Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Krishna Kumar, K.

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    Surface Improvement of Shafts by Turn-Assisted Deep Cold Rolling Process
    (EDP Sciences edps@edpsciences.com, 2016) Prabhu, R.; Sharma, S.S.; Jagannath, K.; Krishna Kumar, K.; Kulkarni, S.M.
    It is well recognized that mechanical surface enhancement methods can significantly improve the characteristics of highly-stressed metallic components. Deep cold rolling is one of such technique which is particularly attractive since it is possible to generate, near the surface, deep compressive residual stresses and work hardened layers while retaining a relatively smooth surface finish. In this paper, the effect of turn-assisted deep cold rolling on AISI 4140 steel is examined, with emphasis on the residual stress state. Based on the X-ray diffraction measurements, it is found that turn-assisted deep cold rolling can be quite effective in retarding the initiation and initial propagation of fatigue cracks in AISI 4140 steel. © The Authors, published by EDP Sciences, 2016.
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    Reliability Analysis Using Bayesian Belief Network on Drone System: A Case Study
    (Institute of Electrical and Electronics Engineers Inc., 2024) Das, M.; Mohan, B.R.; Ram Mohana Reddy, G.; Chhaparwal, E.; Krishna Kumar, K.; Chowdhury, S.; Sharma, S.
    Ensuring the reliability of software components is of paramount importance in safety-critical systems. Grave consequences might occur if software failures in such systems. Hence, predicting software reliability is important in these systems. This research uses Bayesian Belief Network(BBN) and leverages historical failure data to find fault interdependencies, giving much more insights than methodologies like Fault Tree Analysis (FTA) and Reliability Block Diagrams (RBD). By comparing BBNs with these traditional methods, the research shows the dynamic capabilities of BBNs. BBN also shows the capability of using real-time data and machine learning together to increase the software reliability of the software components, making this system much safer. © 2024 IEEE.