Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
11 results
Search Results
Item Fast and efficient synthesis of N-substituted ?-aminobutyric acids by grinding at room temperature(Springer Verlag, 2013) Bhat, S.I.; Trivedi, D.R.Green chemistry is gaining increasing interest due to the growing awareness of the chemical community for sustainable development. Green chemistry solutions include synthesis without solvent and catalyst because many solvents and catalysts are toxic and expensive. Herein, we report the solvent and catalyst free method for the synthesis of N-substituted derivatives of ?-aminobutyric acid by direct aza-Michael addition of amines to crotonic acid. The protocol involves simple mixing or grinding the reactants at room temperature. The ?-amino acid derivatives were obtained in 82-100 % yield with a short reaction time without any tedious workup procedures. Our findings thus reveal a promising alternative to previously used procedures. © 2013 Springer-Verlag Berlin Heidelberg.Item Prediction of Bond's work index from field measurable rock properties(Elsevier B.V., 2016) Ram Chandar, K.; Deo, S.N.; Baliga, A.J.In mineral beneficiation, grinding is the final stage in the process of size reduction. The power consumed in this stage is higher when compared to other stages, owing to increased size reduction ratio. The primary purpose of grinding is to reduce the particle size to optimum so that mineral particles can be extracted more economically. Decision making plays an important role here, as it involves determining and comparing the energy that is required to perform the grinding process and also determining the amount of minerals lost as the coarser size particles are arrived at in mineral beneficiation. In general, Bond's work index is used to determine the grinding efficiency and also to calculate the power requirement. The process is very time consuming and it requires skilled labor and specialized mill. A systematic investigation was carried out to predict Bond's work index using simple field measurable properties of rocks. Tests were conducted on Basalt, Slate and Granite using a laboratory scale ball mill and rock properties namely density, Protodyakonov's strength index and rebound hardness number were determined. The results were analyzed using artificial neural networks and regression analysis. Mathematical equations were developed to predict Bond's work index based on rock properties using regression analysis, which resulted a very good correlation co-efficient values. © 2016 Elsevier B.V.Item Corrosion behavior of high and low temperature austempered ductile iron (ADI) in iron ore slurry(ASTM International, 2017) Aithal, P.M.; Vijayan, V.; Surendranathan, A.O.; Udupa, K.R.; Samuel, K.G.Corrosion behavior of austempered ductile iron (ADI) and forged EN31 steel balls in a ground iron ore slurry was studied as a function of time in the slurry, while the microstructure of ADI developed due to different tempering temperature and tempering time. The corrosion rates of the grinding balls immersed in the iron ore slurry were determined using electrochemical analysis and weight loss methods. It was found that the pH of the iron ore slurry increased with time and the corrosion behavior was influenced by the pH of the slurry. The corrosion rate of forged EN31 steel balls increased with the increase in time and pH of the slurry, whereas the corrosion rate of ADI balls depended on the austempering treatment. In general, the forged EN31 steel ball offered better corrosion resistance than ADIs during the early stages of exposure in the slurry (low pH values of the slurry), but at higher pH values of the slurry, the ADIs yielded better corrosion resistance than forged EN31 steel balls. The ADI austempered at higher temperatures showed better corrosion resistance than the ones austempered at lower temperatures. © © 2017 by ASTM International.Item Prediction of rock properties using grinding characteristics of ball mill(Inderscience Publishers, 2020) Ram Chandar, R.C.; Umamahesh, A.; Kumar, K.P.; Avinash, D.Knowledge of physico-mechanical properties of rocks is essential starting from the preliminary exploration to processing in mining projects. The strength properties of rocks considered necessary for mine planning and design, selection of equipment, use of suitable processing technique, etc. Sophisticated laboratory facilities are required to determine various properties of rocks using some international standards like ISRM, ASTM, etc., which is time consuming and costly affair. In this study, an