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Genetic algorithm optimization of process parameters for magnetic pulse welded copper–stainless steel tubular joints

Publication Type : Journal Article

Publisher : Journal of Computational and Theoretical Nanoscience

Source : Journal of Computational and Theoretical Nanoscience, vol. 15, no. 8, pp. 2438–2443, 2018

Url : https://www.ingentaconnect.com/content/asp/jctn/2018/00000015/00000009/art00058;jsessionid=2mceqlm18o6h9.x-ic-live-02

Campus : Chennai

School : School of Engineering

Department : Mechanical Engineering

Year : 2018

Abstract : This study attempts to join pure copper and low carbon stainless steel 316L tubes using Magnetic Pulse Welding process. The welding is carried out by varying the welding process parameters; standoff distance, discharge energy and impact angle. Based on the result of the obtained weldability matrix, the parameter combination of the samples resulting in complete circumferential bonding is used to develop Genetic Algorithm based optimization. Genetic Algorithm is used to optimize the process parameters by minimizing the least square error based objective function. Experimental validation is carried out by observing the micro hardness and torsion properties of the joints. Subsequently, microscopic analysis of the samples joined using optimized parameters. The obtained results indicate good agreement between the predicted and experimental parameters

Cite this Research Publication : S. G. Rahul and P. Kavitha, “Genetic algorithm optimization of process parameters for magnetic pulse welded copper–stainless steel tubular joints”, Journal of Computational and Theoretical Nanoscience, vol. 15, no. 8, pp. 2438–2443, 2018

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