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基于生物地理学优化算法的AA6061-T6和AA7075-T6搅拌摩擦焊工艺参数多目标优化

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

作者信息

Tamjidy Mehran, Baharudin B T Hang Tuah, Paslar Shahla, Matori Khamirul Amin, Sulaiman Shamsuddin, Fadaeifard Firouz

机构信息

Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, 43400 Serdang, Selangor, Malaysia.

Advanced Manufacturing Research Centre, University Putra Malaysia, 43400 Serdang, Selangor, Malaysia.

出版信息

Materials (Basel). 2017 May 15;10(5):533. doi: 10.3390/ma10050533.

Abstract

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.

摘要

搅拌摩擦焊(FSW)的发展提供了一种快速可靠地生产高质量焊缝的替代方法。本研究聚焦于AA6061-T6和AA7075-T6铝合金异种搅拌摩擦焊的力学性能。搅拌摩擦焊工艺参数,如工具转速、工具行进速度、倾斜角度和工具偏移量,对搅拌摩擦焊接头的力学性能有显著影响。建立了一个数学回归模型来确定搅拌摩擦焊工艺参数与力学性能之间的经验关系,并对结果进行了验证。为了获得能同时优化热影响区(HAZ)的极限抗拉强度、伸长率和最小硬度的工艺参数最优值,提出了一种基于生物地理学优化的元启发式多目标算法。通过使用两种不同的决策技术,即理想解相似排序法(TOPSIS)和香农熵,获得了三目标和双目标函数的帕累托最优前沿,并选择了最佳最优解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fbe/5459031/6d9d5c7e8ddb/materials-10-00533-g001.jpg

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