Journal Articles
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884
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Item Abrasive wear behavior of granite-filled glass-epoxy composites by SiC particles using statistical analysis(2011) Basavarajappa, .S.; Manjunath Yadav, S.M.; Kumar, S.; Arun, K.V.; Narendranath, S.This experimental investigation deals with the evaluation of abrasive wear behavior of Glass Epoxy (G-E) composites on pin-ondisc test rig. A plan of experiments, based on the Taguchi Design of Experiments, was performed to acquire data in controlled way. An orthogonal array and the analysis of variance were employed to investigate the percentage of contribution of various process parameters like sliding speed, applied load, sliding distance and their interactions affecting the abrasive wear volume loss of composites. The correlations between the various factors affecting the abrasive wear behavior of composites were obtained by using multiple linear regression equations. The obtained results indicate that applied load and sliding distance were the wear factors that have the highest physical as well as statistical influence on the abrasive wear behavior of both filled and unfilled G-E composites. A good agreement between the predicted and actual wear resistance was observed within±12%. © Taylor & Francis Group, LLC.Item Evaluation of wire electro discharge machining characteristics of Ti50Ni50-xCux shape memory alloys(Cambridge University Press, 2016) Manjaiah, M.; Laubscher, R.F.; Narendranath, S.; Basavarajappa, S.; Gaitonde, V.N.The machining of shape memory alloys (SMAs) is fairly essential and integral part in the manufacture of components for utilizing in engineering applications. An effort has been made in the present work to study the effect of wire electro discharge machining process parameters such as pulse on time (T on), pulse off time (T off) and servo voltage (SV) have been analyzed on material removal rate and surface roughness. The investigation clearly reveals that an increased pulse on time with decrease in pulse off time as well as SV increases the amount of material removed in machining of SMAs. On the other hand, the surface roughness increases with increased pulse on time and decreases with increased pulse off time as well as SV. The surface topography of the machined surface was analyzed using scanning electron microscope (SEM) and confocal micrographs. Phase changes on the machined surface with respect to pulse on time and SV were evaluated from X-ray diffractometer (XRD) analysis. © Materials Research Society 2016.Item Dry Sliding Wear Behavior of Super Duplex Stainless Steel AISI 2507: A Statistical Approach(De Gruyter Open Ltd peter.golla@degruyter.com, 2016) Davanageri, M.; Narendranath, S.; Kadoli, R.The dry sliding wear behavior of heat-treated super duplex stainless steel AISI 2507 was examined by taking pin-on-disc type of wear-test rig. Independent parameters, namely applied load, sliding distance, and sliding speed, influence mainly the wear rate of super duplex stainless steel. The said material was heat treated to a temperature of 850°C for 1 hour followed by water quenching. The heat treatment was carried out to precipitate the secondary sigma phase formation. Experiments were conducted to study the influence of independent parameters set at three factor levels using the L27 orthogonal array of the Taguchi experimental design on the wear rate. Statistical significance of both individual and combined factor effects was determined for specific wear rate. Surface plots were drawn to explain the behavior of independent variables on the measured wear rate. Statistically, the models were validated using the analysis of variance test. Multiple non-linear regression equations were derived for wear rate expressed as non-linear functions of independent variables. Further, the prediction accuracy of the developed regression equation was tested with the actual experiments. The independent parameters responsible for the desired minimum wear rate were determined by using the desirability function approach. The worn-out surface characteristics obtained for the minimum wear rate was examined using the scanning electron microscope. The desired smooth surface was obtained for the determined optimal condition by desirability function approach. © 2016 M. Davanageri et al., published by De Gruyter Open 2016.Item ANN and RSM modeling methods for predicting material removal rate and surface roughness during WEDM of Ti50Ni40Co10 shape memory alloy(AMSE Press 16 Avenue Grauge Blanche Tassin-la-Demi-Lune 69160, 2017) Soni, H.; Narendranath, S.; Ramesh, M.R.Present study exhibits the comparison between experimental and predicted values. Where response surface method (RSM) and artificial neural network (ANN) were used as predictor for the prediction of wire electro discharge machining (WEDM) responses such as the material removal rate (MRR) and surface roughness (SR) during the machining of Ti50Ni40Co10 shape memory alloy. It has been noticed from the literature survey that pulse on time and servo voltage are most important process parameters for the machining of TiNiCo shape memory alloy, hence there are five levels of these process parameters were chosen for the present study. For the present study selected alloy has been developed through vacuum arc melting and L-25 orthogonal array has been created by using Taguchi design of experiment (DOE) for experimental plan. During the present study ANN predicted values have been found to very close to experimental values compare to RSM predicted values, hence it can be say that ANN predictor gives more accurate values compare to RSM predicted values. © 2017 AMSE Press. All rights reserved.Item Modeling and Optimization of Wear Rate of AISI 2507 Super Duplex Stainless Steel(Springer Netherlands rbk@louisiana.edu, 2019) Davanageri, M.B.; Narendranath, S.; Kadoli, R.The present work attempts to study the parameters influencing wear, namely, applied load, heat-treated temperature, sliding velocity, and sliding distance using statistical Design of Experiments (DOE) and Response Surface Methodology (RSM). The wear behavior of super duplex stainless steel was evaluated under dry sliding conditions. A three-level Central Composite Design (CCD) based non-linear model was used to establish input-output relationship based on the collected experimental input-output data. Surface plots were used to study the influence of applied load, heat-treated temperature, sliding distance, and sliding velocity on the wear rate of super duplex stainless steel. The wear rate was observed to vary nearly non-linearly with applied load and linearly with the rest of the input parameters. Analysis of Variance (ANOVA) was conducted to test the statistical adequacy of the non-linear model developed. Applied load and heat-treated temperature were found to have a more positive contribution towards the wear rate than other parameters. Although the sliding velocity had a negligible effect, its interaction with applied load and heat-treated temperature had a significant impact on the wear rate. The regression equation developed was tested for its prediction precision with the help of 20 test cases. Further, attempts were also made to determine the optimum combination of input parameters that minimize the wear rate using the Desirability Function Approach (DFA). The objective of minimizing the wear rate was met with the highest desirability value of 1. Confirmation experiments were conducted for the determined optimal set of input parameters of 20 test cases resulting in an average absolute percent deviation in prediction of 6.34% and 5.58%. © 2018, Springer Science+Business Media B.V., part of Springer Nature.