Journal Articles
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Item Degradation of paracetamol in aqueous solution by Fenton Oxidation and photo-Fenton Oxidation processes using iron from Laterite soil as catalyst(2011) Manu, B.; MahamoodFor the treatment of paracetamol in water, the photo-Fenton Oxidation process and Classic Fenton oxidation process have been demonstrated and found effective. An iron catalyst extracted from lateritic soil is used to exhibit the degradation and mineralization of paracetamol. Paracetamol reduction and chemical oxygen demand (COD) removal are measured as the objective functions to be maximized. The experimental conditions of the degradation of paracetamol are optimized by Fenton process. the optimum conditions observed for 10 mg/L initial paracetamol concentration are influent pH 3, initial H 2O 2 dosage 30 mg/L, [paracetamol]/[H 2O 2] ratio 1:3 (w/w) and [H 2O 2] / [Laterite iron] ratio 30:0.75 (w/w). At the optimum conditions, for 10 mg/L of initial paracetamol concentration, 76% paracetamol reduction and 69% COD removal by Fenton oxidation and 79% paracetamol reduction and 77% COD removal by UV-C Fenton process are observed in 120 minutes reaction time. At the above optimum conditions, HPLC analysis has demonstrated 100% removal of paracetamol for Fenton oxidation process in 240 minutes and for UV-C photo- Fenton process in 120 minutes. The methods are effective and they may be used in the paracetamol industry. © 2011 CAFET-INNOVA TECHNICAL SOCIETY.Item Enhanced degradation of paracetamol by UV-C supported photo-Fenton process over Fenton oxidation(2011) Manu, B.; Mahamood, S.For the treatment of paracetamol in water, the UV-C Fenton oxidation process and classic Fenton oxidation have been found to be the most effective. Paracetamol reduction and chemical oxygen demand (COD) removal are measured as the objective functions to be maximized. The experimental conditions of the degradation of paracetamol are optimized by the Fenton process. Influent pH 3, initial H 2O 2 dosage 60 mg/L, [H 2O 2]/[Fe 2+] ratio 60 : 1 are the optimum conditions observed for 20 mg/L initial paracetamol concentration. At the optimum conditions, for 20 mg/L of initial paracetamol concentration, 82% paracetamol reduction and 68% COD removal by Fenton oxidation, and 91% paracetamol reduction and 82% COD removal by UV-C Fenton process are observed in a 120 min reaction time. By HPLC analysis, 100% removal of paracetamol is observed at the above optimum conditions for the Fenton process in 240 min and for the UV-C photo-Fenton process in 120 min. The methods are effective and they may be used in the paracetamol industry. © IWA Publishing 2011.Item Pickup and delivery problem using metaheuristics techniques(2012) D'Souza, C.; Omkar, S.N.; Senthilnath, J.Dial-a-ride problem (DARP) is an optimization problem which deals with the minimization of the cost of the provided service where the customers are provided a door-to-door service based on their requests. This optimization model presented in earlier studies, is considered in this study. Due to the non-linear nature of the objective function the traditional optimization methods are plagued with the problem of converging to a local minima. To overcome this pitfall we use metaheuristics namely Simulated Annealing (SA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Immune System (AIS). From the results obtained, we conclude that Artificial Immune System method effectively tackles this optimization problem by providing us with optimal solutions. © 2011 Published by Elsevier Ltd. All rights reserved.Item Modelling and multi-objective optimisation of squeeze casting process using regression analysis and genetic algorithm(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2016) Gowdru Chandrashekarappa, G.C.; Krishna, P.; Parappagoudar, M.B.In the present work, an attempt has been made using statistical tools to develop a non-linear regression model and to identify the significant contribution of squeeze cast process parameters on surface roughness, hardness and tensile strength. Microstructure examination performed on the squeeze cast samples has revealed that a maximum of 100 MPa pressure is good enough to eliminate all possible casting defects. Accuracy of the developed models has been tested with the help of ten test cases. It is important to note that the developed models predict responses with a reasonably good accuracy and the developed mathematical input–output relationship helps the foundry-man to make better predictions. The present work comprises four objectives, which are conflicting in nature. Hence, mathematical formulation is used to convert four objective functions into a single objective function. The popular evolutionary