Optimization of Process Parameters for in High-Energy Ball Milling of CNTs/Al2024 Composites Through Response Surface Methodology

The mathematical models are developed to evaluate the ultimate tensile strength( UTS) and hardness of CNTs / Al2024 composites fabricated by high-energy ball milling. The effects of the preparation variables which are milling time,rotational speed,mass fraction of CNTs and ball to powder ratio on UST and hardness of CNTs / Al2024 composites are investigated. Based on the central composite design( CCD),a quadratic model is developed to correlate the fabrication variables to the UST and hardness. From the analysis of variance( ANOVA),the most influential factor on each experimental design response is identified. The optimum conditions for preparing CNTs / Al2024 composites are found as follows: 1. 53 h milling time,900 r / min rotational speed,mass fraction of CNTs 2. 87% and Ball to powder ratio 25 ∶ 1. The predicted maximum UST and hardness are 273.30 MPa and 261.36 HV,respectively. And the experimental values are 283.25 MPa and256.8 HV,respectively. It is indicated that the predicted UST and hardness after process optimization are found to agree satisfactory with the experimental values.     

一种求解车间调度的混合算法

针对流水车间作业调度问题, 提出了一种基于``alldifferent'约束的混合进化算法(Hybrid particle and genetic algorithm, HPGA), 将粒子群算法、遗传操作及模拟退火策略有效地结合在一起. 为了提高算法的求解质量, 引入了一种随机邻域搜索策略. 最后将此算法在不同规模的实例上进行了测试, 并与其他几种最近提出的具有代表性的算法进行了比较. 结果表明, 无论是在求解质量还是收敛速度方面都优于其他几种算法.