C
C. Sathiya Narayanan
Researcher at National Institute of Technology, Tiruchirappalli
Publications - 53
Citations - 824
C. Sathiya Narayanan is an academic researcher from National Institute of Technology, Tiruchirappalli. The author has contributed to research in topics: Formability & Forming limit diagram. The author has an hindex of 16, co-authored 53 publications receiving 620 citations. Previous affiliations of C. Sathiya Narayanan include J. J. College of Engineering and Technology.
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Analysis of Form Tolerances in Electrical Discharge Machining Process for Inconel 718 and 625
TL;DR: An experimental work and investigation on electrical discharge machining (EDM) of Inconel 718 and 625 superalloys is presented in this article, where the significance of input parameters namely peak current, pulse-on time, and pulse-off time (T off) on the form tolerances were investigated.
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Optimization of EDM process parameters in machining Si 3 N 4 –TiN conductive ceramic composites to improve form and orientation tolerances
TL;DR: In this article, the electric discharge machining (EDM) of a Si 3 N 4 -TiN composite using a copper electrode as the EDM tool was investigated using a Taguchi L 25 orthogonal array.
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Optimization of EDM Parameters on Machining Si3N4–TiN Composite for Improving Circularity, Cylindricity, and Perpendicularity
TL;DR: In this article, the current, pulse on time (Ton), pulse off time (Toff), and dielectric flushing pressure (DP) are considered sparking parameters for the machining of a Si3N4-TiN composite.
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Some aspects on fracture limit diagram developed for different steel sheets
TL;DR: In this article, the average size of voids developed at fracture under various conditions were measured using the fractography of the sheets and the average void sizes were also correlated with the ratio of Mohr's circle shear strain ǫ31 to effective strain.
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Modelling of forming limit diagram of perforated commercial pure aluminium sheets using artificial neural network
TL;DR: In this article, a model based on an artificial neural network (ANN) is introduced to reveal the forming limit diagram of perforated sheet with different geometrical features, which is a feed forward back propagation neural network.