Faculty Publications
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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 Application of particle swarm optimization and response surface methodology for machining parameters optimization of aluminium matrix composites in milling operation(Springer Verlag service@springer.de, 2017) Malghan, R.L.; Karthik, K.M.C.; Shettigar, A.K.; Rao, S.S.; D’Souza, R.J.Face milling is extensively used machining operation to generate the various components. Usually the selection of the process parameters are incorporated by trial and error method, literature survey and the machining hand book. This kind of selection of process parameters turns out to be very tedious and time-consuming. In order to overcome this there is a need to develop a technique that could be able to find the optimal process parameters for the desired responses in machining. The present paper illustrates an application of response surface methodology (RSM) and particle swarm optimization (PSO) technique for optimizing the process parameters of milling and provides a comparison study among desirability and PSO techniques. The experimental investigations are carried out on metal matrix composite material AA6061-4.5%Cu-5%SiCp to study the effect of process parameters such as feed rate, spindle speed and depth of cut on the cutting force, surface roughness and power consumption. The process parameters are analyzed using RSM central composite face-centered design to study the relationship between the input and output responses. The interaction between the process parameters was identified using the multiple regression technique, which showed that spindle speed has major contribution on all the responses followed by feed rate and depth of cut. It has shown good prediction for all the responses. The optimized process parameters are acquired through multi-response optimization using the desirability approach and the PSO technique. The results obtained from PSO are closer to the values of the desirability function approach and achieved significant improvement. © 2016, The Brazilian Society of Mechanical Sciences and Engineering.Item Optimization of ferrochrome slag as coarse aggregate in concretes(Techno Press technop2@chollian.net, 2019) Yaragal, S.C.; Kumar, B.C.; Mate, K.The alarming rate of depletion of natural stone based coarse aggregates is a cause of great concern. The coarse aggregates occupy nearly 60-70% by volume of concrete being produced. Research efforts are on to look for alternatives to stone based coarse aggregates from sustainability point of view. Response surface methodology (RSM) is adopted to study and address the effect of ferrochrome slag (FCS) replacement to coarse aggregate replacement in the ordinary Portland cement (OPC) based concretes. RSM involves three different factors (groUnd granulated blast furnace slag (GGBS) as binder, flyash (FA) as binder, and FCS as coarse aggregate), with three different levels (GGBS (0, 15, and 30%), FA (0, 15, and 30%) and FCS (0, 50, and 100%)). Experiments were carried out to measure the responses like, workability, density, and compressive strength of FCS based concretes. In order to optimize FCS replacement in the OPC based concretes, three different traditional optimization techniques were used (grey relational analysis (GRA), technique for order of preference by similarity (TOPSIS), and desirability function approach (DFA)). Traditional optimization techniques were accompanied with principal component analysis (PCA) to calculate the weightage of responses measured to arrive at the final ranking of replacement levels of GGBS, FA, and FCS in OPC based concretes. Hybrid combination of PCA-TOPSIS technique is foUnd to be significant when compared to other techniques used. 30% GGBS and 50% FCS replacement in OPC based concrete was arrived at, to be optimal. © 2019 Techno-Press, Ltd.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.Item Multi-criteria optimization of fly ash and iron ore tailing based concretes subjected to elevated temperatures(Associated Cement Companies Ltd., 2019) Yaragal, S.C.; Babu Narayan, K.S.; Kumar, B.; Francis, J.G.Due to the rapid increase in concrete utilization all over the world, there is increased consumption of Ordinary Portland Cement (OPC), natural fine aggregate (NFA), and natural coarse aggregates. Increased use of OPC, is posing a serious threat due to excess CO2 emissions, and its production is highly energy intensive. On the other hand, extraction and processing stone-based fine and coarse aggregates too, is energy intensive, and the virgin resources are fast depleting. Therefore, for sustainable development, efforts are on all over the world to look for alternative materials in place of conventional ones. In this study, it is attempted to partly replace OPC with