The aim of the present work is to develop a model for simulating double-peak precipitation hardening kinetics in Al-Zn-Mg alloy with the simultaneous formation of different types of precipitates at elevated temperatur...
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The aim of the present work is to develop a model for simulating double-peak precipitation hardening kinetics in Al-Zn-Mg alloy with the simultaneous formation of different types of precipitates at elevated temperatures based on the modified Langer-Schwartz approach. The double aging peaks are present in the long time age-hardening curves of Al-Zn-Mg alloys. The physically-based model, while taking explicitly into account nucleation, growth, coarsening of the new phase precipitations and two strengthening mechanisms associated with particle-dislocation interaction （shearing and bypassing）, was used for the analysis of precipitates evolution and precipitation hardening during aging of Al-Zn-Mg alloy. Model predictions were compared with the measurements of Al-Zn-Mg alloy. The systematic and quantitative results show that the predicted hardness profiles of double peaks via adding a shape dependent parameter in the growth equation for growth and coarsening generally agree well with the measured ones. Two strengthening mechanisms associated with particle-dislocation interaction （shearing and bypassing） were considered operating simultaneously in view of the particle size-distribution. The transition from shearing to bypassing strengthening mechanism was found to occur at rather early stage of the particle growth. The bypassing was found to be the prevailing strengthening mechanism in the investigated alloys.
针对在蚁群算法中初始参数设置对算法收敛性能的影响较大,提出了一种新的改进蚁群算法NACA(new ant colony algorithm),针对蚁群算法中的四个关键参数随机编码,得到初始的染色体,从而获得一组较优解;再利用遗传算法的优点对上一步的结...
详细信息
针对在蚁群算法中初始参数设置对算法收敛性能的影响较大,提出了一种新的改进蚁群算法NACA(new ant colony algorithm),针对蚁群算法中的四个关键参数随机编码,得到初始的染色体,从而获得一组较优解;再利用遗传算法的优点对上一步的结果单点顺序交叉、对换变异、选择操作以产生更好的解;然后以这组数据为蚁群算法下一次的工作备选值,并进行最大次数的循环迭代直至停止,即求得参数组合的近似最优解。将它应用于网格系统任务调度中,系统的性能得到了明显的改善。仿真模拟结果表明,所提出的算法具有更短的调度长度和更宽的适应性,当任务已知时,执行时间约缩短了21.7%,且负载变化时对网格中各处理器资源的影响大大减小。
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