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Dhiman Chatterjee
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Dhiman Chatterjee
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Dhiman Chatterjee
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Chatterjee, Dhiman
Chatterjee, D.
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3 results
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- PublicationSlurry erosion wear resistance of polyurethane coatings with B4C Nano powders for hydroturbine applications(01-01-2013)
;Syamsundar, C.; ; Maiti, A. K.Hydropower generation from the Himalayan rivers in India face challenge in the form of silt-laden water. These sediments contain abrasive particles which can erode the turbine blades and reduce turbine life. This calls for the development of newer materials for turbine blade. To address this issue in the present investigation, 16Cr- 5Ni martensitic stainless steel has been selected and coated with polyurethane (PU) reinforced with boron carbide (B4C) nano particles to improve the wear resistance. With the increase of B4C content (0-2 wt %) in PU the mechanical properties and erosion wear resistance were investigated. The Shore hardness and pull off adhesion were found to increase with the increased content ofB4C nano particles and from contact angle measurement the coated surfaces are shown to be hydrophilic in nature. This condition reflects better wetting and may be good for cavitation wear resistance. Slurry erosive wear tests were done at various test conditions determined by Taguchi design of experiments of impact velocity, impingement angle, erodent size and slurry concentration. The erosion area of the PU coated samples were analyzed with scanning electron microscope (SEM) and the erosion wear mechanism is discussed Analysis of variance studies of erosion rate indicated that B4C content in PU material is the single most important parameter and interaction of impact velocity and impingement angle are proved to be significant Artificial Neural Network and Genetic Algorithm were employed to arrive at the worst possible scenario. - PublicationExperimental Characterization of Silt Erosion of 16Cr–5Ni Steels and Prediction Using Artificial Neural Network(30-12-2015)
;Syamsundar, C.; Hydropower generation from the Himalayan rivers in India face challenge in the form of sand-laden water. These sediments contain abrasive particles which can erode the turbine blades and reduce turbine life. This calls for the development of newer materials for turbine blade. To address this issue in the present investigation, 16Cr–5Ni martensitic stainless steel has been selected. Silt erosive wear tests were done at various test conditions determined by Taguchi design of experiments of impact velocity, impingement angle, erodent size and silt concentration. Analysis of variance studies of erosion rate and roughness indicated that impact velocity is the single most important parameter and interaction of impact velocity and impingement angle are proved to be significant. The optimized artificial neural networks are finally used to estimate the erosion rate for different combinations of the test conditions in conjunction with optimization techniques like Genetic algorithm were employed to arrive at the worst possible scenario (impact velocity 20 m/s, impingement angle 30°, erodent size 245 µm and silt concentration 60 kg/m3). - PublicationNumerical prediction and optimization of the performance of axial-flow hydrokinetic turbine in an array(01-01-2019)
;Sharma, LaveenaArray of hydrokinetic turbines can be used to produce power from flowing rivers akin to the wind turbine farms. However, arriving at optimum configuration (location and number) of turbines through experimental or numerical routes is not easy. Hence in the present work, attempts have been made to utilize computationally less intensive model-based multivariate optimization techniques coupled with some numerical simulations to arrive at suitable turbine configurations in an array. In this work, we have modeled the complex functions, such as turbine power, non-linear interaction of turbines with wakes of preceding turbines and the area utilized by the turbines, by means of simplified mathematical treatment of response surface methodology. The present work has identified three turbine array geometries as potential configurations and based on numerical simulations and optimization techniques has arrived at pareto-domain and has ranked these pareto-solutions. Further simulations were carried out for the best configurations and the numerical results were compared with the optimization results as a part of the validation of the latter. Flow physics was analyzed and final recommendation of turbine array configuration is made.