Faculty Publications
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Publications by NITK Faculty
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Item Applications of computer in mining industry with special regard to shovel-dumper productivity(2007) Mangalpady, M.; Murthy, Ch.S.N.; Pai, R.; Nand, R.Now-a-days computer is used in every field of engineering, including mining industry, at various stages in various capacities. One of the major problems in surface mining is material handling, which involves transportation of both ore and overburden. Most of the projects make use of shoveldumper system in spite of its huge capital investment and recurring costs. Hence a lot of mind and time has to be devoted before its procurement so as to optimize their number and maximize its utility. This paper addresses various optimization models available for productivity analysis of shovel-dumper fleet. Match factor method is one of the commonly used techniques to know the relative coverage which shovels are getting from truck fleet. Operations research techniques like queuing theory, integer programming, simulation and goal programming consider the probabilistic nature associated with the system. Even though many models are available for optimization and analyzing the productivity of shovel dumper system, further research and study is needed to devise a desirable technique for the same.Item Experimental analysis of SI engine performance and emission characteristics with gasoline-denatured spirit blends as alternative fuels(2010) Hubballi, P.A.; Ashok Babu, T.P.The experimental study focused on investigating benefits of unleaded gasoline (P100) - denatured spirit [DNS (ethanol 93.3% v/v + water 6.7% v/v)] blends as fuel in a four cylinder four stroke SI engine. Performance tests were conducted to study volumetric efficiency (VolE), brake thermal efficiency (BThE), brake power (BP), engine torque (torque), brake specific fuel consumption (BSFC). Engine exhaust emissions were investigated for carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NOx) and carbon dioxide (CO2). Experiments were conducted at different engine speeds between 2500 - 4500 rpm maintaining throttle position of 50% throughout the experiments. The fuel blends used include DNS30P70 (ethanol 28 % + water 2% + gasoline 70 %), DNS50P50 (ethanol 46.65 % + water 3.35 % + gasoline 50 %) and DNS85P15 (ethanol 79.3 % + water 5.7 % + gasoline 15 %) which were compared with base fuel P100. The investigations revealed that blending DNS with P100 increases BThE, VolE, BP, torque and BSFC. The CO, HC, NOx and CO2 emissions in the exhaust decrease when compared to P100 operation. The DNS85P15 blend produced encouraging results in improved engine performance and decreased engine exhaust emission.Item Behavioral study of alumina nanoparticles in pool boiling heat transfer on a vertical surface(2011) Hegde, R.N.; Reddy, R.P.; Rao, S.S.Experiments were carried out to investigate the pool boiling of alumina-water nanofluid at 0.1 g/l to 0.5 g/l of distilled water, and the nucleate pool boiling heat transfer of pure water and nanofluid at different mass concentrations were compared at and above the atmospheric pressure. At atmospheric pressure, different concentrations of nanofluids display different degrees of deterioration in boiling heat transfer. The effect of pressure and concentration of nanoparticles revealed significant enhancement in heat flux and deterioration in pool boiling. The heat transfer coefficient of 0.5 g/l alumina-water nanofluid was compared with pure water and clearly indicates deterioration. At all pressures the heat transfer coefficients of the nanofluid were lower than those of pure water. Experimental observation revealed particles coating over the heater surface and subsequent SEM inspection of the heater surface showed nanoparticles coating on the surface forming a porous layer. To substantiate the nanoparticle deposition and its effect on heat flux, investigation was done by measuring the surface roughness of the heater surface before and after the experiment. While SEM images of the heater surface revealed nanoparticle deposition, surface roughness of the heater surface confirmed it. Based on the experimental investigations it can be concluded that an optimum thickness of nanoparticles coating favors an increase in heat flux. Higher surface temperature due to the presence of nanoparticles coating results in the deterioration of boiling heat transfer. © 2011 Wiley Periodicals, Inc.Item Effects of energy price rise on investment: Firm level evidence from Indian manufacturing sector(Elsevier, 2015) Sadath, A.C.; Rajesh Acharya, H.R.This paper analyses the effects of the rising prices of energy products on the investment of a large panel of manufacturing firms in India during 1993-2013. The prime motivation behind this study is the absence of an empirical study into this research issue exclusively on Indian economy. The empirical results obtained by estimating an Error Correction Model (ECM) using Generalized Method of Moments (GMM) show that energy price rise has negative effect on the investment of firms in the manufacturing sector. The negative effect is transmitted to the firm's investment through both demand-side and supply-side factors. The transmission also depends upon factors such as the energy intensity of production. The results also show that the sales-growth-investment relationship becomes weak in the face of the rising prices of the energy which could be due to the cautious approach to investment adopted by the firms. Therefore, it calls for the attention of the policy makers to evolve a comprehensive energy-policy to ensure continuous supply of energy at affordable prices to the manufacturers. © 2015 Elsevier B.V.Item Thermal and cost analysis of various air filled double glazed reflective windows for energy efficient buildings(Elsevier Ltd, 2020) Gorantla, G.; Saboor, S.; Vali, S.S.; Mahapatra, D.; Talanki Puttaranga Setty, A.B.; Kim, K.