RT - Journal Article
T1 - Optimizing Properties of Aluminum-Based Nanocomposites by Genetic Algorithm Method
JF - iut-jame
YR - 2015
JO - iut-jame
VO - 34
IS - 2
UR - http://jame.iut.ac.ir/article-1-666-en.html
SP - 19
EP - 30
K1 - Optimization
K1 - Elastic Properties
K1 - Nanocomposite
K1 - Molecular Dynamics
K1 - Genetic Algorithm
AB - Based on molecular dynamics simulation results, a model was developed for determining elastic properties of aluminum nanocomposites reinforced with silicon carbide particles. Also, two models for prediction of density and price of nanocomposites were suggested. Then, optimal volume fraction of reinforcement was obtained by genetic algorithm method for the least density and price, and the highest elastic properties. Based on optimization results, the optimum volume fraction of reinforcement was obtained equal to 0.44. For this optimum volume fraction, optimum Youngâ€™s modulus, shear modulus, the price and the density of the nanocomposite were obtained 165.89 GPa, 111.37 GPa, 8.75 $/lb and 2.92 gr/cm3, respectively.
LA eng
UL http://jame.iut.ac.ir/article-1-666-en.html
M3 10.18869/acadpub.jame.34.2.19
ER -