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Chandigarh, India

PEC University of Technology, formerly known as Punjab Engineering College , is an engineering institute located in the city of Chandigarh, India and is one of the most prestigious institutes in North India. Wikipedia.


Mishra D.P.,Indian Institute of Technology Kanpur | Patyal A.,PEC University of Technology
Fuel | Year: 2012

The increasing demand for higher energy density fuels and the ever-increasing concern for their safety have propelled research in the field of gel propellants. For studying the fundamental parameters without the interference of neighbouring droplets, isolated droplet burning of organic ATF (aviation turbine fuel) gel propellants was chosen to investigate experimentally the effects of initial droplet diameter and chamber pressure on the burning under normal gravity conditions at room temperature. Under ambient pressure condition, an increase in the burning rate constant was observed with increase in initial droplet diameter. For a given range of diameters, the burning rate constant also continued to increase with pressure. Experiments were also carried out to study how these variations were affected by initial droplet diameter and chamber pressure changes, respectively. The intensity of microexplosions was observed to decrease with increase in chamber pressure. A balance between the heat loss by the droplet to the surroundings and the heat gain by the droplet has been put forward to explain the variations of burning rate constant with varying pressures as well as varying initial droplet diameters. © 2012 Elsevier Ltd. All rights reserved. Source


Singh S.,PEC University of Technology
Advanced Science Letters | Year: 2012

Barium titanate (BaTiO 3) nanoparticles with an average size of 28 nm were synthesized by modified sol- gel method and characterized by X-ray diffraction (XRD) and transmission electron microscopy equipped with energy-dispersive X-ray spectroscopy (EDX). XRD and selected area electron diffraction (SAED) investigations demonstrated that as-prepared BaTiO 3 nanoparticles have tetragonal perovskite crystal structure. Dielectric measurement results indicate a diffuse ferroelectric cubic to tetragonal phase transition and also shift to lower temperature side. This lowering and diffuseness in phase transition may be because of the particle size effect. Polarization investigation shows leaky ferroelectric loops in BaTiO 3 nanoparticles which may be due to the defects such as grain boundaries and the pores. © 2012 American Scientific Publishers. All rights reserved. Source


Jangra K.K.,PEC University of Technology
International Journal of Advanced Manufacturing Technology | Year: 2014

This work presents the investigation on multi-pass cutting operation (single rough cut followed by multi trim cuts) in wire electrical discharge machining (WEDM) of WC-5.3 % Co composite. Trim cuts were performed using Taguchi’s design of experiment method to investigate the influence of rough cut history (RHis), discharge current (Ip), pulse-on time (Ton), wire offset (WO) and number of trim cuts (Ntrim) on two performance characteristics namely depth of material removed (DMR) and surface roughness (SR). Result shows that the surface finish improves significantly in trim cutting operation irrespective of the rough cutting operation, while depth of material removed is proportional to the number of trim cuts followed. Using analysis of variance (ANOVA) on experimental data, it is found that Ton, WO and Ntrim are most significant parameters affecting the DMR, while Ip, Ton and WO are most significant for SR in trim cutting operation. Impact of RHis was negligible on final surface roughness, but it can influence the dimensional tolerance of the machined component. Using Taguchi method, WEDM parameters were optimized for DMR and SR, individually. Using nominal value of DMR from trim cutting operation, wire offset value has been predicted for rough cutting operation which helps to achieve the final dimensional precision. Using the same strategy, problem of selection of accurate wire offset and discharge parameters for rough and trims cutting operations can be solved easily for WEDM of new and exotic materials. © 2014, Springer-Verlag London. Source


Mali H.S.,Gautam Buddha University | Manna A.,PEC University of Technology
International Journal of Advanced Manufacturing Technology | Year: 2012

Abrasive flow machining (AFM) is a multivariable finishing process which finds its use in difficult to finish surfaces on difficult to finish materials. Near accurate prediction of generated surface by this process could be very useful for the practicing engineers. Conventionally, regression models are used for such prediction. This paper presents the use of artificial neural networks (ANN) for modeling and simulation of response characteristics during AFM process in finishing of Al/SiCp metal matrix composites (MMCs) components. A generalized back-propagation neural network with five inputs, four outputs, and one hidden layer is designed. Based upon the experimental data of the effects of AFM process parameters, e.g., abrasive mesh size, number of finishing cycles, extrusion pressure, percentage of abrasive concentration, and media viscosity grade, on performance characteristics, e.g., arithmetic mean value of surface roughness (Ra, micrometers), maximum peak-valley surface roughness height (Rt, micrometers), improvement in Ra (i.e., ΔRa), and improvement in Rt (i.e., ΔR t), the networks are trained for finishing of Al/SiCp-MMC cylindrical components. ANN models are compared with multivariable regression analysis models, and their prediction accuracy is experimentally validated. © 2012 Springer-Verlag London Limited. Source


Kalra P.,PEC University of Technology | Prakash N.R.,PEC University of Technology
Robotics and Computer-Integrated Manufacturing | Year: 2011

Exploring a virtual model under simulated environments is the best way to learn about a real system. This is particularly true in robotics where it is quite expensive to provide the system to each individual. The interdisciplinary area of robotics is being studied commonly in various fields like electrical, computer, mechanical engineering, nanotechnology, etc. A virtual robot system can help one fully understand the controls and working of a robot. The system may also be helpful to design the path and plan the trajectory of a robot in an industrial environment or other robotics application. Virtual model of RV-M1 robot has been developed in the MATLAB environment. The virtual system performs forward kinematics and inverse kinematics in addition to providing a simulation of the robot teachbox. © 2011 Elsevier Ltd. All rights reserved. Source

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