Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Mechanical

This paper describes a network prototype of embedded wireless system with a thermocouple sensor to monitor the temperature variation in industrial operations through internet. The hardware and software selection and the sensor interfacing have been described. Using Raspberry Pi and internet service, the temperature at a remote location is continuously tracked and thus it provides a truthful and convenient mode of control. Thermocouple sensor senses the temperature variation and information is transmitted via internet to the control room. Internet based sensing and process monitoring is said to hold the key for the factories of future. © 2020 IJSTR.

World University root node

School of Mechanical Engineering

Chennai Campus

International Journal of Scientific and Technology Research

Remote temperature monitoring using thermocouple sensor via internet service

The boundary layer flow of a steady, two-dimensional, incompressible non-Newtonian nanofluid is studied in this analysis over a stretched sheet with an external uniform magnetic field. To analyse the flow of non-Newtonian fluid, the Eyring–Powell model is considered. In the energy equation, Newtonian heating impacts are regarded. The technique of similarity is used to convert non-linear partial differential equations into the ordinary differential equations. The reduced equations numerical solutions are achieved using the spectral relaxation method (SRM) with the MATLAB package. The spectral relationship method convergence is enhanced by combining SRM with SOR. It is observed that for non-Newtonian nanofluid, the fluid velocity is greater than that of classical nanofluid. The temperature and concentration profiles of nanoparticles increase significantly in order to increase the viscous dissipation and the Newtonian heating parameter. In addition, in the case of magnetic field strength, the surface shear stress is observed to be increased. © 2019, © 2019 Informa UK Limited, trading as Taylor &amp; Francis Group.

International Journal of Ambient Energy

Effects of Newtonian heating on the boundary layer flow of non-Newtonian magnetohydrodynamic nanofluid over a stretched plate using spectral relaxation method

The aim of this paper is to study the non-linear torsional vibrations of lengthy thin-walled simply supported beam of open section resting on Winkler foundation. The governing differential equation of motion is derived. An effort has been made to obtain and solve the governing differential equation of large amplitude torsional vibrations of doubly symmetric thin-walled beams of open section with simply supported boundary. Approximate solutions are obtained for simply supported beams using the well-known Galerkin's method. Plots specifying the effect of large amplitudes on nonlinear frequency of torsional vibrations for various non-dimensional beam constants are furnished. From the present study, we observe, that for lower values of Winkler stiffness parameter λ≤0.1, the non-linear frequency increases drastically as β increases. Also, it is noticed that as the value of Winkler stiffness parameter λ increases, the influence of β decreases. For higher values of λ≥30, the effect of β in the present range 0–0.1 on non-linear frequency seems to be negligible. © 2019 Elsevier Ltd

Applied Acoustics

Non-linear torsional vibration of lengthy thin-walled simply supported beam of open section resting on Winkler foundation

Abundant availability of fly ash due to the combustion of coal in thermal power plants presents a major threat to rising environmental pollution. To preserve the environment, fly ash was explored as the starting material for cordierite synthesis. Cordierite ceramics are widely used in the production of microelectronic components, catalyst substrate material for internal combustion engine. Hence, this research was pursued to fabricate the cordierite in a cost effective manner using fly ash containing the major constituent’s silica (SiO2) and alumina (Al2O3). Cordierite synthesis is carried out using raw materials fly ash, magnesia and dopants such as ZrO2, CeO2 and TiO2 at different composition (5–20 wt%). The properties and the microstructure of prepared samples were evaluated using X-ray diffraction (XRD), thermogravimetric and differential thermal analysis (TG/DTA), and scanning electron microscopy. Their mechanical and thermal properties such as the hardness, the fracture toughness, the flexural strength and the thermal expansion coefficient (CTE) were studied and compared with their morphology. It was found that the hardness, the fracture toughness, and the flexural strength were improved on the addition of the dopant in the cordierite matrix. The cordierite-ZrO2 ceramics (CZr20) exhibited a Vickers hardness value of 7.04 GPa, the fracture toughness of 3.47 MPa m½, and flexural strength of 196.72 MPa. The results confirm the cordierite synthesized with fly ash along with dopants is found suitable for use as catalytic substrate materials with improved mechanical properties. © 2018, Springer Nature B.V.

