TY - JOUR
T1 - Optimizing Properties of Aluminum-Based Nanocomposites by Genetic Algorithm Method
TT - بهینهسازی خواص نانوکامپوزیت زمینه آلومینیم به روش الگوریتم ژنتیک
JF - iut-jame
JO - iut-jame
VL - 34
IS - 2
UR - http://jame.iut.ac.ir/article-1-666-en.html
Y1 - 2015
SP - 19
EP - 30
KW - Optimization
KW - Elastic Properties
KW - Nanocomposite
KW - Molecular Dynamics
KW - Genetic Algorithm
N2 - 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 Young’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.
M3 10.18869/acadpub.jame.34.2.19
ER -