-H.The enormous amount of energy is being consumed by buildings in an attempt to deliver thermal comfort in buildings. This paper aims at reducing/increasing the total solar heat gain through various combinations of double glazed reflective windows of buildings. The spectral characteristics of six reflective glasses namely bronze, green, grey, opal blue, sapphire blue and gold-reflective glasses at a normal angle of incidence by using UV-3600 Shimadzu spectrophotometer according to ASTM E 424 standards were experimentally measured. The solar optical properties of the glasses were deduced by developing a MATLAB code using spectral data which was obtained from experiments in the solar spectrum wavelength range of 300 nm–2500 nm. Thirty air-filled double-glazed reflective windows have been studied for both thermal and cost analysis in the Indian composite climatic zone (New Delhi 28.580 N, 77.200 E). The configuration C13 (Grey reflective glass-Air gap 10 mm-Gold reflective glass) is observed to be the best air-filled double glazed window from the highest annual cost savings ($ 79.29 per annum in SE direction) and lower payback period (1.42 years) point of views among thirty double-glazed reflective glasses studied. The results of this paper are useful in the design of sustainable passive solar buildings. © 2019 Elsevier LtdItem Fine-grained data-locality aware MapReduce job scheduler in a virtualized environment(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2020) Jeyaraj, R.; Ananthanarayana, V.S.; Paul, A.Big data overwhelmed industries and research sectors. Reliable decision making is always a challenging task, which requires cost-effective big data processing tools. Hadoop MapReduce is being used to store and process huge volume of data in a distributed environment. However, due to huge capital investment and lack of expertise to set up an on-premise Hadoop cluster, big data users seek cloud-based MapReduce service over the Internet. Mostly, MapReduce on a cluster of virtual machines is offered as a service for a pay-per-use basis. Virtual machines in MapReduce virtual cluster reside in different physical machines and co-locate with other non-MapReduce VMs. This causes to share IO resources such as disk and network bandwidth, leading to congestion as most of the MapReduce jobs are disk and network intensive. Especially, the shuffle phase in MapReduce execution sequence consumes huge network bandwidth in a multi-tenant environment. This results in increased job latency and bandwidth consumption cost. Therefore, it is essential to minimize the amount of intermediate data in the shuffle phase rather than supplying more network bandwidth that results in increased service cost. Considering this objective, we extended multi-level per node combiner for a batch of MapReduce jobs to improve makespan. We observed that makespan is improved up to 32.4% by minimizing the number of intermediate data in shuffle phase when compared to classical schedulers with default combiners. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.Item Novel Stock Crisis Prediction Technique - A Study on Indian Stock Market(Institute of Electrical and Electronics Engineers Inc., 2021) Naik, N.; Mohan, B.R.A stock market crash is a drop in stock prices more than 10% across the major indices. Stock crisis prediction is a difficult task due to more volatility in the stock market. Stock price sell-offs are due to various reasons such as company earnings, geopolitical tension, financial crisis, and pandemic situations. Crisis prediction is a challenging task for researchers and investors. We proposed a stock crisis prediction model based on the Hybrid Feature Selection (HFS) technique. First, we proposed the HFS algorithm to removes the irrelevant financial parameters features of stock. The second is the Naive Bayes method is considered to classify the strong fundamental stock. The third is we have used the Relative Strength Index (RSI) method to find a bubble in stock price. The fourth is we have used moving average statistics to identify the crisis point in stock prices. The fifth is stock crisis prediction based on Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN) regression method. The performance of the model is evaluated based on Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error(RMSE). HFS based XGBoost method was performed better than HFS based DNN method for predicting the stock crisis. The experiments considered the Indian datasets to carry out the task. In the future, the researchers can explore