Faculty Publications
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Item Assessment of hydropower potential in Nethravathi river basin using SWAT model(CAFET INNOVA Technical Society cafetinnova@gmail.com 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2015) Babar, S.; Shobhita, M.P.; Ramesh, H.Hydropower plants have the advantage of producing renewable and clean power, the renewable and reliable energy source that serves national environmental and energy policy objectives. Therefore, the development of hydropower plant and improvements of water management have essential in contributing to sustainable growth and energy production in developing countries like India. The present study is concerned with the development of methodology and assessment of hydropower potential in the Nethravathi River basin with the help of Remote Sensing and GIS. The drainage area covers about 3190 km2 at Bantwal gauging point, and most of the land cover of the basin is dominated by forest. The basin was divided into six sub-basins based on hydrology and topography using GIS tools. The climate over the basin is coastal humid tropical and receives an average annual rainfall of about 4000 mm. sub-basin discharges were estimated using the Soil Conservation Services (SCS) curve number method. To ensure the total discharge from six sub-basins computed from SCS curve number method, the flows were routed and simulated at the gauging location using Soil and Water Assessment Tool (SWAT). SWAT model was calibrated for monthly time steps from 1998–2001, and validated for 2002–2003. Flow-duration curves (FDC) were generated for each sub-basin to assess the dependable yield. The results have shown a good agreement between observed and the simulated flows. The available discharge at 75%, 80% and 90% of time for each sub-basin were extracted from the FDC. This result were used to calculate the hydropower potential in all the six sub-basins at Q75, Q80 and Q90, by integrating thematic layers using ArcSWAT. © 2015 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.Item Studies on application of vertical axis hydro turbine for sustainable power generation in irrigation channels with different bed slopes(Elsevier Ltd, 2021) Shashikumar, S.; Honnasiddaiah, R.; Hindasageri, V.; Madav, V.The present work is carried out to study the performance of a Savonius rotor for small-scale hydropower generation. It has been observed that some of the irrigation channels available in the rural areas are having enough bed slope to generate kinetic energy, which can be harnessed through a Savonius rotor. An in-house fabricated scale-down model of the Savonius rotor is tested at an inclination of the re-circulating indoor multipurpose tilting flume at 0°, 0.5°, 1.0°, 1.5° and 2.0° to determine performance under controlled conditions. It is observed that at the tip speed ratio of 0.92 and channel inclination of 0.5° compared to 0° inclination, the coefficient of power and coefficient of torque improved to 40% and 10%, respectively. Furthermore, it is found that the torque and power developed by the turbine are maximum at a bed slope of 2.0° owing to the maximum available energy. © 2020 Elsevier LtdItem Estimating Long-Run Relationship between Renewable Energy Use and CO2 Emissions: A Radial Basis Function Neural Network (RBFNN) Approach(MDPI, 2022) Jena, P.R.; Majhi, B.; Majhi, R.The long-run relationship between economic growth and environmental quality has been estimated within the framework of the environmental Kuznets Curve (EKC). Several studies have estimated this relationship by using statistical models such as panel regression and time series regression. The current study argues that there is a nonlinear relationship between environmental quality indicators and economic and non-economic predictors and hence an appropriate nonlinear model is required to predict it. An adaptive and nonlinear model, namely radial basis function neural network (RBFNN) has been developed in this study. CO2 emission is used as the target output and renewable energy consumption share, real GDP, trade openness, urban population ratio, and democracy index are used as the predictors to estimate the EKC relationship for nineteen major CO2 emitting countries that account for 78% of the global emissions. The model developed in this study could predict the CO2 emissions of all the countries with more than 95% accuracy. This finding underlines the usefulness of the RBFNN model which can be used to predict emission levels of other pollution indicators at the global level. Further, comparing two models, one with all the predictors and the other excluding the renewable energy share, it was found that the model with renewable energy share predicts CO2 emissions more accurately. This reinforces the already strengthening campaign to encourage industries and governments to increase the share of renewable energy in total energy use. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Item Implementation of tubercles on Vertical Axis Wind Turbines (VAWTs): An Aerodynamic Perspective(Elsevier Ltd, 2022) Sridhar, S.; Joseph, J.; Radhakrishnan, J.In recent days, enhancement of Vertical Axis Wind Turbines (VAWTs) by mitigating flow deteriorating effects like dynamic stalling, unsteady wake is given great importance. The following article focuses on implementing four different tubercles on the blades’ leading edge and studying its performance and flow characteristics using CFD techniques. Results indicate that the addition of tubercles generated counter-rotating vortices and delayed flow separation and helped control dynamic stalling. Between azimuth angles 70°–160°, the flow was seen to separate only along the trough regions of the blade and remained attached along the peak regions, thus providing more torque and power. In addition to the