Faculty Publications

Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736

Publications by NITK Faculty

Browse

Filters

20252

Settings

Author: search.filters.author.Sahu, R.K.Subject: search.filters.subject.Hafnium alloys

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Machining Parameter Optimization of Wire Electrical Discharge Machining for Ni50.3Ti29.7Hf20 Alloy Using TOPSIS and Grey Wolf Optimization Technique
    (Springer, 2025) Bhaskar, M.; Balaji, V.; Narendranath, S.; Sahu, R.K.
    Ni50.3Ti29.7Hf20 is an alloy with shape memory characteristics that can withstand high temperatures. It possesses remarkable strength, hardness, and exceptional corrosion resistance. SMAs are well-suited for various applications, including automotive sensors, automobiles, aerospace technologies, robotics, actuators, and MEMS devices. However, its unique properties make it difficult to machine using conventional methods. Wire EDM is an unconventional machining process suited for difficult-to-machine materials like Ni-Ti-Hf alloy, providing high accuracy and precision and minimizing the risk of material damage. This paper focuses on the optimization of machining parameters, namely Discharge time (PON), Pause time (POFF), Gap voltage (GV), and Wire travel speed (WS) during WEDM of Ni-Ti-Hf shape memory alloy utilizing the TOPSIS and GWO techniques. The aim is to obtain optimal machining parameters for improving the machined Ni-Ti-Hf alloy’s material removal rate (MRR) and surface roughness (Ra). The optimal machining parameters from GWO were PON = 123.8 µs, POFF = 50 µs, WS = 2, and GV = 25. The predicted values of material removal rate and surface roughness are 4.22 mm3/min and 3.62 µm, respectively. The experimental verification demonstrates the proposed optimization approach's effectiveness, as the predicted values correlate strongly with the actual values. © ASM International 2023.
  • No Thumbnail Available
    Item
    Process parametric and performance characteristics study of WED machined Ni-Ti-Hf high-temperature shape memory alloys: an experimental and artificial intelligence approach
    (Institute of Physics, 2025) Balaji, V.; Sahu, R.K.; Narendranath, S.
    In recent years, to meet the shortcomings of the conventional machining of Ni-Ti-Hf shape memory alloy (SMA), Wire Electric Discharge Machining (WEDM) as one of the unconventional machining methods, has emerged as the preferred method for processing SMAs. Therefore, in this study, according to the Response Surface Methodology-based Central Composite Design layout, WED machining of Ni-Ti-Hf SMA is carried out using the control parameters like spark time (SON), spark pause time (SOFF), gap voltage (Vg), and dielectric flow rate (FDL). A General Regression Neural Network (GRNN) model was used to predict the critical WEDM responses: material removal rate (MRR), surface roughness (Ra), and kerf width (KW). The GRNN model closely agrees with the experimental WEDM responses, resulting in a Mean Absolute Percentage Error below 2%. Field Emission Scanning Electron Microscopy result revealed a recast layer thickness of 10.64 ± 2.06 µm and 38.19 ± 9.55 µm for the samples with the lowest surface roughness (Ra) and highest MRR, respectively. The shape recovery test result shows a less than 4% reduction in recovery ratio post-WEDM. Further, electrochemical corrosion studies revealed that owing to these surface defects, the corrosion rate increased with higher discharge energy. The corrosion rate of the base material, low Ra sample, and high MRR sample were 0.0013 mm yr?1, 0.0128 mm yr?1, and 0.0334 mm yr?1, respectively. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.