Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Herbert, M.A.Subject: search.filters.subject.Microstructure

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    Study on Mechanical and microstructural characteristics of Friction Stir Welded Aluminium Matrix composite
    (Elsevier Ltd, 2020) Prabhu B, S.R.B.; Shettigar, A.K.; Herbert, M.A.; Rao, S.S.
    Aluminium matrix composites (AMCs) are part of advanced materials, possesses capabilities to serve the present industrial needs due to its superior properties. Potential use of these AMCs in a particular application is limited if it is unable to join properly. In the present study AMCs are prepared by stir casting technique and welded by friction stir welding (FSW) process. FSW is performed using combined threaded and square profiled pin (CTSP). Further the welded joints were examined for microstructure and joint strength. Tensile test indicates that joint efficiency of 97 % is obtained, normal to the weld direction. Compare to the base material the nugget zone of weld region shows higher hardness. The microstructural study reveals that uniform distribution of finer grains are visible at nugget zone. © 2018 Elsevier Ltd.
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    Experimental investigation of joint properties of friction stir welded aluminium matrix composite
    (Elsevier Ltd, 2021) Prabhu B, S.R.; Shettigar, A.; Herbert, M.A.; Rao, S.S.
    The present study is focused on welding of particulate aluminium matrix composites using friction stir welding process and investigating the influence of various process variables on the joint properties. The microstructural study and mechanical behaviors such as tensile strength and hardness of the weld zone were measured. Microstructural studies showed that process variables play pivotal role in refinement of grains. Compared to the top of the weld region, smaller grains were formed at the bottom due to variation in the heating effect. Measurement of the tensile strength and hardness of the weld zone, indicated that process variables plays important role in controlling the joint properties. Beyond the optimum range of process variables, the joint strength of welded part deteriorates due to the insufficient stirring and lack of plasticization leads to defect formation. Joint welded with traverse speed of 100 mm/min and revolution speed of 1200 rpm exhibited better mechanical properties. © 2021 Elsevier Ltd. All rights reserved.
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    A study of microstructure and mechanical properties of friction stir welded joint of Al-Ce-Si-Mg aluminium alloy plates and optimization cum prediction techniques using Taguchi and ANN
    (Elsevier Ltd, 2023) D’Souza, A.D.; Rao, S.S.; Herbert, M.A.
    In the current research work, the effect of friction stir welding (FSW) on joint strength and evolution of microstructure at the weld zone of the friction stir welded of Al-Ce-Si-Mg aluminium alloy (Al10Mg8Ce3.5Si and Al5Mg8Ce3.5Si) is studied. The experimentations demonstrated that the speed of tool revolution, contour of tool pin and tool movement rate have influence on the quality of the FSW joint of the alloy. It was noticed that the size of grains at nugget zone (NZ) depends upon the speed of tool spin, speed, of tool feed, tool pin contour and composition of the aluminium alloy. The grain size at the bottom of the NZ was discovered to be reducing when compared to that at the top of the NZ. It was also noted that highest hardness was reached at NZ. Lowest hardness was found at heat affected zone (HAZ) and most of the tensile specimens fractured at HAZ. The Taguchi orthogonal array-based design has demonstrated that the tool pin contour had the greatest influence in enhancing the joint strength, followed by speed of tool feed, material composition and speed of tool spin. A speed of revolution of tool of 1000 rpm, tool movement rate of 20 mm/min, triangular contour pin (TCP) tool and Al10Mg8Ce3.5Si aluminium alloy were concluded as the optimum variables of the process. The percentage contribution of each one of these input process parameters on optimum output quality characteristics was also found out and noticed to be lying well within the confidence interval of 95% suggested by the Taguchi design. The current study has shown that the prediction results with artificial neural network (ANN) are better compared to those predicted using statistical methods like Taguchi Techniques. © © 2023 Elsevier Ltd. All rights reserved.