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Optimization of the EMS process parameters in compocasting of high-wear-resistant Al-nano-TiC composites

机译:高耐磨Al-nano-TiC复合材料复合铸造中EMS工艺参数的优化

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摘要

Understanding of the electromagnetic stirrer (EMS) process parameters-wear relation in nanocomposite is required for further creation of tailored modifications of process in accordance with the demands for various applications. This study depicts the performance of hybrid algorithm for optimization of the parameters in EMS compocasting of nano-TiC-reinforced Al-Si alloys. Adaptive neuro-fuzzy inference system (ANFIS) coupled with particle swarm optimization (PSO) was applied to find the optimum combination of the inputs including mold temperature, mix time, impeller speed, powder temperature, cast temperature and average particle size. The optimized condition was obtained in minimization of objective function. The objective function is calculated by ANFIS and then minimized by PSO. The optimized parameters were used to produce semisolid cast aluminum matrix composites reinforced with nano-TiC particles. The optimized nanocomposites were then studied for their tribo-logical properties.
机译:必须了解纳米复合材料中的电磁搅拌器(EMS)工艺参数-磨损关系,才能根据各种应用需求进一步创建定制的工艺修改方案。这项研究描述了纳米TiC增强的Al-Si合金的EMS复合铸造中优化参数的混合算法的性能。自适应神经模糊推理系统(ANFIS)与粒子群优化(PSO)结合使用,以找到输入的最佳组合,包括模具温度,混合时间,叶轮速度,粉末温度,铸造温度和平均粒度。在最小化目标函数的情况下获得了最佳条件。目标函数由ANFIS计算,然后由PSO最小化。优化的参数用于生产用纳米TiC颗粒增强的半固态铸造铝基复合材料。然后研究了优化的纳米复合材料的摩擦学性能。

著录项

  • 来源
    《Applied Physics》 |2016年第2期|457.1-457.14|共14页
  • 作者单位

    Department of Mechanical Engineering, Faculty of Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Isfahan, Iran;

    Department of Mechanical Engineering, Faculty of Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Isfahan, Iran;

    Iran University of Industries and Mines (IUIM), Tehran, Iran;

    Department of Mechanical Engineering, McMaster University, Hamilton, ON, Canada;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
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