enhancements in the flow characteristics, a 28% increase in power coefficient was observed for the optimal configuration at the optimal tip speed ratio. Additionally, a 14% increase in maximum lift generated by the blade was observed. Preliminary aeroacoustics analysis revealed a 12% and 20% decrease in the noise emissions along the blade tip and mid-plane of the turbine, respectively. Hence, it can be shown that tubercles effectively control dynamic stall, reduce noise emissions, and increase the power output of VAWTs. © 2022 Elsevier LtdItem Effect of dry torrefaction pretreatment of the microwave-assisted catalytic pyrolysis of biomass using the machine learning approach(Elsevier Ltd, 2022) Ramesh, R.; Suriapparao, D.V.; Sankar Rao, C.S.; Sridevi, V.; Kumar, A.This study employs the Leave-One-Out cross-validation approach to build a machine-learning model using polynomial regression to predict pyro product yield through microwave-assisted pyrolysis of sawdust over KOH catalyst and graphite powder a susceptor. The determination of coefficient (R2) validates the developed models. All the developed models achieved a high prediction accuracy with R2 > 0.93, which signifies that the experimental values are in good agreement with the predicted one. The dependence of the catalyst loading and pretreatment temperature on dominating process parameters such as heating rate, pyrolysis temperature, susceptor thermal energy, and pyro products, namely bio-oil, biochar, and biogas, are explored. The yield of biochar is reduced; however, bio-oil and biogas are enhanced as the catalyst loading increased. On the other hand, increasing the temperature of pretreated sawdust decreased bio-oil and biogas yields while increasing biochar yields. Further, microwave conversion efficiency, and susceptor thermal energy increased with increased catalyst quantity and pretreatment temperatures of sawdust. It was observed that the average heating rate was increased by increasing the catalyst quantity while maintaining the same pyrolysis time until pretreatment temperatures of 150 °C were reached, after which the heating rate dropped due to the continuous microwave energy input to the system. © 2022 Elsevier LtdItem Thermal performance assessment of a cylindrical box solar cooker fitted with decahedron outer reflector(SAGE Publications Inc., 2023) Anilkumar, B.C.; Maniyeri, R.; Anish, S.One of the important issues humankind globally faces in recent years is the scarcity of non-renewable energy resources. Solar energy is considered safe and renewable, which can fulfil the demand and supply chain requirements. Solar box cookers (SBCs) are popular in domestic cooking due to their ease of use and handling. The prime objective of the present work is to develop and test the performance of a cylindrical SBC fitted with decahedron-shaped reflector (CSBC-FDR). The CSBC is designed using minimum entropy generation (MEG) method. Through experiments, we observed that absorber plate attains peak temperature of about 138°C–150°C with the aid of decahedron reflector. The first figure of merit (F1) is found to be 0.13, indicating better optical efficiency and low heat loss coefficient for the SBC. The second figure of merit (F2) is obtained as 0.39, which indicates good heat exchange efficiency (F') and less heat capacity for cooker's interior. The average energy efficiency, exergy efficiency, and standardized cooking power values are 21.93%, 3.04%, and 25.28W, respectively. These results show that the present CSBC-FDR is able to cook food in a shorter period with better efficiency. The experimental and numerical values of overall heat loss coefficient of the developed SBC are in close agreement. The experimentally assessed performance parameters reveal superior performance of the present cylindrical SBC in comparison with many conventional rectangular and trapezoidal box solar cookers. © The Author(s) 2021.Item A smart and sustainable energy approach by performing multi-objective optimization in a minichannel heat sink for waste heat recovery applications(Elsevier Ltd, 2023) Narendran, G.; Jadhav, P.H.; Gnanasekaran, N.Minichannel heat sink is widely used in waste heat recovery systems for their compactness and ability to recover heat effectively from high heat flux applications. However, the heat recovery efficiency is constrained by the flow configurations resulting in flow maldistribution. Numerous neural network combined evolutionary algorithms have been used to reduce pressure drop and flow maldistribution factors in the literature. But it is very challenging to assign appropriate weights to these parameters with no physical significance between them for optimization studies. To overcome this, TOPSIS-based optimization studies have been used in the current work to reduce the flow maldistribution factor (ϕ) and increase the Nusselt number (Nu) with ribs and inclined structures. Four Minichannel designs are studied to assess the channel heat recovery efficiency from small-scale incinerators using water and Graphene oxide (GO) nanofluid for three different volume fractions of GO-0.02%, GO-0.07%, and GO-0.12%. The motive is to determine an optimal nanofluid volume fraction and a suitable Minichannel configuration for the given heat flux. The TOPSIS method handles five criteria, including the combination of weightage for the maldistribution factor and Nusselt number. For criteria I ((ϕ)min: (Nu)max = 0.0:1.0) maximum weightage is given to heat transfer, the ribbed channel has gained a higher performance score for GO-0.07% nanofluid volume fraction. For criteria V ((ϕ)min: (Nu)max = 1.0:0.0) maximum weightage is given to maldistribution reduction, the ribbed inclined channel has gained with significantly higher performance score for all the studied nanofluid volume fractions. Further, the study is extended