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Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm

机译:基于生物地理学的优化算法对Aa6061-T6和Aa7075-T6搅拌摩擦焊工艺参数的多目标优化

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The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon’s entropy.
机译:搅拌摩擦焊(FSW)的发展为快速,可靠地生产高质量焊缝提供了另一种方法。这项研究的重点是AA6061-T6和AA7075-T6铝合金的异种搅拌摩擦焊的力学性能。 FSW过程参数(例如工具转速,工具移动速度,倾斜角和工具偏移)会显着影响搅拌摩擦焊接接头的机械性能。建立了数学回归模型来确定FSW工艺参数与机械性能之间的经验关系,并对结果进行验证。为了获得可同时优化热影响区(HAZ)的极限抗拉强度,伸长率和最小硬度的工艺参数的最优值,提出了一种基于生物地理学的优化的启发式多目标算法。通过使用两种不同的决策技术(通过类似于理想解的优先顺​​序排序技术(TOPSIS)和香农熵),获得了用于三重和双重目标函数的帕累托最优边界,并选择了最佳最优解。

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