algorithm, that is genetic algorithm has been utilised to determine the optimal process parameters. © 2015 Engineers Australia.Item Enhanced mobility aware routing protocol for Low Power and Lossy Networks(Springer New York LLC barbara.b.bertram@gsk.com, 2019) Sanshi, S.; Jaidhar, C.D.Due to the technological advancement in Low Power and Lossy Networks (LLNs), sensor node mobility becomes a basic requirement for many extensive applications. Routing protocol designed for LLNs must ensure real-time data transmission with minimum power consumption. However, the existing mobility support protocols cannot work efficiently in LLNs as they are unable to adapt to the change in the network topology quickly. Therefore, we propose an Enhanced Routing Protocol for LLNs (ERPL), which updates the Preferred Parent (PP) of the Mobile Node (MN) quickly whenever the MN moves away from the already selected PP. Further, a new objective function that takes the mobility of the node into an account while selecting a PP is proposed. Performance of the ERPL has been evaluated with the varying system and traffic parameters under different topologies similar to most of the real-life networks. The simulation results showed that the proposed ERPL reduced the power consumption, packet overhead, latency and increased the packet delivery ratio as compared to other existing works. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.Item Enhanced mobility routing protocol for wireless sensor network(Springer, 2020) Sanshi, S.; Jaidhar, C.D.Recently, the routing protocol for low power and lossy networks (RPL) was standardized and is considered as the default standard for routing over the low power and lossy networks. However, it has not been optimized to work effectively, especially under mobility, and suffers from frequent disconnections that result in packet loss and increased energy consumption. In this paper, an enhanced mobility routing protocol for wireless sensor network (EM-RPL) that incorporates modules to support the mobility of nodes has been proposed. The main goal of the EM-RPL is to increase network reliability and efficiency by selecting a route that is more stable and reduces the frequency of route discovery process. The performance of the proposed EM-RPL has been evaluated in the Contiki-based Cooja simulator and compared with the performance of other protocols that support mobility in the RPL. The simulation results demonstrated that the EM-RPL improves the packet delivery ratio and minimizes power consumption by allowing the mobile nodes to select a more stable path. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.Item Inverse approach using bio-inspired algorithm within Bayesian framework for the estimation of heat transfer coefficients during solidification of casting(American Society of Mechanical Engineers (ASME), 2020) Vishweshwara, P.S.; Gnanasekaran, N.; Arun, M.In any parameter estimation problem, it is desirable to obtain more information in one single experiment. However, it is difficult to achieve multiple objectives in one single experiment. The work presented in this paper is the simultaneous estimation of heat transfer coefficient parameters, latent heat, and modeling error during the solidification of Al-4.5 wt %Cu alloy with the aid of Bayesian framework as an objective function that harmoniously matches the mathematical model and measurements. A 1D transient solidification problem is considered to be the mathematical model/forward model and numerically solved to obtain temperature distribution for the known boundary and initial conditions. Genetic algorithm (GA) and particle swarm optimization (PSO) are used as an inverse approach and the estimation of unknown parameters is accomplished for both pure and noisy temperature data. The use of Bayesian framework for the estimation of unknown parameters not only provides the information about the uncertainties associated with the estimates but also there is an inherent regularization term in which the inverse problem boils down to well-posed problem thereby plethora of information is extracted with less number of measurements. Finally, the results of this work open up new prospects for the solidification problem so as to obtain a feasible solution with the present approach. © © 2020 by ASMEItem Selection of optimal composition of MR fluid for a brake designed using MOGA optimization coupled with magnetic FEA analysis(SAGE Publications Ltd, 2021) Acharya, S.; Saini, T.R.S.; Sundaram, V.; Kumar, H.The design of Magnetorheological (MR) brake and the composition of MR fluid (MRF) used in it have a significant effect on its performance and hence an effort has been made in this study to determine the optimal dimensions of MR brake and