to determine the heat recovery efficiency, and it is found that with the increase in mass flow rate and nanofluid volume fraction, the heat recovery efficiency increases significantly. In particular, the maximum heat recovery efficiency of 66% was obtained for ribbed Minichannel using GO-0.12% nanofluid. © 2023 Elsevier LtdItem Modified Odd–Even–Prime pattern for effective dispersion of shade over the PV array under partial shading conditions(Elsevier Ltd, 2024) Ramesh, D.; Karthikeyan, A.Photovoltaic (PV) arrays are extensively used for power generation being the most abundant renewable energy sources available. Partial shading of the PV array leads to mismatch between the modules and decrease in output power. A new Modified Odd–Even–Prime (MOEP) method of module arrangement for total cross tied (TCT) connection is presented in this paper to mitigate the effects of partial shading. The proposed MOEP method is a physical relocation method where the modules of PV array are relocated without altering the electrical connections. MOEP method of module rearrangement is based on row positions of the PV array. In this method, the row positions of PV modules in the first column are filled with odd, even and prime numbers in ascending order. The row positions of further columns are formed based on MOEP method. The proposed MOEP method is implemented on 9 × 9 and 8 × 8 PV arrays under various shading patterns. Further, the results are compared with TCT, Odd Even (OE) and Odd–Even–Prime (OEP) patterns. MATLAB/Simulink is used to validate the results. An experimental setup of 9 × 9 and 8 × 8 PV array is developed and tested in real time environment to validate the effectiveness of MOEP method over TCT, OE and OEP methods. The performance of proposed MOEP method is evaluated in terms of GMPP, mismatch power loss (MPL), Fill Factor (FF), Efficiency (η) and Shade Dispersion Ratio (SDR). A detailed study on energy savings from the proposed MOEP method is made on hourly, daily and yearly basis. From the experimental results obtained, it is observed that MOEP method generates a significant improvement in GMPP, efficiency and reduces the mismatch loss compared to TCT, OE and OEP methods. © 2024 International Solar Energy SocietyItem Performance analysis of a 50 MW grid-connected solar PV system for sustainable mining operations(World Researchers Associations, 2025) Shiva Kumar, B.S.; Kunar, B.M.; Murthy, C.S.N.The strategic use of renewable resources has become essential for guaranteeing energy security in response to rising energy demands. Mining operations require creative solutions to provide steady energy delivery because of their high energy needs and dependence on continuous power. A technically sound and financially advantageous option for extensive energy integration in these industries is grid-connected photovoltaic (PV) system. The performance of 50 MW grid-connected solar PV power plant in Peddapalli, a major mining hub with ideal solar conditions, is assessed in this study. With an average yearly temperature of 27.3°C and a mean solar insolation of 4.97 kWh/m2, the plant uses a seasonal tilt approach to maximize solar energy capture. A quarterly energy yield of 15,798.192 MWh, a capacity utilization factor (CUF) of 17.68% and a performance ratio (PR) of 86.12% are examples of key performance measures. By successfully integrating solar PV technology into mining operations, operational expenses and carbon emissions are decreased while issues with energy stability are resolved. This study provides helpful insights for utilizing renewable energy in energy-intensive businesses by highlighting the necessity of robust architecture, stable buildings and efficient energy management to maintain a consistent power supply. © 2025, World Researchers Associations. All rights reserved.Item Analysing the role of globalisation, institutional qualities, and renewable energy consumption in environmental degradation mitigation: the SAARC experience(Springer Science and Business Media B.V., 2025) Padhan, L.; Bhat, S.The main purpose of this work is to investigate the impacts of four different dimensions of globalisation (financial, trade, social, and political), institutional qualities, and renewable energy consumption on ecological footprints and carbon dioxide (CO2) emissions in the Environmental Kuznets Curve (EKC) framework. For quantitative analysis, this study includes yearly data from 1995 to 2020 for five South Asian Association for Regional Cooperation (SAARC) nations: Bangladesh, India, Nepal, Pakistan, and Sri Lanka. SAARC countries are the most vulnerable to climate change and fast economic transitions. The study employs the second-generation panel unit root test, the Westerlund cointegration technique, and the Driscoll-Kraay (DK) Standard Errors regression technique. The study shows that social globalisation, institutional quality, renewable energy consumption, and industrialisation benefit the environment by lowering the ecological footprint and CO2 emissions. Trade and political globalisation are harmful to the environment as both indicators have a significant positive impact on ecological footprint and CO2 emissions. Financial globalisation has a significant negative impact on only CO2 emissions and is not significant in the case of ecological footprint. Further, the empirical estimates validate the inverted U-shaped EKC hypothesis concerning ecological footprints and CO2 emissions. Furthermore, the robustness of long-term outcomes has been examined using the FMOLS and DOLS techniques. The present work suggests that SAARC countries can achieve a cleaner environment by adopting renewable energy, implementing strong institutional qualities, and promoting efficient technologies through globalisation. © The Author(s), under exclusive licence to Springer Nature B.V. 2023.