کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
236314 | 465668 | 2013 | 5 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Computational modeling of cast aluminum 2024 alloy matrix composites: Adapting the classical algorithms for optimal results in finding multiple optima Computational modeling of cast aluminum 2024 alloy matrix composites: Adapting the classical algorithms for optimal results in finding multiple optima](/preview/png/236314.png)
• Al alloyed with Cu and Si has been used as the matrix material.
• The composites had greater wear resistances than the Al alloy.
• NN-FPSO algorithm was used to optimize the process.
Many processing techniques have been developed successfully to manufacture metal matrix composites on the commercial scale. The most simplified approach to develop near net shaped aluminum based composites is by liquid metallurgy route as it is economical and can result in mass production. This research focuses on the performance of NN-FPSO for optimization of the parameters in processing metal matrix composites. The concept of the near-neighbor effect is integrated into the force-imitated mechanism and then applied into the PSO algorithm to improve its ability of locating multiple optima on MOPs. In this approach, a new information-sharing scheme is adopted. Each particle iteratively samples a region conducted by a compound acceleration vector, which is composed of the difference between the particle and its personal best position, attraction acceleration, and repulsion acceleration.
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Journal: Powder Technology - Volume 249, November 2013, Pages 77–81