Department of Software and Systems Engineering

School of Information Technology and Engineering

Vellore Campus

Department of English

School of Social Sciences & Languages

Department of Automotive Engineering

Silicon

Fly Ash Constituent-Silica and Alumina Role in the Synthesis and Characterization of Cordierite Based Ceramics

Lubricants are used during the metal cutting process to remove the heat generated during the process and to reduce the Coefficient of friction (CoF). In this paper an attempt was made to synthesize an environment-friendly nano-lubricant using virgin coconut oil as base fluid by separately blending Copper (Cu) and Silver (Ag) nanoparticles in concentrations of 0.1%, 0.25%, 0.5% and 1% on the mass basis. The nanoparticles were blended in coconut oil by the means of ultrasonic shaking to obtain a uniform blend. The dependence of the Coefficient of friction of nanofluids and its performance on the concentration of the nanoparticles is well reported by researchers; therefore the optimal concentration of the nanoparticles was identified by Pin-on-Disk tribological testing. The following tests were conducted on the synthesised nano-lubricant such as Coefficient of friction (Pin-on-disk test), viscosity, flash &amp; fire point and real time turning operation to determine the cutting force, and operating temperature. From the wear test results, it was inferred that copper added coconut nanofluids exhibited lower Coefficient of friction as compared to silver added coconut nanofluids. Further, it was identified that the lowest Coefficient of friction in the range was exhibited by copper added coconut nanofluids of 0.25% concentration. When these nanolubricants were tested in a real time turning operation using lathe tool dynamometer, it was found that 0.25% concentration of copper added coconut nanolubricant exhibited minimum cutting force and operating temperature indicating minimum coefficient of friction. © 2019

VIT Unitversity

Fulltext

Engineering Science and Technology, an International Journal

Measurement of tribological properties of Cu and Ag blended coconut oil nanofluids for metal cutting

Humidity and high temperature both adversely affect the productivity of workers. At these atmospheric conditions even a safety helmet won't provide a comfortable situation for the wearer. This paper suggests a cooling system for these safety helmets using NanoGraphene (NG)/paraffin composite Phase Change Material (PCM) which absorbs and stores the heat thus achieving comfort cooling for the wearer. The heat absorbing capacity of a PCM depends on its thermal conductivity, which can be enhanced by adding different concentrations of nanoparticles. Such a technique is employed in this work, in which nano graphene is added to paraffin wax. This composite PCM is employed in an Industrial helmet for providing thermal comfort to the wearer. In principle, wearer's head transfers heat to the PCM mainly by conduction without the use of any kind of external power source. Moreover, the system maintains the wearer head temperature very close to the PCM temperature range of 28–33 °C thereby avoiding any kind of discomfort which would otherwise affect his/her alertness. It is found that the Nano-graphene/paraffin composite PCM integrated helmet provides a faster cooling compared to a normal PCM due to the changes in its thermal properties such as thermal conductivity and latent heat upon adding NG at various concentrations. Among the various tested concentration of nano graphene, the thermal conductivity of NG/paraffin composite PCM showed a maximum of 146% improved thermal conductivity and a maximum of 3% reduction in latent heat at 3% concentration of NG, when compared to those of the ordinary PCM. The designed helmet incorporated with composite PCM can provide thermal comfort to its wearer for more than four hours for all concentrations at an ambient temperature of 35 °C. © 2019 Elsevier Ltd

Chemistry

School of Advanced Sciences

Journal of Energy Storage

Enhancement of heat transfer in paraffin wax PCM using nano graphene composite for industrial helmets

