Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
3 results
Search Results
Item Microstructural characterization and hardness evaluation of friction stir welded composite AA6061-4.5Cu-5SiC (Wt.%)(Defense Scientific Information and Documentation Centre, 2013) Shettigar, A.K.; Salian, G.; Herbert, M.A.; Rao, S.Recent developments in advanced materials research have led to the emergence of new materials having features like low density, high strength to weight ratio, excellent mechanical properties, heat and corrosion resistance. In friction stir welding (FSW), a non-consumable rotating welding tool is used to generate the frictional heat and plastic deformation of the material in the welding zone, which is in the solid state. The advantages of FSW as compared to the fusion welding are high joint strength, less defect weld, uniform distribution of grain structure in the weld zone and low power consumption. AA6061 with 4.5 % weight of copper and 5 % weight of SiC composite material has been prepared to conduct experiment and carry out characterization, evaluation of the mechanical properties. Micro-structural characterization of the weld zone is carried out by scanning electron microscope (SEM). Evaluation of hardness was also carried out across the weld zone. A successful method for FSW of AA6061-4.5(wt.%) Cu-5(wt.%) SiC has been developed. © 2013, DESIDOC.Item Development of machine learning regression models for the prediction of tensile strength of friction stir processed AA8090/SiC surface composites(Institute of Physics, 2024) Adiga, K.; Herbert, M.A.; Rao, S.S.; Shettigar, A.K.; Vasudeva, T.V.Friction Stir Processing is a state-of-the-art technology for microstructure refinement, material property enhancement, and fabrication of surface composites. Machine learning approaches have garnered significant interest as prospective models for modeling various production systems. The present work aims to develop four machine learning models, namely linear regression, support vector regression, artificial neural network and extreme gradient boosting to predict the influence of FSP parameters such as tool rotational speed, tool traverse speed and groove width on ultimate tensile strength of friction stir processed AA8090/SiC surface composites. These models were developed through Python programming and the original dataset was divided into 80% for the training phase and 20% for the testing phase. The performance of the models was evaluated by root mean squared error, mean absolute error and R2. Based on the results and graphical visualization, it was observed that the XGBoost model outperformed other models with high accuracy in predicting UTS of AA8090/SiC surface composites. © 2024 The Author(s). Published by IOP Publishing Ltd.Item Investigation of the effect of process parameters on the mechanical properties of friction stir additive manufactured (FSAM) AA8090 alloy(Elsevier B.V., 2025) D A P, P.; Shettigar, A.K.; Herbert, M.A.; Korgal, A.; Adiga, K.Friction Stir Additive Manufacturing (FSAM), an emerging technique, falls under the category of sheet lamination additive manufacturing. It employs a layer-by-layer fabrication where all the plates should be flat and of the same size. This process was developed to fabricate near-net-shaped components and refined microstructures. FSAM has been extensively used in the fabrication of aluminum alloys for aerospace applications. In this work, FSAM has been carried out for AA8090 aluminum alloy. AA8090 is the second-generation Al-Li alloy with 2.3 % Li, lightweight, 10 % lower density and 11 % higher modulus than the existing commercial 2014 and 2024 Al alloy. The experiments were carried out at rotational speed (1000 – 2000 rpm), traverse speed (45–55 mm/min) and 1° constant tilt angle. The macrostructure and microstructure analysis were carried out. This was followed by microhardness and tensile test analysis. The microhardness was carried out at nine points on each layer and tensile specimen was made according to ASTM E8 standard. The maximum reduction in grain size, which is 62 %, maximum hardness value 113 HV and maximum tensile value 346.8 MPa were observed at 2000 rpm. The size of the grains decreased from the top layer into the bottom layers. The maximum hardness for all the experiments was observed in the re-stir zone of the specimens. It was concluded that with increase in process parameters, better mechanical and microstructural properties can be achieved. The fractography analysis showed the presence of dimples and tear ridges indicating a ductile fracture. © © 2025. Published by Elsevier B.V.