Faculty Publications

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Publications by NITK Faculty

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    Computational fluid dynamic approach to understand the effect of increasing blockage on wall shear stress and region of rupture in arteries blocked by arthesclerotic plaque
    (UK Simulation Society Clifton Lane Nottingham NG11 8NS, 2016) Hegde, S.S.; Deb, A.; Nagesh, S.
    Computational bio-mechanics is developing rapidly as a non-invasive tool to assist the medical fraternity to help in both diagnosis and prognosis of human body related issues such as injuries, cardio-vascular dysfunction, atherosclerotic plaque etc. Any system that would help either properly diagnose such problems or assist prognosis would be a boon to the doctors and medical society in general. This project is an attempt to use numerical analysis techniques; in particular, computational fluid dynamics (CFD) to solve hemodynamics related problems. The mathematical modeling of the blood flow in arteries in the presence of successive blockages has been analyzed using CFD technique. Different cases of blockages in terms of percentages have been modeled to study the effect of blockage on wall shear stress values and also the effect of increase in Reynolds number on wall shear stress values. The concept of fluid structure interaction (FSI) has been used to study the effect of increasing von Mises stress on arteries and to determine the region of rupture in arteries. The simulation results are validated using in vivo measurement data from existing literature. © 2016, UK Simulation Society. All rights reserved.
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    The effect of Sr modification on thermal diffusivity of Al–8Si alloy
    (Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Vijayan, V.; Prabhu, K.N.
    Newtonian and Fourier analysis techniques were used to calculate the solid fraction and latent heat during the solidification of Al–8Si alloy and the subsequent results were used to study the effect of Sr modification on thermal diffusivity of the solidifying melt. The results indicate that the thermal diffusivity increased significantly with increase in Sr content. The increase in the thermal diffusivity was attributed to the increase in the electronic conduction of the modified alloy due to the decreased activity of the bifilm. The results also indicate that the latent heat evolved during solidification increased with increase in Sr concentration and was associated with the increase in the solidification range that occurred during the modification process. © 2017 Informa UK Limited, trading as Taylor & Francis Group.
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    Gearbox fault diagnosis based on Multi-Scale deep residual learning and stacked LSTM model
    (Elsevier B.V., 2021) Ravikumar, K.N.; Yadav, A.; Kumar, H.; Gangadharan, K.V.; Narasimhadhan, A.V.
    Fault diagnosis methods based on signal analysis techniques are widely used to diagnose faults in gear and bearing. This paper introduces a fault diagnosis model that includes a multi-scale deep residual learning with a stacked long short-term memory (MDRL-SLSTM) to address sequence data in a gearbox health prediction task in an internal combustion (IC) engine. In the MDRL-SLSTM network, CNN and residual learning is firstly utilized for local feature extraction and dimension reduction. The experiment is carried out on the gearbox of an IC engine setup, two datasets are used; one is from bearing and the other from 2nd driving gear of gearbox. To reduce the number of parameters, down-sampling is carried out on input data before giving to the architecture. The model achieved better diagnostic performance with vibration data of gearbox. Classification accuracy of 94.08% and 94.33% are attained on bearing datasets and 2nd driving gear of gearbox respectively. © 2021 Elsevier Ltd
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    Study of Correlated Motions to Detect the Conformational Transitions of the Intrinsically Disordered Sheep Prion Peptide
    (American Chemical Society, 2024) Chakraborty, D.; Singh, O.; Parameswaran, D.
    Intrinsically disordered proteins (IDPs) are known for their random structural changes throughout their sequence based on the environment. The mechanism underlying these structural changes is difficult to explain. All biological processes are known to follow the direction through which they act. A study of the correlated motion can help to understand the direction of the change. Herein, we introduced the multivariate statistical analysis (MSA) technique to study the correlated motion of the peptide. The correlated motion of the sheep prion peptide was studied with the change in the temperature and solvent. These techniques helped to identify the contributing residual motions that helped to form the different secondary structures of the protein and also the triggering factors that drive these sorts of residual motions. The structural details match the experimentally reported data. It was found that the direction of the change of the secondary structure for this peptide shifted from the C-terminal to the N-terminal with an increase in the temperature. It was found that the involvement of the hydrophobic residues present at the C-terminal and the middle residues (residues 12-17) is responsible for forming a β-sheet at the normal temperature. Hydration water was found to play an important role in this change. Insights gained from this study can be used to design strategies for desirable structural changes in the IDPs. © 2024 American Chemical Society.