Showing papers by "Indian Institute of Technology Bhubaneswar published in 2013"

Supercapacitor electrodes based on layered tungsten disulfide-reduced graphene oxide hybrids synthesized by a facile hydrothermal method.

Abstract: We report here the synthesis of layer structured WS2/reduced graphene oxide (RGO) hybrids by a facile hydrothermal method for its possible application as supercapacitor materials in energy storage devices. The prepared two-dimensional materials are characterized thoroughly by various analytical techniques to ascertain their structure and to confirm the absence of any impurities. Two-electrode capacitance measurements have been carried out in aqueous 1 M Na2SO4. The WS2/RGO hybrids exhibited enhanced supercapacitor performance with specific capacitance of 350 F/g at a scan rate of 2 mV/s. The obtained capacitance values of WS2/RGO hybrids are about 5 and 2.5 times higher than bare WS2 and RGO sheets. Because of the unique microstructure with combination of two layered materials, WS2/RGO hybrids emerge as a promising supercapacitor electrode material with high specific capacitance, energy density, and excellent cycling stability.

Superior field emission properties of layered WS2-RGO nanocomposites.

Abstract: We report here the field emission studies of a layered WS2-RGO composite at the base pressure of ~1 × 10−8 mbar. The turn on field required to draw a field emission current density of 1 μA/cm2 is found to be 3.5, 2.3 and 2 V/μm for WS2, RGO and the WS2-RGO composite respectively. The enhanced field emission behavior observed for the WS2-RGO nanocomposite is attributed to a high field enhancement factor of 2978, which is associated with the surface protrusions of the single-to-few layer thick sheets of the nanocomposite. The highest current density of ~800 μA/cm2 is drawn at an applied field of 4.1 V/μm from a few layers of the WS2-RGO nanocomposite. Furthermore, first-principles density functional calculations suggest that the enhanced field emission may also be due to an overalp of the electronic structures of WS2 and RGO, where graphene-like states are dumped in the region of the WS2 fundamental gap.

Role of behavioural factors in green supply chain management implementation in Indian mining industries

Abstract: Green supply chain management (GSCM) integrates ecological concepts with those of supply chain management in order to minimize energy and material usage and to reduce adverse impacts of supply chain activities on the environment. GSCM implementation in mining industries depends largely upon certain factors which are influenced by human behaviours. Human behaviour is dynamic in nature and the relationships between them continuously evolve and change. In this ever-changing context, therefore, identifying and ranking the behavioural factors that affect GSCM implementation becomes essential. This can be taken as a reference by the decision makers while deciding the hierarchy of action necessary for effective implementation of green practices in mining supply chains. The present research attempts to explore various behavioural factors affecting GCSM practices and their interactions which help to attain green-enabled needs. Interpretive structural modelling (ISM) is employed in this research to extract the interrelationships among the identified behavioural factors.

Effect of Metakaolin Content on the Properties of High Strength Concrete

Abstract: This study presents the effect of incorporating metakaolin (MK) on the mechanical and durability properties of high strength concrete for a constant water/binder ratio of 0.3. MK mixtures with cement replacement of 5, 10 and 15 % were designed for target strength and slump of 90 MPa and 100 ± 25 mm. From the results, it was observed that 10 % replacement level was the optimum level in terms of compressive strength. Beyond 10 % replacement levels, the strength was decreased but remained higher than the control mixture. Compressive strength of 106 MPa was achieved at 10 % replacement. Splitting tensile strength and elastic modulus values have also followed the same trend. In durability tests MK concretes have exhibited high resistance compared to control and the resistance increases as the MK percentage increases. This investigation has shown that the local MK has the potential to produce high strength and high performance concretes.