other technical indicators to predict the crisis point. There is more scope to improve and fine-tune the XGBoost method with a different optimizer. © 2013 IEEE.Item Sustainable reflective triple glazing design strategies: Spectral characteristics, air-conditioning cost savings, daylight factors, and payback periods(Elsevier Ltd, 2021) Gorantla, K.; Saboor, S.; Kontoleon, K.J.; Mazzeo, D.; Maduru, V.R.; Vali, S.V.Buildings with conventional glazing systems are responsible for excessive cooling and heating costs. Sustainable use of energy in building environments requires the use of high-performing opaque and windowed walls. Triple glazing units attenuate solar heat gain/loss compared to single- and double-glazing assemblies, thus reducing air-conditioning costs and greenhouse gas emissions. The optical, energy, economic and environmental performances of a glazing unit are strictly correlated with each other. An improvement of optical properties leads to higher glazing energy performance, cost savings, and greenhouse gas emission mitigations. This work aims to suggest and define an energy-efficient triple glazing unit for lowering cooling and heating costs in buildings while experimentally testing the spectral performance of reflective glasses and assessing heat gains/losses. In this regard, bronze, green, grey, sapphire blue, and gold reflective glasses were considered and settled in sixty different triple glazing combinations. Spectral characteristics of reflective glasses were measured experimentally using a spectrophotometer over the entire solar spectral range (300–2500 nm). For the aims of this investigation, a numerical model was developed to assess the net annual cost saving ($/m2) and the payback period of the examined glazing units for the eight cardinal directions (N, N-E, E, S-E, S, S–W, W and N–W). The results confirmed that the TWG35 window glass unit in the S-E orientation was the most energy-efficient glazing in terms of alleviating this critical challenge (air-conditioning cost-saving 16.72 $/m2 among all other studied window glass units), while a payback period of 2.2 years was revealed. On the other hand, the TWG33 window glass unit has led to the optimal-lowest payback period (2.1 years), with a net annual cost saving of 16.55 $/m2. The findings of this paper demonstrate the significance of triple-glazing design approaches from an economic and environmental point of view. © 2021 Elsevier LtdItem Improved Gamma type Y-source inverter for rooftop PV based V-G applications(Elsevier Ltd, 2022) Reddivari, R.; Jena, D.Renewable energy generation is inherently unpredictable and may contain unacceptably significant variations. In particular, high solar photovoltaic (PV) penetration makes it difficult for utility companies to coordinate production and consumption on the grid. PV generation with an energy storage element flattens the duck curve and eliminates the PV curtailment during the mid-day hours. This paper proposes a novel improved Gamma (Γ-) type Y-source inverter for rooftop photovoltaic (PV)-grid applications with battery storage ability. The proposed inverter can maintain high voltage gain even under partial shading conditions, where the PV voltage at the maximum power point is far away from the open circuit PV voltage. The proposed inverter allows plant owners to charge the battery from PV source during low-peak loading hours and can reduce power import during high-peak loading hours (or) export the excess power to the distribution grid, which increases the return on investment. The operation of the proposed inverter is analysed in three modes (a) stand-alone operational mode without battery, (b) stand-alone operational mode with battery, and (c) stand-alone operational mode with PV and battery. A scaled-down laboratory prototype of 70 W is created to test the functionality of the proposed inverter and validate the simulation results. Experiments show that the proposed Improved Gamma type YSI can generate a boosted ac voltage using independent PV and battery sources, as well as their combination. © 2022 Elsevier LtdItem Is the effect of oil price shock asymmetric on the Indian stock market? Firm-level evidence from energy-intensive companies(Emerald Publishing, 2023) Aruna, B.; Rajesh Acharya, R.H.Purpose: This paper aims to examine the asymmetric impact of the oil price increase and decrease on stock returns at the firm level. Design/methodology/approach: To ascertain the impact oil price can exert on the stock price at the firm level, this study uses panel structural vector auto regression with various linear and nonlinear measures of oil price shock on a data set, containing 1,168 firms listed in Indian stock markets. This study also considers stock index returns, Fama-French factors and inflation as control variables. Findings: This paper finds evidence that at firm level, net oil price increase and decrease have an asymmetric impact on stock returns. Other oil price shock measures, namely, shock because of oil price increase and decrease, do not show any sign of asymmetric impact on stock returns. Originality/value: The comparison of firm-level return on its response towards oil price fluctuation can give valuable insights into a firm’s features. © 2022, Emerald Publishing Limited.