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Pages 200-211 http://dx.

Use of nanocomposites is increasing rapidly due to their enhanced thermal and structural properties. In the present work, the numerical modelling of nanocomposites is conducted with the help of the (GA) genetic algorithm and (FD) finite difference techniques to find out a set of nanocomposites with best thermal and structural properties. The genetic algorithm is utilized to find out the best set of nanocomposites on the basis of thermal and structural properties while the finite difference technique is utilized to solve the heat conduction equation. Different nanocomposites considered in the present work are Al-B4C, Al-SiC and Al-Al2O3. The weight percentage of these nanocomposites is varied to see its effect on the nanocomposites properties. In the end, the solidification curve for all the nanocomposites is plotted and analysed. Result reveals that GA helps in identifying the best set of nanocomposites while FD technique helps in predicting the solidification curve accurately. Increment in the wt. % of nanocomposites makes the solidification curve steeper.