搅拌铸造铝复合材料的硬度与增强Al2O3颗粒的大小和质量分数的关系

J. Petrović, S. Mladenović, A. Ivanović, I. Marković, S. Ivanov
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摘要

本文采用搅拌铸造法制备了以ane6061合金为基体,Al2O3颗粒为增强剂的复合材料。复合材料是一种重要的工程材料。因此,有必要对其生产方法及影响其力学性能的因素进行详细的研究。为此,我们与ASM International进行了一项有计划的实验,目的是利用回归分析来预测粒径和质量分数对得到的复合材料硬度的影响。采用双因素全因子试验设计,在三个水平上进行分析。硬度作为系统响应,粒径和质量分数作为影响因素。在粒径50、80和110 μ m以及质量% 2、5和8三个水平上观察影响因素。复合材料的测量硬度值在72 HV10到80 HV10之间。根据概率值(p<0.05)确定哪些因素对系统响应重要。统计分析表明,影响因素(增强颗粒尺寸和质量分数)的线性项和质量分数的平方项对硬度变化具有统计学意义。粒径的平方项和影响参数的相互作用项对硬度值的预测没有统计学意义。因此,通过回归分析得到二阶多项式模型。通过方差分析(ANOVA)确定输入因素对系统响应的影响以及所获得的数学模型的充分性。通过统计数据分析,得出颗粒质量分数相对于颗粒尺寸对复合材料硬度的影响较大。通过实验值与预测值的比较,获得了高度的一致性,因此所选择的析因实验模型是适当的(R2=0.989)。建立的回归模型可以在一定的粒径和质量分数变化区间内预测Al2O3颗粒增强铝复合材料的硬度。
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Correlation of hardness of aluminum composites obtained by stir casting technology and the size and weight fraction of reinforcing Al2O3 particles
In this work, the stir casting method was applied to obtain composites based on the alloy AN EW 6061 used as a metal base, and Al2O3 particles as a reinforcement. Composites play a significant role as engineering materials. Therefore, it is necessary to study, in detail, the production methods and the factors that affect their mechanical properties. For this purpose, we have carried out a planned experiment wi ASM International th the aim to use regression analysis to predict the influence of particle size and mass fraction on hardness of the obtained composites. The full factorial experimental design with two factors was used, which was analyzed at three levels. Hardness was observed as a system response, while particle size and mass fraction were set as influencing factors. Influencing factors were observed at three levels: 50, 80 and 110 ?m for the particle size and 2, 5 and 8 mass%. Measured hardness values of the composites ranged from 72 HV10 to 80 HV10. Based on the probability values (p<0.05), it was determined which factors are important for the system response. Statistical analysis has shown that linear terms of the influence factors (size and mass fraction of reinforcement particles) and the square term of the mass fraction have statistical significance on the hardness change. The square term of the particle size and the interaction term of the influencing parameters do not have a statistically significant contribution in predicting the hardness value. Thus, a second-order polynomial model was obtained by the regression analysis. Influence of input factors on the system response and the adequacy of the obtained mathematical model were determined by using the Analysis of Variance (ANOVA). Based on the statistical data analysis, it was established that, the particle mass fraction has a greater influence on hardness of the obtained composite in relation to the particle size. By comparing the experimental and predicted values, a high degree of agreement was achieved so that the chosen model of the factorial experiment was adequate (R2=0.989). It can be also concluded that the developed regression model can be applied to predict hardness of the aluminum composite reinforced by Al2O3 particles in the chosen variation interval of particle size and mass fraction.
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