Faculty Publications
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Item A study on the effect of multiple abrasive particle impact on the crater sphericity in AWJM using FEA(Elsevier Ltd, 2022) Balaji, B.; Satyanarayana, S.The workhorse of the Titanium alloy industry i.e., Ti-6Al-4 V, is classified among the foremost widely utilized Titanium (Ti)-alloys and is broadly utilized in aviation and medication industry where low-density, supreme quality and exceptional erosion resistance are required. Since this material has high strength, it is very hard to process by means of conventional methods of machining. Therefore, unconventional machining methods like Abrasive Waterjet Machining (AWJM) become of great importance. Current work exhibits an explicit modelling of multiple abrasive particles impact on Ti-6Al-4 V in AWJM using Finite Element Analysis (FEA) approach. For experimental verification purpose, the crater geometry made on the Ti-6Al-4 V were determined and compared with the crater sphericity values obtained through FEA simulation. Also, the influence of velocity of abrasive particles and jet impact angle on sphericity of the crater was examined. For experimental verification of FEA simulations, the impact angle emerged as a key process parameter. The error between the simulation and experimental crater sphericity values was below 20%. It was also observed that the simulation results were accurate upto 0.04% for 90° impact angle and overall, the simulation model showed better results for 220 m/s abrasive particle velocity. © 2022Item MOGA and TOPSIS-based multi-objective optimization of wire EDM process parameters for Ni50.3-Ti29.7-Hf20 alloy(Elsevier Ltd, 2023) Balaji, B.; Narendranath, N.Conventional machining techniques face challenges in processing Ni-Ti-Hf alloys, which exhibit superior properties and are increasingly considered promising materials for high-temperature shape memory actuator applications. Thus, this article focuses on investigating the effect of Wire Electric Discharge Machining (WEDM) input parameters, namely discharge time (TON), pause time (TOFF), gap voltage (SV), and wire travel speed (WF), on the surface quality and shape memory properties of these alloys. These parameters were optimized to obtain a better removal rate (MRR) and surface finish quality (Ra) by employing a hybrid approach of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Genetic Algorithm (MOGA). TON emerged as the most influencing parameter for both MRR and Ra, and the sample machined using optimal parameter setting, which had a MRR of 5.287 mm3/min and Ra of 2.335 µm, showed better surface quality with fewer surface defects and irregularities, lower recast layer thickness of 10.057 µm, and better shape memory properties with less than 15 % deviation in their latent heat of transformation values and a less than 5ºC change in their austenite and martensite transformation temperature values, which indicates MOGA was successful in finding a trade-off between the two responses. © 2023 Elsevier Ltd