fly ash (FA) and partly replace NFA by iron ore tailings (IOT) in concretes. The performance of such concretes at ambient and elevated temperatures is also presented. Full factorial design of experiments was adopted with two control factors under three levels of replacement, i.e., FA (0, 15, and 30% by weight of OPC) and IOT (0, 50, and 100% by volume of NFA). Total nine concrete mixes were prepared and tested for their compressive strengths at room temperature, and residual compressive strengths when subjected to various levels of elevated temperatures (200, 400, 600, and 800°C), and cost of these concretes has also been analyzed. Further, three traditional multi–criteria optimization methods, i.e., grey relational analysis (GRA), technique for order of preference by similarity to ideal solution (TOPSIS), and desirability function approach (DFA) were used to optimize concrete mixes. Results showed that TOPSIS based optimization method is more significant when compared to other two methods. Further, FA-based concrete mixes showed improved performance under multi-criteria optimization. © 2019, Associated Cement Companies Ltd. All rights reserved.Item Multi-response optimization of the turn-assisted deep cold rolling process parameters for enhanced surface characteristics and residual stress of AISI 4140 steel shafts(Elsevier Editora Ltda, 2020) Prabhu, P.R.; Kulkarni, S.M.; Sharma, S.Surface and near-surface areas play an important role as far as safety and dependability ofengineering components particularly when it is subjected to fatigue loading. By applyingdiverse mechanical surface enhancement (MSE) strategies, close to surface layers can becustom-made bringing about enhanced fatigue strength. MSE methods are used to gener-ate surface hardened components without the time and energy-consuming heat treatment.Deep cold rolling (DCR) is one such method that can be employed where the mechanicalenergy induced enables surface-hardening of steels and thereby the combination of hard-ening and finishing in one single step. The objective of this work is to enhance residualstress and near-surface properties of AISI 4140 steel which is the most commonly usedmaterial in the automobile and aerospace industry. The samples were first turned and thendeep cold rolled with various process parameters. Microstructure, surface hardness, sur-face finish, fatigue life, and residual compressive stress after the treatment were examined.Response surface methodology (RSM) and desirability function approach (DFA) was used torelate the empirical relationship between the various process variables and responses andalso to determine the optimum parameter settings for better responses. Further, numericalsimulation of turn-assisted deep cold rolling (TADCR) process was done by utilizing ANSYS-LS-DYNA software to understand the state of residual stress under various treating settings.Confirmation experiments conducted with the optimum parameter setting to validate theimprovements in response and it is found that the deviation between optimum predictedand confirmatory experimental values is about 5%. © 2020 The Authors.Item Surface Properties and Corrosion Behavior of Turn-Assisted Deep-Cold-Rolled AISI 4140 Steel(Springer, 2020) Prabhu, P.R.; Prabhu, D.; Sharma, S.; Kulkarni, S.M.In this research, the effect of various turn-assisted deep-cold-rolling process parameters on the residual stress, microstructure, surface hardness, surface finish, and corrosion behavior of AISI 4140 steel has been investigated. The examination of the surface morphology of the turned and processed samples was performed by using a scanning electron microscope, energy-dispersive spectroscopy, and atomic force microscopy. Response surface methodology and desirability function approach were used for reducing the number of experiments and finding local optimized conditions for parameters under the study. The results from the residual stress measurements indicate that the rolling force has the highest effect by generating a deeper layer of residual compressive stress. The outcomes of surface hardness and surface finish emphasize that rolling force and number of tool passes are the most significant parameters affecting the responses. Surface studies confirmed the corrosion and its intensity onto the metal surface, and according to atomic force microscopy studies, the surface had become remarkably rough after exposure to the corrosive medium. Improvements in surface microhardness from 225 to 305.8 HV, the surface finish from 4.84 down to 0.261 ?m, and corrosion rate from 6.672 down to 3.516 mpy are observed for a specific set of parameters by turn-assisted deep-cold-rolling process. The multiresponse optimization for surface finish and corrosion rate together shows that a ball diameter of 10 mm, a rolling force of 325.75 N, initial