Objective: This study seeks to determine compression (Cmax) and compression-related injury variables (velocity and viscous injury criterion: Vmax and VCmax) from chestband data in pure lateral and oblique far-side impact sled tests. Methods: The 3-point belt–restrained mid-sized male Test Device for Human Occupant Restraint (THOR) dummy was placed on a buck and subjected to side impacts with and without center-mounted airbags. The change in velocity was 8.3 m/s for all conditions. Two chestbands were routed around the outer circumference of the THOR at the levels of the third and sixth ribs. Maximum chest deflections were computed using strain gauge signals from the chestbands and their temporal contours. Three methods were used to determine deflection metrics. The first method paralleled methods used in previously published human cadaver studies; the second method used the actual anchor point location and actual alignment of the dummy’s internal sensors; and the third method used the anchor location of the internal sensor but determined the sensor’s locations on the contour confining to the aspect of the sensor. These 3 approaches are abbreviated as the SD, ID, and TD variables. The injury variables Cmax, Vmax, and VCmax were determined according to accepted procedures. Their peak magnitudes were extracted and an evaluation of their accuracy was made based on the SD method. Results: The average SD-based Cmax magnitudes for the upper and lower chest levels were 0.12 and 0.17 m/s, the Vmax magnitudes were 5.3 and 1.8 m/s, and the VCmax magnitudes were 0.24 and 0.15 m/s, respectively. Other data are given for all variables at the 2 levels of the thorax in the body of this paper. The ID-based peak variables were the lowest, and this observation was true regardless of the aspect, right or left side. In contrast, the SD method produced the greatest magnitudes of the variables. The VCmax variable had the greatest normalized difference among all 3 injury variables. Conclusions: Though the present study is limited in scope, the predetermined placement of the internal sensors in the THOR dummy underpredicted chest deflection-related injury variables, and the viscous criterion was the least reliable variable in these lateral and oblique far-side impact sled tests. © 2019, © 2019 Medical College of Wisconsin.

Traffic Injury Prevention

Compression-based injury variables from chestbands in far-side impact THOR sled tests

This paper describes the application of an artificial neural network, genetic algorithm and analytic network process-technique for order preference by similarity to ideal solution for the selection of the optimum fuel blend. A single-cylinder, constant-speed direct-injection diesel engine with a rated output of 4.4 kW was used for exploratory analysis at different load conditions. Ten objectives–brake thermal efficiency, maximum rate of pressure rise, NOx, CO2, CO, HC, smoke, exhaust gas temperature, ignition delay and combustion delay were considered. The proposed ANN model is integrated with GA and the hybrid multi-criteria decision-making technique of ANP-TOPSIS to evaluate the optimum blend. First the ANN model was developed to predict the performance, combustion and emission parameters of the engine. A multi-layer perception network was used for non-linear mapping between input and output parameters. The performance of the ANN model is determined and shows the efficiency of the model to predict the performance, emission and combustion parameters, with a determination coefficient of 0.9627. Second, GA was used to determine the optimum load and blend based on the predicted ANN output parameter. Third, an approach based on the TOPSIS method was used for finding the best blend from the observed optimum parameters of GA. © 2017, © 2017 Informa UK Limited, trading as Taylor &amp; Francis Group.

Department of Design and Automation

Biofuels

A genetic algorithm-based artificial neural network model with TOPSIS approach to optimize the engine performance

The deep drawing process is utilized for the manufacturing of sheet metal components in the automobile and aerospace industries. The present study briefs about the current developments in the deep drawing process at the elevated temperature. The comparative study is carried out on the utilization of different approaches and techniques for deep drawing of various sheet metals. The effects of geometrical and process parameters are considered for the elimination of defects like tearing, wrinkling, earing, and spring-back. The study also focuses on deep drawing of the sandwich composite materials at elevated temperatures. The different behaviors and formability are observed from the result for different materials at the elevated temperatures, which indicates the positivity in drawing of complex profile components as per the industry requirements. © 2019 CIRP

CIRP Journal of Manufacturing Science and Technology

Deep drawing process at the elevated temperature: A critical review and future research directions

In this modern world, most of the structural components are being replaced by composite materials. Sandwich panels have major advantages and applications in light weight systems like aircraft wings and helicopter components because of their low weight and high strength. The sandwich panel is fabricated by joining two face sheets to a core. Here, the face sheets are made of jute reinforced polymer matrix composite and the core is poly-propylene (PP) honeycomb structure. In this work, the flexural and fracture strengths of sandwich panels with different face sheet thickness, core thickness and orientations are compared numerically and experimentally. The ANOVA (Analysis of Variation) evaluation is used to find out the influence of the factors on flexural strength and stress intensity factor of the sandwich panel. The MINITAB software is used to carry out ANOVA analysis. The regression equations are obtained for maximum flexural stress and stress intensity factor. From the regression equations, the jute fiber layer is most significant factor than other two factors i.e. core thickness and jute fabric orientation. © 2019 IOP Publishing Ltd.