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Prasad J.P.,Visvesvaraya Technological University | Mohan S.C.,BIET
1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016 | Year: 2016

Generally in practice there are Optical Fiber, Waveguides, Satellite Communication, Coaxial Cable and copper Wire which are utilized by the heterogeneous and homogeneous networks to offer wider range of data and voice communication to the end users. In future as the demands for bandwidth increases for the purpose of communication, this results into imbalance of the traffic load. To provide addition channel capacity the implementation of wireless sensor Networks (WSN's) in communication network can play vital role to meet network service provider as well as users demands for extra bandwidth. WSN's efficiency can be boosted up by proper novel design of secure data routing techniques with optimize use of network resources. WSN's nodes distributed across surrounding of globe and among sensor nodes coordination and connectivity we propose an innovative and optimized algorithm in WSN using Elliptical Curve based Spherical Grid Data Dissemination (SGDD) scheme. The performance analysis of proposed network is evaluated using Network Simulator-2(NS-2) and result shows the better tradeoff between network scalability versus network performance. © 2016 IEEE.

Prasad J.P.,BIET | Mohan S.C.,BIET
2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings | Year: 2016

The recent development in Wireless Sensor Networks (WSN) has proven that the WSN can be deployed in the Global Wireless Telecommunication with marginally high performance in terms of low power consumption, scalability, adaptability, reliability, security and data delivery. The implementation of WSN in wireless tele-communication using the proposed N-Tier Spherical Grid Routing (NSGR) WSN's architecture can offer data routing which provide extra bandwidth to improve global level channel capacity along with other existing channel. The proposed NSGR protocol can offer communication link which can be implemented for small scale area coverage to global area coverage using wireless sensor networks. The NSGR protocol is also suitable for a resource constrained environment with optimized performance and efficiency. The proposed method is simulated and tested using network simulator-2 to measure NSGR performance using metric terms such as packet delivery ratio, Average power consumption, Throughput, Control overheads, End-End delay. © 2016 IEEE.

Abdul Khadar A.,BITM Ballari | Khan J.A.,MIT Madanpalli | Nagaraj M.S.,BIET
Advances in Intelligent Systems and Computing | Year: 2017

The rapid growth of electricity consumption globally defines the need of electronic power conditioning, control of production and distribution of electricity over smart grid from a technical aspect. To reduce the global carbon emission, integrated framework deployments on the smart grid have gain lot of attention from research scientists. Therefore, the present scenario in the field of electricity and power distribution management incorporates the advanced information and communication technology. It can enhance efficiency, reliability and safety standards by conceptualizing distributed renewable energy utilization. This paper aims to represent an efficient and structured power distribution network (i.e. Grid) based framework to optimize the electricity cost of smart appliances. The proposed study conceptualizes the optimal framework by introducing a novel energy buffering methodology which integrates both micro grid controller and distributed energy storage to formulate the network. An analytical modeling has been introduced and tested considering storage capacity, financial cost, and electricity price to ensure the effectiveness of the proposed operational energy measurements using smart meters. The study also depicts ability of proposed method to significantly reduce the long-term term financial cost. © Springer International Publishing AG 2017.

Vishwakarma D.K.,B.I.E.T | Kumar N.,B.I.E.T | Padap A.K.,B.I.E.T
Materials Research Express | Year: 2017

In the present paper an effort is made to study the effect of aging parameters solution time, aging temperature and aging time on thermal conductivity and coefficient of thermal expansion (CTE) of Al 6082 alloy by using central composite rotatable design (CCRD) of response surface methodology (RSM). Three different parameters at five levels each are chosen for the experimentation. A second order polynomial mathematical model is developed for thermal conductivity and CTE to study the main and interactive effect of parameters on thermal conductivity and coefficient of thermal expansion. The aging parameters are also optimised for the optimum value of thermal properties. The results reveal that aging temperature is most significant parameter for change in thermal conductivity and CTE followed by aging time and solution time. Thermal conductivity and coefficient of thermal expansion has been improved by 17% and 20% respectively as compared as-received alloy. The improvement in thermal properties is attributed to the precipitation of Mg2Si particles in the alloy matrix. © 2017 IOP Publishing Ltd.

Recently, the modelling of whole process of software (SW) development is performed using extended waterfall and agile models. The further advancement of extended waterfall and agile models in the main phases like communication, planning, modelling, construction and deployment can improve the overall quality of the product. Accordingly, in this study, artificial intelligence (AI) activities are integrated into SW development processes. The important AI activities like intelligent agents, machine learning (ML), knowledge representation, statistical model, probabilistic methods, and fuzzy are integrated into the extended waterfall model. Again, AI activities like intelligent decision making, ML, Turing test, search and optimisation are integrated into the agile model. Two metrics such as, Usability Goals Achievement Metric and Index of Integration are evaluated in five independent SW projects. Once SW projects are developed using these models, feedback queries have been collected formally and the collected data are extensively analysed to identify the individual characteristics of products, identifying correlation behaviour of products with respect to model and metrics. © The Institution of Engineering and Technology 2016.

