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Suryan A.,Government Engineering College Idukki | Kim H.D.,Andong National University | Setoguchi T.,Saga University
Journal of Mechanical Science and Technology | Year: 2013

Environmental pollution and rapid depletion of fossil fuels had necessitated the search for alternative technologies and energy sources for transportation. Hydrogen fuel can be an environment friendly alternative. High pressure gas is a widely used storage mode for hydrogen fuel. Refueling of a vehicular hydrogen tank should be reasonably short to gain consumer acceptability. However, quick filling at high pressures can result in high temperatures. This should be avoided because of safety reasons. A numerical model can aid in optimizing the filling up process. The paper reports the numerical simulation of the refueling of high pressure hydrogen tanks using computational fluid dynamics method. Real gas equations are included to accurately simulate the process at the high temperature and pressure associated with the fast filling. Local temperature distribution in the tank is obtained at different durations of the fill. The numerical results obtained are validated with available experimental data. The results give an accurate visualization of the thermo fluid dynamic behavior of hydrogen gas during fast filling. © 2013 The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg. Source

Suryan A.,Government Engineering College Idukki | Kim H.D.,Andong National University | Setoguchi T.,Saga University
International Journal of Hydrogen Energy | Year: 2013

Compressed hydrogen gas is a popular mode of fuel storage for hydrogen powered vehicles. When hydrogen gas is filled at high pressure, the gas temperature increases. The maximum gas temperature should be within acceptable safety standards. Numerical studies can help optimize the filling process. There is a high level of turbulence in the flow as the high velocity inlet jet is penetrating the nearly stagnant gas in the tank. Selection of a suitable turbulence model is important for accurate simulation of flow and heat transfer during filling of hydrogen tanks. In the present work, a comparative study is performed to identify suitable turbulence model for compressed hydrogen tank filling problem. Numerical results obtained with different turbulence models are compared with available experimental data. Considering accuracy, convergence and the computational expenses, it is observed that the realizable k-ε model is the most suitable turbulence model for hydrogen tank filling problem. Copyright © 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. Source

Sivakumar R.,Government Engineering College Idukki
Proceedings - 2013 IEEE International Multi Conference on Automation, Computing, Control, Communication and Compressed Sensing, iMac4s 2013 | Year: 2013

The proposed system uses the principle of illuminating a sample with a laser beam and collecting the emitted photons through the sample using an array of photo detectors placed in fan beam geometry. Tissue model phantoms with different optical properties are used here for checking the effectiveness of the system. On the diffusely transmitted photons coming out of the sample, tomographic principles are applied to obtain the cross sectional details or tomogram of the tissue models and thereby checking for any abnormalities. The reconstruction of the tomogram was achieved by using convolution back projection algorithm and the whole system works on the basis of transillumination principle. © 2013 IEEE. Source

Chandran S.,Government Engineering College Idukki
2014 International Conference on Power Signals Control and Computations, EPSCICON 2014 | Year: 2014

This paper presents the MatlabbbSimulation of fuzzy logic based Sensorless sindirect vector control of induction motor with a rotor resistance adaptation scheme using Neural Learning Algorithm. Here the fuzzy controller offers superior transient performance when compared with the conventional control algorithms using PI controller. Rotor resistance of the motor changes significantly with temperature and frequency. This variation has a major influence on the field oriented control performance of an induction motor due to the deviation of slip frequency from the set value. This paper also uses neural learning algorithm for adaptation in a MRAS based rotor resistance estimator for making the robust against rotor resistance variation. © 2014 IEEE. Source

Remesh Babu K.R.,Government Engineering College Idukki | Saranya S.,Government Engineering College Idukki | Samuel P.,Cochin University of Science and Technology
Advances in Intelligent Systems and Computing | Year: 2016

Multi-tenant applications come into existence in clouds, which aims “better resource utilization” for application provider. Today most of the present application optimizations are based on Service Level Agreements which focuses on virtual machine (VM) based computing service, while other services such as storage and cache are often neglected. This paper mainly focuses on cache based approach for multi-tenant application on PaaS. Currently in multi-tenant cloud applications data are often evicted mistakenly by cache service, which is managed by existing algorithms such as LRU. It keeps the query information to reload the evicted data from storage which might be sensitive. Hence there is a possibility of data breach when these data are accessed improperly by other tenants. For faster access caching of the data is common in cloud based applications while the security is an important area that should not be neglected when these systems uses other third party systems/networks as caching servers. Also security of the tenant’s data/information is also a crucial component of the SLA between cloud service provider and tenant. So this paper proposes a DES based information security framework within Platform as a Service (PaaS) for better security and Quality of Service (QoS). © Springer International Publishing Switzerland 2016. Source

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