MODELING AND OPTIMIZING THE TENSILE BEHAVIOR OF DEVELOPED ALUMINUM HYBRID COMPOSITE

Abstract

Aluminum and its alloy are versatile metal materials engaged in various applications based on their high strength, corrosion resistance and light weight. However, there are many limitations to its applications when compared with steel. In a bid to improve on the properties, aluminum composites are developed. In this study, Al 6111 composite was developed by the blend of silica and bamboo leaf ash (BLA) as reinforcement employing stir casting process. The input factors for the experiment were silica dosage (A), BLA proportion (B) and stirring temperature (C). The experimental design was carried out via Box Behnken design of the response surface methodology. Composites were fabricated through stir casting process by varying the inputs according to the dictations of the experimental runs. Parameters evaluated are yield strength, ultimate tensile strength, elastic modulus and elongation. Result of the ANOVA analysis showed that the parameters had consequential effect on the response and the developed model for each parameter are fit for predictions. From the surface plot, interaction between 5[Formula: see text]wt.% and 10[Formula: see text]wt.% silica and 2[Formula: see text]wt.% and 4[Formula: see text]wt.% BLA led to improvement in yield, ultimate tensile strength but decrease in elongation even as proportions 10[Formula: see text]wt.% and 15[Formula: see text]wt.% silica and 4[Formula: see text]wt.% and 6[Formula: see text]wt.% BLA ensued reduction in the value. Stirring temperature of 700–800∘C is favorable to the strength parameters while 800–900∘C led to strength reduction. Optimization via response surface, predicted optimum conditions of 11.6249[Formula: see text]wt.%, 3.95707[Formula: see text]wt.% and 789.033∘C for A, B and C, respectively. Predicted values for yield strength, ultimate tensile strength, elastic modulus and elongation are 278.26[Formula: see text]MPa, 378.24[Formula: see text]MPa, 97.7885[Formula: see text]GPa and 10.132%, respectively. Validation experiment was carried out at the optimum condition and the deviation in parameters between the predicted and validated values is [Formula: see text]. Hence, the models are statistically fit for property predictions.