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RISS 인기검색어
- 검색키워드
- 저자 : P. Gopi Krishnan (검색결과 3 건)
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Study on effect of welding speed on friction stir welded aluminium metal matrix hybrid composite
P. Gopi Krishnan,B. Suresh Babu,S. Madhu,S. J. Gowrishankar,C. Bibin,S. Saran,S. Shree Ram,A. R. Sri Hari,S.Vidyasagar 한양대학교 세라믹연구소 2021 Journal of Ceramic Processing Research Vol.22 No.5
The development of aluminum series matrix hybrid composites with ceramic reinforcements has recently caught the interestof new researchers. The addition of more than one or two reinforcements in aluminium alloy leads to the fabrication of theAluminium Metal Matrix Hybrid Composite (AMMHC). The present investigation is aimed at the development of newlydeveloped AMMHC followed by friction stir welding for obtaining the improved mechanical properties. The stir castedAA6063 with reinforcement of 5%, 10% and 15% wt. Silicon Carbide (SiC) and 10% wt. Boron Carbide (B4C) werefabricated by stir casting technique and the AMMHC with 10% each of SiC and B4C showed higher mechanical properties. Further the AMMHC are joined by friction stir welding (FSW) route. A prime experimental work has been tried out in theFSW process by varying welding speed (20, 30, 40, 50 and 60 mm/min). The effect of welding speed on AMMHCs were studiedon macro and microstructural observations followed by micro hardness and ultimate tensile. Strength, in which 40 mm/minof welding speed gives better properties than other processing condition. The weldment reveals the better joint strength withthe presence of fine particle dispersion in the microstructure.
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P. Gopi Krishnan,B. Suresh Babu,K. Siva 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.2
Friction stir welding (FSW) grabs more attention since the past decade among the researchers worldwide due to its excellentcharacteristics such as no emission of fumes, no filler material, comparatively economical and so on. Friction stir weldingis effectively used in bringing better joint without any appreciable defects in light materials such as Aluminium, Magnesiumetc., Experiments in FSW of materials with high density such as steel, copper alloys etc., have also been tried out. Theselection of proper welding parameters determines a good weldment. In this work, Aluminium matrix hybrid compositewas manufactured through stir casting with the matrix AA7010 and reinforcements SiC and Al2O3. The hybrid compositeworkpieces were subjected to friction stir welding process by varying the process parameters such as tool rotation speed,welding speed and axial force using Taguchi L27 orthogonal array. Tensile strength of FS welded composite was examinedand regression analysis was done. Genetic Algorithm technique was used to optimize the weld tensile strength within thedesign space of 53 = 125 alternatives of parametric combinations. The study focuses on the improvement of the tensilestrength of the welded specimens.
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P. Gopi Krishnan,R. Srinivasan,D. Pritima,A. Bovas Herbert Bejaxhin 한양대학교 청정에너지연구소 2023 Journal of Ceramic Processing Research Vol.24 No.6
Friction stir welding (FSW) is a green manufacturing process that does not liberate smoke, fume and odour unlike the conventionalarc welding. This research article aims at finding the ultimate tensile strength of the Aluminium matrix compositeswelded by FSW with the process parameters such as tool rotation speed, weld traverse speed and axial force. The searchoptimization is carried out in two phases using MATLAB environment. Firstly, the regression equation of the experimentsis utilized to find the better design points by Genetic Algorithm (GA) through pool generation, cross-over and mutation. Secondly, the top design points obtained in GA are stored in a new pool, from which the global best optimal design is selectedby Firefly Algorithm (FA). Since, every algorithm has different features and highlights, the coupled GA-FA algorithm isutilized to obtain the optimal point that gives the best ultimate tensile strength of the welded composite. The results demonstratethat the optimal points are distributed in several points of design space that needs to be searched out by the effectiveoptimization strategy. The convergence rate, speed of the optimization and coverage of the design points are also improved. The algorithm shows good agreement with the confirmation tests also with errors less than 5%.
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