| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 237131 | Powder Technology | 2012 | 6 Pages |
Based on the idea of survival of the fittest and natural selection, a class of parallel iterative algorithm with specific learning ability was introduced to find the optimal solidification conditions and produce 2024 Al alloy with minimum wear and maximum strength. This novel algorithm repeats evaluation, selection, crossover and mutation after initialization until the stopping condition is satisfied. Mechanical and wear properties of unreinforced 2024 Al alloy and composites with different vol.% of coated boron carbide particles were also experimentally investigated. It is seen that incorporation of hard particles to 2024 aluminum alloy contributes to the improvement of the mechanical properties and wear resistance of the base alloy to a great extent.
Graphical abstractThe fitness F(x) of each of the chromosome `x' in the population is calculated and the offspring from current population using the three operators namely selection, crossover and mutation is created. The current population is replaced with the new population. This algorithm is repeated to breed next generation.Figure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Mechanical properties of composites were investigated. ► Practical method is presented to model and optimize the tribological properties. ► The combination of FEM, ANN and GA is implemented for modeling of these properties.