Wavelet Singular Entropy-Based Islanding Detection in Distributed Generation

Abstract: The paper presents wavelet singular entropy (WSE)-based islanding detection in distributed generation (DG) interfaced to the microgrid. Initially, the three-phase voltage signals retrieved at the target DG location are processed through wavelet transform (WT) to derive detailed coefficient at different levels of decomposition. From the detailed coefficients, the singular value matrix is generated and the WSE for each phase is calculated. Finally, the WSE index (WSEI) for islanding detection is computed by adding the WSE of each phase. The proposed WSEI is able to detect islanding within 10 ms (half cycle) from the event inception, showing the speed of the developed technique. It is observed that WSEI is highly effective in islanding detection, including different islanding and nonislanding conditions in the initial test system and standard microgrid with wide variations in operating parameters.

Compliance Analysis of PMU Algorithms and Devices for Wide-Area Stabilizing Control of Large Power Systems

Abstract: For the first time, IEEE Std. C37.118.1-2011 now provides metrics for PMU dynamic performance in terms of classes P and M filter designs. This paper attempts to determine whether fulfilling these requirements makes the PMU inherently well suited for stability control applications such as wide-area power system stabilizers (PSSs). In this aim, we considered two different frequency-adaptive approaches for class-P and -M compliance to ensure operation over a wide frequency range. The first is based on a finite-impulse response (FIR) with no overshoot in either the phase or the amplitude step responses, while the second is Kalman filter-based (EKF), which allows for a more refined out-of-band interference rejection at the cost of a phase step response with overshoot. These two approaches are benchmarked against Hydro-Quebec`s existing PSS requirements and the conclusion is that the total vector error-based response time is not indicative of the phase lag within the frequency band of interest, nor of the 3-dB bandwidth under sinusoidal amplitude/frequency modulation phenomena, which are key criteria when specifying PSS PMUs. Using simulated and field-recorded network fault responses, we also show that a class-M PMU is unsatisfactory for wide-area stabilizing control, unless its performance is improved during the fault period, which is not covered by Std. C37.118.1-2011.

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model

Abstract: The performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real-time prediction of tropical cyclones (TCs) over the north Indian Ocean (NIO) at 27-km resolution is evaluated on the basis of 100 forecasts for 17 TCs during 2007‐11. The analyses are carried out with respectto1)basinsofformation,2)straight-movingandrecurvingTCs,3)TCintensityatmodelinitialization, and 4) season of occurrence. The impact of high resolution (18 and 9km) on TC prediction is also studied. Model results at 27-km resolution indicate that the mean track forecast errors (skill with reference to persistence track) over the NIO were found to vary from 113 to 375km (7%‐51%) for a 12‐72-h forecast. The model showed a right/eastward and slow bias in TC movement. The model is more skillful in track prediction when initialized at the intensity stage of severe cyclone or greater than at the intensity stage of cyclone or lower. The model is more efficient in predicting landfall location than landfall time. The higher-resolution (18 and 9km) predictions yield an improvement in mean track error for the NIO Basin by about 4%‐10% and 8%‐24%, respectively. The 9-km predictions were found to be more accurate for recurving TC track predictions by ;13%‐28% and 5%‐15% when compared with the 27- and 18-km runs, respectively. The 9-km runs improve the intensity prediction by 15%‐40% over the 18-km predictions. This study highlights the capabilities of the operational ARW model over the Indian monsoon region and the continued need for operational forecasts from high-resolution models.

Freeze-dried WS2 composites with low content of graphene as high-rate lithium storage materials

Abstract: Few layered WS2–graphene nanosheet composites are prepared by a simple and scalable hydrothermal reaction and a subsequent freeze-drying method. The freeze-dried WS2–graphene composite exhibits good cycling stability and outstanding high-rate capability of lithium storage. The reversible capacity remains 647 mA h g−1 after 80 cycles at a current density of 0.35 A g−1. Comparable capacities of 541 and 296 mA h g−1 can still be maintained when cycling at even higher current densities of 7 and 14 A g−1 (7 and 14 mA cm−2) respectively.