Panda G.,National Institute of Technology Meghalaya | Kumar P.,National Institute of Technology Rourkela | Puhan P.S.,BIET | Dash S.K.,SUIIT
International Journal of Electrical Power and Energy Systems | Year: 2013

Estimation of power system harmonics and their elimination is an interdisciplinary area of interest for many researchers. This paper presents Variable Step Size Least Mean Square (VSS-LMS) approach for harmonics estimation and Shunt Active Power Filter (SAPF) with two-level Hysteresis Current Control (HCC) technique for their elimination in a three-phase distribution system. In the estimation process, the weight is updated using VSS-LMS algorithm. Harmonics components are estimated from the updated weights. In order to mitigate harmonics produced by the nonlinear load connected in a three-phase distribution system, SAPF with two-level HCC is proposed. A three-phase insulated gate bipolar transistor (IGBT) based current controlled voltage source inverter (CC VSI) with a dc bus capacitor is used as an active power filter. The first step is to calculate SAPF reference currents from the sensed nonlinear load currents by applying the synchronous detection method and then the reference currents are fed to the proposed controller for generation of switching signals. The nonlinear load consists of one three-phase and one single-phase diode rectifier feeding R-L load, so that the effectiveness of the two-level HCC scheme to compensate for unbalanced nonlinear load can be tested. Various simulation results are presented to verify the good behavior of the SAPF with proposed two levels HCC. © 2013 Published by Elsevier Ltd.

Kumar N.,B.I.E.T | Gautam R.K.,Indian Institute of Technology BHU Varanasi | Mohan S.,Indian Institute of Technology BHU Varanasi
Materials and Design | Year: 2015

AA5052/ZrB2 composites with different volume percent (i.e. 0, 3, 6, 9 and 10vol.%) ZrB2 particles were developed by in-situ reaction of molten AA5052 alloy with two inorganic salts K2ZrF6 and KBF4 at a temperature of 860°C. The in-situ composites were characterized by DTA, XRD, SEM, TEM for reaction analysis and morphology. Their mechanical properties like hardness and tensile properties were evaluated using standard methods. Morphology studies show that grain size of Al-rich phase reduces due to the presence of ZrB2 particles. Microstructural studies also reveal the uniform distribution of second phase particles, clear interface, good bonding, dislocations and morphology of ZrB2 particles. It is found that ZrB2 particles are mostly in nano size with hexagonal or rectangular shape, however, few particles in micron size are also observed. Density and hardness of the composites increases with increase in the amount of reinforcement. Ultimate tensile strength and 0.2% yield strength (YS) also improved continuously with increase in the volume fraction of ZrB2 particles up to 9vol.% but beyond this composition strength reduced. It is important to note that with dispersion of ZrB2 particles in base alloy an improvement in ductility is observed which is contrary to many other composites. © 2015 Elsevier Ltd.

Gupta A.K.,Krishna Institute of Engineering and Technology | Singh Y.P.,BIET
Communications in Computer and Information Science | Year: 2011

This paper aims that analysing neural network method in pattern recognition. A neural network is a processing device, whose design was inspired by the design and functioning of human brain and their components. The proposed solutions focus on applying Feature Recognition Neural Network model for pattern recognition. The primary function of which is to retrieve in a pattern stored in memory, when an incomplete or noisy version of that pattern is presented. An associative memory is a storehouse of associated patterns that are encoded in some form. In auto-association, an input pattern is associated with itself and the states of input and output units coincide. When the storehouse is incited with a given distorted or partial pattern, the associated pattern pair stored in its perfect form is recalled. Pattern recognition techniques are associated a symbolic identity with the image of the pattern. This problem of replication of patterns by machines (computers) involves the machine printed patterns. There is no idle memory containing data and programmed, but each neuron is programmed and continuously active. © 2011 Springer-Verlag.

Khan S.Z.,BIET | Suman S.,Indian National Institute of Engineering | Pavani M.,Indian National Institute of Engineering | Das S.K.,Indian National Institute of Engineering
Geoscience Frontiers | Year: 2016

Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks (FN) using data available in the literature. The performance of FN was compared with support vector machine (SVM) and artificial neural network (ANN) based on statistical parameters like correlation coefficient (R), Nash - Sutcliff coefficient of efficiency (E), absolute average error (AAE), maximum average error (MAE) and root mean square error (RMSE). Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output. © 2015 China University of Geosciences (Beijing) and Peking University.

Rizvi S.A.H.,B.I.E.T. | Agarwal S.,B.I.E.T.
Procedia CIRP | Year: 2016

One of the most important non- conventional machining methods is Electrical Discharge Machining (EDM). The present study performs the EDM process with copper-tungsten electrode of diameter 2 mm to establish the influence of the EDM parameters on various aspects of the surface integrity of AISI 4340 steel. The residual stress induced by the EDM process is measured using the X-rays diffraction method. The experimental results reveal that the values of material removal rate (MRR), surface roughness (SR), and induced residual stress tend to increase at higher values of pulse current and pulse-on duration. However, for extended pulse-on duration, it is noted that the MRR, SR, and surface crack density all decrease. A smaller pulse current (i.e. 1A) tends to increase the surface crack density, while a prolonged pulse-on duration (i.e. 30 μs) widens the opening degree of the surface crack, thereby reducing the surface crack density. It is determined that the residual stress can be controlled effectively by specifying an appropriate pulse-on duration. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

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