Yazar "Chattopadhyaya, Somnath" seçeneğine göre listele

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    Experimental Investigation and Parametric Optimization of Friction Stir Welding on Aluminium Alloy 6061-T6
    (Nova Science Publishers, Inc., 2022) Bora, Bhabani; Chattopadhyaya, Somnath; Sharma, Shubham; Kılınç, Hüseyin Çağan
    Friction Stir Welding (FSW) is a green solid-state joining process which can easily join alloys that are generally difficult to weld by conventional fusion welding. This process uses a non-consumable spinning tool bit. The relative motion between the tool and the work piece produces heat, which joins the material of two edges by plastic atomic diffusion. This joining technique is energy efficient, environmentally friendly and versatile. An attempt has been made to review the research papers on experimental work carried out in the field of friction stir welding and its impact on microstructure, fracture surface, and thermal and mechanical properties of welded joints. Also, Tungsten Inert Gas (TIG) and Metal Inert Gas (MIG) welding have been carried out to compare their mechanical and micro-structural properties with FSW. In this experimental work, focus has been placed on: a) How to conduct the experiments of FSW on AA 6061-T6 (Aluminium Alloy) using ‘Full Factorial’ design of experiment and developing a mathematical model which provides the empirical relationship between the process parameters (Rotational Speed and welding Speed) and the output responses (Maximum Process Temperature (TMax), Maximum Vickers Micro Hardness (HMax), Yield Strength (YS), Ultimate Tensile Strength (UTS) and % Elongation (% E)). b) The effects of process parameters on temperature distribution and mechanical properties (Tensile properties, Vickers Micro Hardness) of AA 6061-T6 friction stir welded butt joints. c) How to find the optimum welding parameters that would minimize temperature and maximize mechanical properties. d) Analyzing thermal properties using simulations in ANSYS software. Analysis of variance (ANOVA) and scatter diagram have been employed to assess the significant effect of the factors and the adequacy of the models developed for the response variables. The developed mathematical models can be effectively used at 95% confidence level. Also, from the experimental data, it is revealed that FSW joints exhibit superior mechanical properties as compared to the TIG and MIG welded joints. © 2022 by Nova Science Publishers, Inc.
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    Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
    (MDPI, 2022) Ansari, Md Obaidullah; Chattopadhyaya, Somnath; Ghose, Joyjeet; Sharma, Shubham; Kozak, Drazan; Li, Changhe; Wojciechowski, Szymon
    Breakout is one of the major accidents that often arise in the continuous casting shops of steel slabs in Bokaro Steel Plant, Jharkhand, India. Breakouts cause huge capital loss, reduced productivity, and create safety hazards. The existing system is not capable of predicting breakout accurately, as it considers only one process parameter, i.e., thermocouple temperature. The system also generates false alarms. Several other process parameters must also be considered to predict breakout accurately. This work has considered multiple process parameters (casting speed, mold level, thermocouple temperature, and taper/mold) and developed a breakout prediction system (BOPS) for continuous casting of steel slabs. The BOPS is modeled using an artificial neural network with a backpropagation algorithm, which further has been validated by using the Keras format and TensorFlow-based machine learning platforms. This work used the Adam optimizer and binary cross-entropy loss function to predict the liquid breakout in the caster and avoid operator intervention. The experimental results show that the developed model has 100% accuracy for generating an alarm during the actual breakout and thus, completely reduces the false alarm. Apart from the simulation-based validation findings, the investigators have also carried out the field application-based validation test results. This validation further unveiled that this breakout prediction method has a detection ratio of 100%, the frequency of false alarms is 0.113%, and a prediction accuracy ratio of 100%, which was found to be more effective than the existing system used in continuous casting of steel slab. Hence, this methodology enhanced the productivity and quality of the steel slabs and reduced substantial capital loss during the continuous casting of steel slabs. As a result, the presented hybrid algorithm of artificial neural network with backpropagation in breakout prediction does seem to be a more viable, efficient, and cost-effective method, which could also be utilized in the more advanced automated steel-manufacturing plants.
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    Real-Time Comprehensive Energy Analysis of the LHD 811MK-V Machine with Mathematical Model Validation and Empirical Study of Overheating: An Experimental Approach
    (Springer Heidelberg, 2022) Siddiqui, Mohd Ahtesham Hussain; Chattopadhyaya, Somnath; Sharma, Shubham; Assad, Mamdouh El Haj; Li, Changhe; Pramanik, Alokesh; Kılınç, Hüseyin Çağan
    Overheating is a critical problem encountered with an electro hydraulically operated machine working in underground mines. Aggrandizement in the temperature of the hydraulic fluids is caused due to deficiencies in the components. Thermal instability of hydraulic power systems causes temperature transients, which not only mitigates machine productivity but is also harmful. Especially considering the system inefficiency, the hydraulically driven machine has an inbuilt cooling arrangement. When the energy loss caused by faulty elements exceeds the system cooling capacity, hydrostatic transmission is overheated. Mathematical models, experimental studies, and analytical approaches evaluate the substantive reasons for heating and determine heat energy generation due to inefficient parts of the hydraulic system of the load haul dumper. The mathematical model is used to calculate heat energy addition, emulating power loss in hydraulic components and equivalence. Efficiency block diagram of entire hydraulic system has been created. Hydraulic components get worn out in due course of continuous operation of the machine. While calculating the series function, the overall efficiency up to 60% of all the components in the system will not accumulate the heat in the system. The Weibull distribution is used to analyse system reliability, and it is discovered that if the system inefficiency exceeds 40%, failure rate due to overheating increases. Excess heat energy causes fluid degradation, deterioration of rubber parts and seals, acceleration of wear, and tear of relative and mating parts and has an impact on the overall operation of the machine. Actuators' performance becomes erratic and sluggish.