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      • KCI등재

        Investigation of Corner Cracks in Continuous Casting Billet Using Thermomechanical Model and Plant Measurements

        Aditya Narayan Shiv Shankar Swain,Suvankar Ganguly,Arunava Sengupta,Elanjickal Zachariah Chacko,Swapnil Dhakate,Pankaj Kumar Pandey 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.10

        A coupled thermofluidic-mechanical model has been developed to analyse the thermomechanical state of the solidifying shellin a continuously cast steel billet. The computational fluid dynamics (CFD) based solver simulates the three-dimensionalflow field and solidification of molten steel as it flows inside the mould. Finite element method based thermomechanicalmodel is coupled with the CFD model to determine the resultant temperature distribution and stress–strain evolution in thesolidifying strand. The heat transfer at the mould-billet interface is taken into account by the calculation of heat flux using anovel inverse heat transfer algorithm. Temperature measurements made in the industrial billet mould have been used for thepurpose. Plant experiments and observations are correlated with the numerical results to provide quantitative understandingof the complex thermomechanical process during billet casting. Various parametric studies are also undertaken to examinethe effects of casting speed, superheat and heat flux changes on resultant strain and temperature distribution. It is observedthat the accumulated plastic strains exceed the critical strain at the off-corner region thereby indicating the possibility ofcrack formation in this region. Reduction of heat flux can lead to lowering of the strain rate at the corners and offer a viablesolution for reducing corner cracks.

      • KCI등재

        Speech Recognition using Machine Learning

        Vineet Vashisht,Aditya Kumar Pandey,Satya Prakash Yadav 대한전자공학회 2021 IEIE Transactions on Smart Processing & Computing Vol.10 No.3

        Speech recognition is one of the fastest-growing engineering technologies. It has several applications in different areas, and provides many potential benefits. A lot of people are unable to communicate due to language barriers. We aim to reduce this barrier via our project, which was designed and developed to achieve systems in particular cases to provide significant help so people can share information by operating a computer using voice input. This project keeps that factor in mind, and an effort is made to ensure our project is able to recognize speech and convert input audio into text; it also enables a user to perform file operations like Save, Open, or Exit from voice-only input. We design a system that can recognize the human voice as well as audio clips, and translate between English and Hindi. The output is in text form, and we provide options to convert audio from one language to the other. Going forward, we expect to add functionality that provides dictionary meanings for Hindi and English words. Neural machine translation is the primary algorithm used in the industry to perform machine translation. Two recurrent neural networks used in tandem to construct an encoder-decoder structure are the architecture behind neural machine translation. This work on speech recognition starts with an introduction to the technology and the applications used in different sectors. Part of the report is based on software developments in speech recognition.

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