are prepared by employing the conventional stir c...In the present work, the surface characteristics of Electrical Discharge Machined (EDM) Al (6351)eSiC and Al (6351)eSiCeB4C composites are investigated. The composites are prepared by employing the conventional stir casting technique, as it can produce better particle dispersion in the matrix. The detailed experimental study is performed on the composites by varying current (I), duty factor (t), pulse on time (Ton), and the gap voltage (V) in order to analyze the Heat Affected Zone (HAZ) formed in the sub surface and the average crater diameter formed on the machined surface of the composites as an output function. The formation of recast layers, presence of bubbles and the surface texture of the composites at various machining conditions are observed. The results show that the increased Metal Removal Rate (MRR) increases the depth of HAZ and the average crater diameter on the machined area. Further, the addition of B4C particles to the composite produces more surface defect than the AleSiC composite.展开更多
Al-Cu-Mg/B4Cp metal matrix composites with reinforcement of up to 20 wt% were produced using the powder metallurgy technique. The effects of reinforcement ratio, reinforcement size, milling time, and compact pressure ...Al-Cu-Mg/B4Cp metal matrix composites with reinforcement of up to 20 wt% were produced using the powder metallurgy technique. The effects of reinforcement ratio, reinforcement size, milling time, and compact pressure on the density and porosity of the composites reinforced with 0, 5, 10, and 20 wt% B4C particles were studied. Moreover, an artificial neural network model has been developed for the prediction of the effects of the manufacturing parameters on the density and porosity of powder metallurgy Al-Cu-Mg/B4Cp composites. This model can be used for predicting the densification behavior of Al-Cu-Mg/B4Cp composites produced under reinforcement of different sizes and amounts with various milling times and compact pressures. The mean absolute percentage error for the predicted values did not exceed 1.6%.展开更多
文摘In the present work, the surface characteristics of Electrical Discharge Machined (EDM) Al (6351)eSiC and Al (6351)eSiCeB4C composites are investigated. The composites are prepared by employing the conventional stir casting technique, as it can produce better particle dispersion in the matrix. The detailed experimental study is performed on the composites by varying current (I), duty factor (t), pulse on time (Ton), and the gap voltage (V) in order to analyze the Heat Affected Zone (HAZ) formed in the sub surface and the average crater diameter formed on the machined surface of the composites as an output function. The formation of recast layers, presence of bubbles and the surface texture of the composites at various machining conditions are observed. The results show that the increased Metal Removal Rate (MRR) increases the depth of HAZ and the average crater diameter on the machined area. Further, the addition of B4C particles to the composite produces more surface defect than the AleSiC composite.
基金the Karadeniz Technical University Research Fund for financially supporting this research (No: 2010.112.010.4)
文摘Al-Cu-Mg/B4Cp metal matrix composites with reinforcement of up to 20 wt% were produced using the powder metallurgy technique. The effects of reinforcement ratio, reinforcement size, milling time, and compact pressure on the density and porosity of the composites reinforced with 0, 5, 10, and 20 wt% B4C particles were studied. Moreover, an artificial neural network model has been developed for the prediction of the effects of the manufacturing parameters on the density and porosity of powder metallurgy Al-Cu-Mg/B4Cp composites. This model can be used for predicting the densification behavior of Al-Cu-Mg/B4Cp composites produced under reinforcement of different sizes and amounts with various milling times and compact pressures. The mean absolute percentage error for the predicted values did not exceed 1.6%.
