http://nopr.niscpr.res.in/handle/123456789/18480 2026-10-11T07:01:51Z http://nopr.niscpr.res.in/handle/123456789/18682 Title: Performance prediction of Centrifugal Pumps with variations of blade number Authors: Chakraborty, Sujoy; Choudhuri, Kishan; Dutta, Prasenjit; Debbarma, Bishop Abstract: Centrifugal pumps are used extensively for hydraulic transportation of liquids over short to medium distance through pipelines where the requirements of head and discharge are moderate. At present, the influence of blade number on inner flow field and the characteristics of centrifugal pump have not been understood completely. The use of numerical analysis tools allow us to obtain data in inaccessible positions for the experimentations. In this paper, a two dimensional numerical study of steady, static pressure distribution and incompressible flow characteristics inside the passage with different numbers of blades of centrifugal pump impeller has been carried out. The investigation focuses mainly on the efficiency of the pump. Centrifugal pumps with impeller blades 5, 6 and 7 have been modeled and its efficiency at 3000 rpm is evaluated by FLUENT 6.3 software. The numerical analysis displays that with the increase of blade number, the head and static pressure of the model increases, but the efficiency of centrifugal pump varies with number of blades and shows maximum for 7 number of blade. Page(s): 373-378 2013-06-01T00:00:00Z http://nopr.niscpr.res.in/handle/123456789/18681 Title: An approach for solving multi characteristics optimization of submerged are welding process parameters by using grey based genetic algorithm Authors: Roy, Joydeep; Majumder, Arindam; Barma, J. D.; Rai, R. N.; Saha, S. C. Abstract: The quality of a weld joint is directly influenced by the welding input parameters during welding and the joint quality can be defined in terms of properties like weld-bead geometry, mechanical properties and distortion. In this paper, an attempt has been made to find the optimal process parameters for achieving good quality welded joint by using multi objective function genetic algorithms (GA). Taguchi design of experiment (DOE) was used for conducting the experiment and these experimental data used to develop regression model for correlating mechanical properties with the process parameters. Grey relational analysis has been introduced to convert the multi objective function into single objective one, which will be the objective function in genetic algorithm. Page(s): 340-347 2013-06-01T00:00:00Z http://nopr.niscpr.res.in/handle/123456789/18680 Title: Determination of coal quality using Artificial Intelligence Algorithms Authors: Suljic, Mirza; Banjanovic-Mehmedovic, Lejla; Dzananovic, Izet Abstract: The main task of coal producers is to provide for sufficient quantities of coal of required quality with minimum costs of excavation. Therefore, the prediction of energy values is the most important task aiming to secure the optimal usage of coal energy value. The goal of paper is to identify, examines and evaluate most influential artificial intelligence algorithms that have been widely used in the data mining community, on a real problem of predicting coal quality. Our researches are based on the data achieved under laboratory conditions during the period of five years (2005-2010), and include 33256 coal samples from ’’Kreka’’ Coal Mine Company. The goal of the research is to build, based on the described data, a prediction model that will be used for predicting the coal quality class of unknown samples. Four algorithms have been identified: C4.5, kNN, Naive Bayes and Multilayer Perceptron (MLP). The idea is to find the best model through the following stages: each of the algorithms is calibrated in order to find appropriate model division techniques which maximize the performance of the algorithms, to assess the importance of input attributes and ultimate comparison of the algorithm orders them with respect to their performance. The final evaluation of the outcomes allowed singling out the MLP to be the best predicting methods for the given domain with optimal structure for input, hidden and output layer. Page(s): 379-386 2013-06-01T00:00:00Z http://nopr.niscpr.res.in/handle/123456789/18679 Title: Waste cooking oil: a promising feedstock for biodiesel production through power ultrasound and hydrodynamic cavitation Authors: Pal, Amit; Kachhwaha, Surendra S. Abstract: The present research work deals with the details of development of laboratory test rigs for power ultrasound and hydrodynamic cavitation test rigs for conversion of WCO into biodiesel in comparison to conventional mechanical stirring. Results show that cavitation techniques can be successfully applied to transesterification reactions, to achieve more than 90% yield of the product for molar ratio 4.5:1 with minimum catalyst percentage of 0.5% and appears to be rapid and effective compared to the mechanical stirring method, for preparing alkyl esters from triglycerides. Page(s): 387-392 2013-06-01T00:00:00Z