A systematic fuzzy rule based approach for fault classification in transmission lines

Abstract: The paper presents a new approach for fault classification in transmission line using a systematic fuzzy rule based approach. Fault classification is one of the important requirements in distance relaying for identifying the accurate phases involved in the fault process. The proposed technique starts with preprocessing the fault current signal using advanced time-frequency transform such as S-transform to compute various statistical features. After the required features are extracted, the Decision Tree (DT), a knowledge representation method, is used for initial classification. From the DT classification boundaries, the fuzzy membership functions (MFs) and corresponding fuzzy rule-base is developed for final classification. Thus a systematic fuzzy rule base is developed for fault classification, reducing the redundancies and complexities involved compared to Heuristic fuzzy rule-based approach. Also a qualitative comparison is made between S-transform and Wavelet transform, where S-transform based DT-fuzzy provides highly improved results compared to the later during simulation as well as experimental tests.

Wavelet singular entropy-based symmetrical fault-detection and out-of-step protection during power swing

Abstract: Fault-detection and out-of-step protection functions are two important requirements in distance relays while dealing with power-swing conditions. In the proposed research, the first part focuses on developing wavelet entropy-based out-of-step blocking function during stable power swing and tripping function during unstable power swing. The process starts at retrieving the current signal samples during power swing and process it through wavelet transform to derive singular values, used to find out Shannon entropy, called wavelet singular entropy (WSE). Further, the power swing indicators are computed to distinguish stable power swing from unstable ones. The second part computes WSE-based indicator to distinguish faults from power swing. The WSE blocks the relay during power swing and issue the tripping signal during fault conditions based on a set threshold. The proposed technique is extensively tested for different stable and unstable power swing conditions providing improved response time for fault detection during power swing and distinguishing stable power swings from unstable ones.

On the Field Enhancement and Performance of an Ultra-Stable SPR Biosensor Based on Graphene

Abstract: The effect of graphene on the electric field enhancement and performance of SPR-based sensor has been proposed and compared with Ag-Au bimetallic configuration. We found that a monolayer of graphene on Ag not only addresses the oxidation problem of Ag, but it also shows field enhancement as compared with the widely reported Ag-Au bimetallic combination. Detailed calculations and simulations show that the proposed graphene-based sensor has higher sensitivity and narrower full-width at half-maximum than bimetallic. In addition, the better biomolecules adhesion due to graphene because of π-stacking interaction may open a new window for ultra-stable high performance biosensors for real time bimolecular interactions.

Modelling the challenges of green supply chain management practices in Indian mining industries

Abstract: Purpose – Green supply chain management (GSCM) has received growing attention in the last few years. Almost all industries including mining industries are hit by green fever. In this context, this study aims to identify various challenges faced by the Indian mining industries during GSCM implementation and practices and to represent in a hierarchical manner. Design/methodology/approach – Various barriers and contextual relationships among them have been identified. Classification of barriers has been carried out based upon dependence and driving power (DP) with the help of MICMAC analysis. In addition to this, a structural model of the barriers to GSCM practices in Indian mining industries has been put forward using interpretive structural modelling (ISM) technique. Findings – In the present work, 11 numbers of relevant barriers have been identified from literature and subsequent discussions with experts from academia and industry. Lack of environmental awareness, poor legislation and inadequate pressure ...

A Data-Mining Model for Protection of FACTS-Based Transmission Line

Abstract: This paper presents a data-mining model for fault-zone identification of a flexible ac transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides effective decision on fault-zone identification. Half-cycle postfault current and voltage samples from the fault inception are used as an input vector against target output “1” for the fault after TCSC/UPFC and “ -1” for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate reliable identification of the fault zone in FACTS-based transmission lines.

Evaluation of the use of an alkali modified fly ash as a potential adsorbent for the removal of metals from acid mine drainage