attempt is to predict some of the rock properties like density, tensile strength using grinding characteristics of ball mill. Laboratory experiments conducted on samples of granite, limestone, slate and BHQ varying different parameters like quantity of feed, charge ratio, size of balls, grinding time, etc., at constant RPM of ball mill. Grinding characteristic curves used to obtain 25%, 50%, 80% cumulative passing sieve sizes. In addition, laboratory experiments carried out to find physico-mechanical properties like density, tensile strength, Protodyakonav's strength index, rebound hardness number. Regression analysis carried out with the data obtained from experiments. © © 2020 Inderscience Enterprises Ltd.Item Estimation of Grinding Time for Desired Particle Size Distribution and for Hematite Liberation Based on Ore Retention Time in the Mill(Springer, 2020) Hanumanthappa, H.; Vardhan, H.; Raj, G.R.; Kaza, M.; Sah, R.; Shanmugam, B.K.Iron ores obtained from different sources differ in their chemical and physical properties. These variations make the process of grinding a difficult task. The work carried out in this context focuses on three different samples of iron ore, viz., high silica high alumina, low silica high alumina, and low silica low alumina. The grinding process for all the three iron ores is carried out individually in Bond’s ball mill and the total retention time taken by each iron ore sample is calculated. The present investigation focuses on utilizing the calculated retention time of the iron ore as a standard grinding reference time to the laboratory ball mill for optimizing the grinding time of each ore. The desired P80 (150 ?m) with an acceptable range of hematite liberation (> 75%) was obtained in the laboratory ball mill after reducing 6 min from the total retention time taken in the Bond ball mill. © 2020, Society for Mining, Metallurgy & Exploration Inc.Item Exploring grinding and burnishing as surface post-treatment options for electron beam additive manufactured Alloy 718(Elsevier B.V., 2020) Karthick Raaj, R.; Vijay Anirudh, P.; Karunakaran, C.; Kannan, C.; Jahagirdar, A.; Joshi, S.; Balan, A.S.S.Numerous additive manufacturing (AM) techniques have been developed over the past decade. Features like immense freedom of intricate part design and shorter lead time make AM routes promising for a wide range of applications spanning aerospace, marine and automobile sectors. Among the various metal AM processes, Electron Beam Additive Manufacturing (EBAM) is being widely explored to realise the potential of Ni-based superalloys and Ti alloys for varied high-performance applications. A novel attempt has been made in this paper to assess the surface integrity of as-built EBAM nickel-based superalloy 718 (AB) subjected to grinding (G), Low Plasticity Burnishing (LPB) and their sequential combination. Apart from their influence on sub-surface microstructures, the effect of process variables during the above post-treatments on the residual stress profiles was also investigated. Results revealed that G + LPB results in about 0.6 ?m lower surface roughness, 17% improved microhardness compared to AB + LPB, and higher compressive surface residual stress as compared to LPB processed EBAM samples. The sequential grinding and LPB - improved microhardness, was also found to extend about 500 ?m more when compared to the LPB process. The G + LPB, which is greatly influenced by the prior grinding, smoothens the surface and thus results in a better surface finish. Highest hardness, superior surface finish, reduced porosity and improved compressive residual stress were observed in samples that adopted the AB + G + LPB sequence over other samples, with the LPB step at 40 MPa yielding the best results. © 2020 Elsevier B.V.Item Effect of cryogenic grinding on fatigue life of additively manufactured maraging steel(MDPI AG, 2021) Balan, A.S.S.; Kannan, C.; Kumar, A.V.; Hariharan, H.; Pimenov, D.Y.; Giasin, K.; Nadolny, K.Additive manufacturing (AM) is replacing conventional manufacturing techniques due to its ability to manufacture complex structures with near?net shape and reduced material wastage. However, the poor surface integrity of the AM parts deteriorates the service life of the components. The AM parts should be subjected to post?processing treatment for improving surface integrity and fatigue life. In this research, maraging steel is printed using direct metal laser sintering (DMLS) process and the influence of grinding on the fatigue life of this additively manufactured material was investigated. For this purpose, the grinding experiments were performed under two different grinding environments such as dry and cryogenic conditions using a cubic boron nitride (CBN) grinding wheel. The results revealed that surface roughness could be reduced by about 87% under cryogenic condition over dry grinding. The fatigue tests carried out on the additive manufactured materials exposed a substantial increase of about 170% in their fatigue life when subjected to cryogenic grinding. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Item Grinding parameters prediction under different cooling environments using machine learning techniques(Taylor and Francis Ltd., 2023) Prashanth, G.S.; Sekar, P.; Bontha, S.; Balan, A.S.S.Selection of optimum process parameters is vital for performing a sound grinding operation on Inconel 751 alloy. This paper co-relates the relationship between the most influential input parameters like cutting velocity, depth of cut, feed rate, and environmental conditions to the output parameters, namely, tangential grinding forces, normal grinding forces, temperature, and surface roughness. Three types of machine-learning (ML) algorithms such as support vector machine (SVM), Gaussian process regression (GPR), and boosted tree ensemble techniques are employed to develop a ML model for predicting the output variables during grinding operation of Inconel 751. In order to develop a better ML model, K-fold technique is employed on a total of 81 datasets which are extracted from experimental studies. ML models developed from different algorithms are compared based on performance metrics like R2 score and root-mean-square error (RMSE). GPR algorithm exhibits best results with relatively better R2 score and RMSE value in predicting grinding forces and temperature at wheel work interface. From analyzing the ML models, it is found that cooling environments determined the output grinding parameters to a greater extent when compared with the input grinding parameters. © 2022 Taylor & Francis.Item An overview of the applications of soft computing methods for predicting the physico-mechanical properties of rocks from indirect methods(Inderscience Publishers, 2023) Bijay Mihir Kunar, S.; Chandar, K.R.Rocks are widely used in infrastructure constructions like roads, tunnels, buildings, and dams. Understanding physico-mechanical properties of rocks is vital for selecting suitable rocks, yet some properties pose challenges in determination. High-quality core samples and precise instruments are necessary for accurate assessment. Predicting the physico-mechanical properties of rocks is a key research area in rock mechanics. Researchers have employed diverse methods, including laboratory tests, non-destructive tests, and mineralogical and petrographical characteristics, to determine rock properties. This article reviews the use of soft computing methods, artificial intelligence, and machine learning to predict rock properties through indirect methods. Indirect methods involve engineering indices tests, mineralogical and petrographical characteristics, and additional approaches such as electrical properties, crushability indices, thermal characteristics, and grinding characteristics. The article also proposes various artificial intelligence and machine learning techniques as potential future directions in prediction of rock properties. © © 2023 Inderscience Enterprises Ltd.Item Techno-economic analysis of integrated torrefaction and pelleting process(Taylor and Francis Ltd., 2025) Goyal, I.; Prasad, A.; Kumar, S.; Ojha, D.K.In this work, a techno-economic analysis of an integrated torrefaction and pelleting process is conducted. The proposed integrated process is a single-step process to produce torrefied rice straw pellets. The proposed process shall work as an alternative to the existing multi-step/multi-site process that has multiple disadvantages. Like the conventional process, the proposed process consists of cutting, drying, grinding, torrefaction, and pelleting unit. However, the proposed process doesn’t involve any external binder as the pelleting and torrefaction steps are merged. The binding is achieved by utilizing the lignin present naturally in the biomass and softens during the torrefaction step. The techno-economic assessment estimates that the briquetting process with a production capacity of 30,000 tons briquette/annum could be very profitable and shows a return on investment (ROI) of 30%, payout time of 2.4 years and break-even point of 42% at a selling price of briquette of 73 $/ton. © 2023 Taylor & Francis Group, LLC.