Abstract
Abstract In this paper, the Moth Flame Optimization (MFO) algorithm is applied to optimize the strain compensated Arrhenius constitutive model of a hybrid nanocomposite of aluminum alloy. The hybrid nano-sized particle reinforcement of SiC and B4C combination of 3% by weight is added to the high strength aluminum alloy using an argon gas assisted stir casting process. To obtain the experimental flow behavior data, one-hit hot compression tests are carried out up to 0.5 strain with strain rates of 0.001 s−1, 0.01 s−1, 0.1 s−1 and 1 s−1 and processing temperatures in the range of 573 K to 773 K. The optimized model is found to exhibit an improved R-square value of 0.9952 over 0.9704, while reducing the root mean squared error value from 10.82 to 5.101.
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