Abstract: The coal fly ash (FA), mainly containing high unburnt carbon was modified by alkali hydrothermal treatment. The modified fly ash (MFA) contains lower amounts of Si and Al and has a higher surface area and pH than the untreated fly ash (FA). The objective of this study is to investigate the potential of MFA as a low cost adsorbent material for the removal of Al, Fe, Ni, Pb, Zn and Mn from acid mine drainage (AMD). The effect of dose, contact time and competing cations on the adsorption of metals was investigated. The results showed that the sorption process onto MFA was initially rapid, but slowed down thereafter. The optimum time for metal uptake was 180 min while the optimum dose of MFA for metal removal was 120 g/L. The adsorption data best fit to the Freundlich isotherm model, which demonstrates that the adsorption process is controlled by the heterogeneous nature of the adsorbent. Adsorption kinetics of Al, Fe, Ni, Pb, and Zn onto MFA follow a pseudo second-order reaction, which implies that chemisorption is the adsorption rate-limiting step for them, while for Mn it is intra-particle diffusion. Preliminary treatment of real mine drainage from Jaintia Hills coalfield indicates that MFA can be an effective and low-cost adsorbent for the treatment of AMD. The desorption data show that most of the metal ions were substantially desorbed in the acidic media, implying that the adsorbent can be regenerated and reused efficiently.

Highly Sensitive Plasmonic Temperature Sensor Based on Photonic Crystal Surface Plasmon Waveguide

Abstract: We propose a highly sensitive temperature sensor based on photonic crystal surface plasmon waveguides comprising different plasmonic active metals such as gold, silver, and aluminum, utilizing surface plasmon resonance phenomenon. We found that the resonance wavelength can be easily and substantially tuned over a broad spectral range by changing the temperature and also by judiciously choosing the different plasmonic metals. Employing coupled mode theory, we found that the proposed sensor can be used in harsh environment with sensitivity as high as ∼70 pm/K around telecommunication window.

Hydroxyapatite-Coated Magnesium-Based Biodegradable Alloy: Cold Spray Deposition and Simulated Body Fluid Studies

Abstract: A simple modified cold spray process in which the substrate of AZ51 alloys were preheated to 400 °C and sprayed with hydroxyapatite (HAP) using high pressure cold air nozzle spray was designed to get biocompatible coatings of the order of 20-30 μm thickness. The coatings had an average modulus of 9 GPa. The biodegradation behavior of HAP-coated samples was tested by studying with simulated body fluid (SBF). The coating was characterized by FESEM microanalysis. ICPOES analysis was carried out for the SBF solution to know the change in ion concentrations. Control samples showed no aluminum corrosion but heavy Mg corrosion. On the HAP-coated alloy samples, HAP coatings started dissolving after 1 day but showed signs of regeneration after 10 days of holding. All through the testing period while the HAP coating got eroded, the surface of the sample got deposited with different apatite-like compounds and the phase changed with course from DCPD to β-TCP and β-TCMP. The HAP-coated samples clearly improved the biodegradability of Mg alloy, attributed to the dissolution and re-precipitation of apatite showed by the coatings as compared to the control samples.

Artificial Neural Network Model in Prediction of Meteorological Parameters during Premonsoon Thunderstorms

Abstract: Forecasting thunderstorm is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent nonlinearity of their dynamics and physics. Accurate forecasting of severe thunderstorms is critical for a large range of users in the community. In this paper, experiments are conducted with artificial neural network model to predict severe thunderstorms that occurred over Kolkata during May 3, 11, and 15, 2009, using thunderstorm affected meteorological parameters. The capabilities of six learning algorithms, namely, Step, Momentum, Conjugate Gradient, Quick Propagation, Levenberg-Marquardt, and Delta-Bar-Delta, in predicting thunderstorms and the usefulness for the advanced prediction were studied and their performances were evaluated by a number of statistical measures. The results indicate that Levenberg-Marquardt algorithm well predicted thunderstorm affected surface parameters and 1, 3, and 24 h advanced prediction models are able to predict hourly temperature and relative humidity adequately with sudden fall and rise during thunderstorm hour. This demonstrates its distinct capability and advantages in identifying meteorological time series comprising nonlinear characteristics. The developed model can be useful in decision making for meteorologists and others who work with real-time thunderstorm forecast.