composition of MRF suitable for the brake application. Initially, optimum parameters of MR brake were computed considering the properties of commercially available MRF 132DG fluid using multi-objective genetic algorithm (MOGA) optimization. This was performed in MATLAB software coupled with magnetostatic analyses in ANSYS APDL software. The braking torque of designed MR brake utilizing MRF 132DG fluid was experimentally determined and validated with analytical ones. Further, selection of optimal composition of MRF was done considering In-house MRF samples composed of different combinations of particle mass fractions, mean particle diameters and base oil viscosities. A design of experiments (DOE) technique was employed and braking torque corresponding to the synthesized MRF samples at different speeds and current supplied were measured along with the variation of shaft speed during braking process. Grounded on the experimental results, using MOGA optimization technique, MRF composed of smaller sized iron particles (2.91 microns) with mass fraction of 80.95% and lower viscosity base oil (50 cSt) was selected as optimal composition of MRF for use in MR brake. Maximization of field induced braking torque and minimization of off-state torque were chosen as the objective functions for both the optimal design of MR brake and selection of optimal composition of MRF. Finally, the sedimentation stability of MRFs were investigated. © The Author(s) 2020.Item Optimal Placement and Sizing of Electric Vehicle Charging Infrastructure in a Grid-Tied DC Microgrid Using Modified TLBO Method(MDPI, 2023) Krishnamurthy, N.K.; Sabhahit, J.N.; Jadoun, V.K.; Gaonkar, D.N.; Shrivastava, A.; Rao, V.S.; Kudva, G.In this work, a DC microgrid consists of a solar photovoltaic, wind power system and fuel cells as sources interlinked with the utility grid. The appropriate sizing and positioning of electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) are concurrently determined to curtail the negative impact of their placement on the distribution network’s operational parameters. The charging station location problem is presented in a multi-objective context comprising voltage stability, reliability, the power loss (VRP) index and cost as objective functions. RES and EVCS location and capacity are chosen as the objective variables. The objective functions are tested on modified IEEE 33 and 123-bus radial distribution systems. The minimum value of cost obtained is USD 2.0250 × 106 for the proposed case. The minimum value of the VRP index is obtained by innovative scheme 6, i.e., 9.6985 and 17.34 on 33-bus and 123-bus test systems, respectively. The EVCSs on medium- and large-scale networks are optimally placed at bus numbers 2, 19, 20; 16, 43, and 107. There is a substantial rise in the voltage profile and a decline in the VRP index with RESs’ optimal placement at bus numbers 2, 18, 30; 60, 72, and 102. The location and size of an EVCS and RESs are optimized by the modified teaching-learning-based optimization (TLBO) technique, and the results show the effectiveness of RESs in reducing the VRP index using the proposed algorithm. © 2023 by the authors.Item Novel Fuzzy-based Objective Function for routing protocol for low power and lossy networks(Elsevier B.V., 2023) Kamble, S.; Bhilwar, P.; Chandavarkar, B.R.In both wired and wireless networks, data routing along the best path is constantly a top priority for the research community. Currently, the most widely adopted routing algorithms in the Internet of Things is the Routing Protocol for Low Power and Lossy Networks (RPL). In RPL, selecting the optimal path primarily depends on the Objective Function (OF). Multi-attribute OFs are thought to be a viable method for choosing the best path, but the main concern here is how these attributes must be coupled. Such issues are being taken care by fuzzy based technologies as it deals with imprecise or distorted attribute values. Most of the fuzzy logic-based OFs are mainly based on the Mamdani method, which has low accuracy. However, a better accuracy is observed in Takagi–Sugeno method. Hence the paper develops a Fuzzy-based Takagi and Sugeno Objective Function (FTSOF) for RPL. The FTSOF technique combines the routing metrics to give a crisp value based on which the parent node is selected. The proposed approach is implemented in the Contiki operating system. The simulation was carried out on different network densities and various data rates. The performance parameters considered are packet delivery ratio, latency, network setup time, and control message overhead. The results shows that FTSOF outperforms the state-of-the-art techniques such as OF-0, MRHOF, and the Fuzzy-based Mamdani Objective Function (FMOF). © 2023 Elsevier B.V.