Efficient optimum solution for high strength Al alloys matrix composites

被引:61
作者
Tofigh, Ali Asghar [1 ]
Shabani, Mohsen Ostad [1 ]
机构
[1] MERC, Tehran, Iran
关键词
Aluminum; B4C; Wear; PARTICLE SWARM OPTIMIZATION; ABRASIVE WEAR BEHAVIOR; CAST A356 ALLOY; MECHANICAL-PROPERTIES; ARTIFICIAL NEURONS; MICROSTRUCTURE; PERFORMANCE; PREDICTION; INTELLIGENCE; MODEL;
D O I
10.1016/j.ceramint.2013.02.097
中图分类号
TQ174 [陶瓷工业]; TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
This papers describes a search technique to optimize the fabrication process conditions of the high wear resistance Al alloy matrix composites reinforced with different volume percentages of boron carbide particles. An experimental investigation was then carried out on the abrasive wear behavior of the composites in terms of abrasive particle size, weight fraction and applied load in pin-on-disc type of wear machine. Particle swarm optimization suffers from premature convergence problems when applied to high-dimensional problems, which results in a low optimization precision or even failure. In this study, a self-organizing hierarchical particle swarm optimizer based on the shrinking strategy is introduced for high dimensional function processing optimization of Al matrix composites in order to avoid the premature convergence effectively. (C) 2013 Elsevier Ltd and Techna Group S.r.l. All rights reserved.
引用
收藏
页码:7483 / 7490
页数:8
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