Magnetoelectric coupling in the Haldane spin-chain system Dy 2 BaNiO 5

Abstract: We report the results of various measurements, namely magnetization, complex dielectric permittivity, and electric polarization ($P$), on Dy${}_{2}$BaNiO${}_{5}$ as a function of temperature ($T$) and magnetic field ($H$), apart from heat capacity ($C$), with the primary motivation of exploring the existence of magnetoelectric (ME) coupling among Haldane spin-chain systems The $M$($T$) and $C$($T$) data establish long-range magnetic ordering at 58 K The most noteworthy observations are: (i) Distinct anomalies are observed in the dielectric constant (\ensuremath{\epsilon}\ensuremath{'}) vs $T$ and loss (tan\ensuremath{\delta}) vs $T$ at different temperatures (ie, 125, 30, 50, and 58 K); at low temperatures, three magnetic-field-induced transitions are observed in \ensuremath{\epsilon}\ensuremath{'} vs $H$ at 6, 40, and 60 kOe These transition temperatures and critical magnetic fields track those obtained from magnetization data, establishing the existence of strong magnetoelectric coupling in this compound (ii) Correspondingly, electric polarization could be observed as a function of $T$ and $H$ in the magnetically ordered state, thereby indicating magnetism-induced ferroelectricity in this compound; this result suggests that this compound is a possible multiferroic material among spin $=$1 (nickel-containing) compounds, with successive magnetic transitions and strong magnetoelectric coupling

Ultrasensitive Plasmonic Imaging Sensor Based on Graphene and Silicon

Abstract: We propose an ultrasensitive, accurate, and cost effective surface plasmon resonance sensor based on graphene-on-aluminum and silicon. An angular interrogation method has been theoretically used to study the performance of the sensor in terms of imaging sensitivity, which quantifies the rate of change of slopes of the reflectance curve close to resonance angle. Different optimized design parameters have been reported. It is found that the imaging sensitivity of an aluminum-based sensor is 750% greater than gold, the most widely used SPR active metal. However, graphene-on-aluminum not only prevents the aluminum oxidation but, a monolayer of graphene-on-aluminum exhibits ~400% larger imaging sensitivity compared to that of a conventional gold-film based SPR sensor.

Sustainable development practices in mining sector: a GSCM approach

Abstract: Public interest on environment and ecology has grown manifolds due to rapid climate changes, environmental health hazards and energy crisis. This has drawn the attention of mass media, societies and governments to intensify pressure on organisations for transforming their process into eco-friendly process. Subsequently, organisations have been looking for developing models, algorithms, technologies, information and communication system that can contribute best to their sustainable development (SD) policies by integrating their economical, social and environmental objectives. This paper aims at developing a sustainable development framework for Indian mining industries through GSCM approach. A hierarchical model of the drivers affecting the implementation of green supply chain management in Indian mining industries has been developed using an interpretive structural modelling (ISM) framework. The various drivers of green supply chain management (GSCM) are identified based on the review of GSCM literature a...

Optimal Integration of Disparate C37.118 PMUs in Wide-Area PSS With Electromagnetic Transients

Abstract: The present paper investigates the effective application of phasor measurement units (PMUs) with different technologies and filtering dynamics to the design of wide-area power system stabilizer (WAPSS). Two frequency-adaptive PMU algorithms shown to exceed the C37.118 class-M requirements based on FIR- and Kalman-bandpass filtering are selected for study. Their sharp dynamic differences are characterized using accurate fourth-order transfer functions derived from step responses using system identification techniques. While FIR-based PMUs have no overshoot in their phase and amplitude step responses, the adaptive Kalman filter allows for better out-of-band interference rejection at the cost of a phase step response with overshoot and a higher computational burden. These PMUs are implemented in Simulink and then embedded in electro-magnetic transients (EMT) simulations to experiment the realistic WAPSS behavior with the discrete-time devices in the loop. It is shown that WAPSSs with optimized settings can improve the damping performance of EMT models of a test system and a simplified Hydro-Quebec network including PMU filtering dynamics and transmission delays. However, WAPSSs based on EKF-PMUs yielded better performances, thanks to their shorter group delay compared with FIR-PMUs. PMU devices and algorithms meeting standard C37-118 can thus behave quite differently under stressed dynamics.