Fathima S.T.,Reva Institute of Technology and Management Kattigenahalli |
Naduvinamani N.B.,Gulbarga University |
Marulappa S.H.,East West Institute of Technology
Tribology Online | Year: 2014
In the present investigation, a semi analytic and semi Numerical solution of the hydromagnetic squeeze film between anisotropic porous rectangular plates with lubricant additives has been studied. The effect of transverse magnetic field with the lubricants containing additives has been modelled as Stokes couple stress fluid. The more realistic Beavers-Joseph slip boundary conditions are used to derive the most general form of MHD-Reynolds equation, which accounts for the effects due to the lubricant additives and anisotropic nature of the porous material in the presence of transverse magnetic field. The current work aims to achieve better tribological designing for the design engineers to bring in enhanced load carrying capacity and reduced squeeze film time by the application of transverse magnetic field as compared to non-magnetic case and Newtonian case. © 2014 Japanese Society of Tribologists.
Ahmed M.R.,Reva Institute of Technology and Management Kattigenahalli |
Reddy D.S.B.,Reva Institute of Technology and Management Kattigenahalli |
Kumar K.P.,Reva Institute of Technology and Management Kattigenahalli |
Manasa H.,Reva Institute of Technology and Management Kattigenahalli |
Kaushalya P.B.,Reva Institute of Technology and Management Kattigenahalli
International Journal of Applied Engineering Research | Year: 2015
The field of Brain computer interaction (BCI) has got a great momentum in recent years.Brain is a 1.5kg wetware made up of around 100 billion neurons which communicate though ion exchange at the synapses. Electrical signals are generated due to the neuronal activities. Brain emit waves of frequencies ranging from 0.2Hz to 35Hz and beyond. Several efforts have been made to extract these signals. There are many methods such as fMRI, NIRS, EEG, MEG, etc of extracting brain signals.Electroencephalography(EEG) emerges as best suitable method. This paper aims to demonstrate the use of EEG for recording brain activity. Multisim is used to simulate proposed circuit. Obtained signals are processed using TMS320C54 and MATLAB. Hardware implementation is done using ARM cortex based robot, where the speed of robot is controlled using EEG signals. A decision algorithm is proposed which is based on predefined threshold in the scale of 0-100 on PROCESSING tool. To reach to a larger audience, scope and applications of BCI are discussed at the end. © Research India Publications.