roughness of 4.84 µm, and number of tool passes of 3 give better values for the two responses under consideration with composite desirability of 0.9939. Based on the experimental work at the optimum parameter setting, the absolute average error between the experimental and predicted values for the corrosion rate is calculated as 3.2%. © 2020, The Author(s).Item Numerical and experimental studies on sustainable alkali activated concretes at elevated temperatures(Emerald Publishing, 2023) Yaragal, S.C.; Kumar, B.; Abhinav, M.U.Purpose: To reduce environmental impact caused by excessive use of ordinary Portland cement (OPC) and to mitigate scarcity of base materials such as natural coarse aggregate (NCA), industrial by-products can be carefully used as alternatives to OPC and NCA, in production of concrete. This paper aims to describe the performance of using ground granulated blast furnace slag (GGBS), fly ash (FA) as a complete replacement to OPC and ferrochrome slag (FCS) as replacement to NCA in production of novel FCS based alkali activated slag/fly ash concretes (AASFC) and evaluate their performance at elevated temperatures. Design/methodology/approach: Two control factors with three levels each i.e. FA (0, 25 and 50 per cent by weight) and FCS (0, 50 and 100 per cent by volume) as a GGBS and NCA replacement, respectively, were adopted in AASFC mixtures. Further, AASFC mixture specimens were subjected to different levels of elevated temperature, i.e. 200°C, 400°C, 600°C and 800°C. Compressive strength and residual compressive strength were considered as responses. Three different optimization techniques i.e. gray relational analysis, technique for order preference by similarity to ideal solution and Desirability function approach were used to optimize AASFC mixtures subjected to elevated temperatures. Findings: As FA replacement increases in FCS based AASFC mixtures, workability increases and compressive strength decreases. The introduction of FCS as replacement to NCA in AASFC mixture did not show any significant change in compressive strength under ambient condition. AASFC produced with 75 per cent GGBS, 25 per cent FA and 100 per cent FCS was found to have excellent elevated temperature enduring properties among all other AASFC mixtures studied. Originality/value: Although several studies are available on using GGBS, FA and FCS in production of OPC-based concretes, present study reports the performance of novel FCS based AASFC mixtures subjected to elevated temperatures. Further, GGBS, FA and FCS used in the present investigation significantly reduces CO2 emission and environmental degradation associated with OPC production and NCA extraction, respectively. © 2019, Emerald Publishing Limited.Item COMPARISON OF MULTI CRITERION DECISION MAKING APPROACHES (MCDM) ON PRODUCED FLY ASH BASED PELLETIZED GEOPOLYMER COARSE AGGREGATES INTEGRATED WITH IRON ORE TAILINGS(Associated Cement Companies Ltd., 2023) Sharath, B.P.; Akhilesh Kumar, A.R.; Das, B.B.This research paper explores the implementation of multi-criteria decision-making approaches (MCDM) in the produced fly ash (FA) based pelletized geopolymer coarse aggregates integrated with iron ore tailings (IOT). Despite the fact that many techniques are available to aid the decision-making process, the decision makers (here the authors) are forced to go through the laborious task of selecting the appropriate MCDM method. It is because of the fact that each approach/method results in the attainment of different outcomes when applied to such specific scenario (in this case, the produced FA-based aggregates integrated with IOT). This research paper assesses three varied MCDM approaches, that are grey relation analysis (GRA), technique for order preference by similarity to ideal solution (TOPSIS) and desirability function approach (DFA), for the sixteen mixes involved in the production of FA-based aggregates integrated with IOT. These sixteen mixes were designed by taking into consideration of four experimental parameters that were Na2O and water content dosages, blend proportion of IOT and FA and SiO2/Na2O ratio, with the aid of Taguchi’s experimental methodology. The characteristics of the produced FA-based aggregates like aggregate impact value, aggregate crushing value, individual crushing strength of aggregates and water absorption served as inputs in the implementation of MCDM approaches on the produced FA-based aggregates integrated with IOT. The concluding remarks obtained by the implemented MCDM approaches proved to be effective in understanding the order of influence of experimental parameters taken under consideration for producing FA-based aggregates and among all, GRA stood as a relatively better approach in comparison with the other two approaches. © 2023, Associated Cement Companies Ltd.. All rights reserved.