i-manager's Journal on Future Engineering and Technology (JFET)


Volume 12 Issue 3 February - April 2017

Research Paper

Subsurface Damage Assessment In Mortar Using Electrical Impedance Tomography

T. Ruan* , Poursaee**
* Research Scientist, Zhejiang Institute of Transportation, Hangzhou, China.
** Assistant Professor, Glenn Department of Civil Engineering, Clemson University, South Carolina, USA.
Ruan, T., and Poursaee (2017). Subsurface Damage Assessment In Mortar Using Electrical Impedance Tomography. i-manager’s Journal on Future Engineering and Technology, 12(3), 1-9. https://doi.org/10.26634/jfet.12.3.13429

Abstract

The objective of this study was to explore the feasibility of implementing Electrical Impedance Tomography (EIT) in assessing invisible subsurface damages in mortar specimens. Damages with different geometries and sizes were artificially created using a rotary saw with diamond blade, polypropylene plastic sheet and Poly-Vinyl Chloride (PVC) pipe on one side (bottom surface) of mortar specimens and the EIT tests were performed on the other side (top surface) of the specimens. Although, employing conductive materials in the mixture, using conductive paint on the surface, and saturating specimens can improve the precision and quality of the images they do not represent the actual field condition. Thus, in this study, no specific treatment was employed to collect the data for constructing the images. With the aid of numerical simulation and inverse calculation, two-dimensional images were reconstructed and recognized the artificial damages. The reconstructed images accurately identified the location of the damages and the sizes were qualitatively estimated. This study successfully shows the potentials of utilizing EIT technique in Non-Destructive Evaluation (NDE) of mortar structures.

Research Paper

A Comparative Study of Using Diode Laser, Ultrasound and Alternating Current in Wound Healing

Munqith* , Eman Gh. Khalil**, Mays I. Khudhair***
* Professor, Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Iraq.
** Lecturer, Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Iraq.
*** Assistant Lecturer, Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Iraq.
Dawood, M.S., Khalil, E.G., and Khudhair, M.I., (2017). A Comparative Study of Using Diode Laser, Ultrasound and Alternating Current in Wound Healing. i-manager’s Journal on Future Engineering and Technology, 12(3), 10-20. https://doi.org/10.26634/jfet.12.3.13430

Abstract

The laser, ultrasound, and electrical current energies are widely applied in the healing processes as well as in many other therapeutic applications in medicine. This study was established to evaluate the role of laser, ultrasound, and electric current on the wounds healing process and compare the results according to histological parameters of healing. Forty eight male mice of 20-25 gm in weight were randomly subdivided into four groups of twelfth animals each as follows: Laser group, ultrasound group, electrical current group, and control group. A one centimeter linear incision was made on the shaved backs of all mice. Group 1 had given continuous diode laser with a wavelength of 637 nm, 250 mW power. 2 Group 2 had treated with 1 MHz ultrasound frequency, 0.5 W/cm intensity. Group 3 had submitted to pulsed biphasic rectangular current of 30 Hz frequency, 1 mA current. Group 4 was kept as control. The treatments were applied at the same day, three sessions/week, for two weeks. The results were collected and compared histologically for certain days during the healing process. This study showed that, both electric current treatment and laser treatment have beneficial effects in the inflammatory and proliferation phases of wound healing, as compared with ultrasound treated group and control group.

Research Paper

Effect of Monoglycerides, Water and Soap Contamination on the Low Temperature Flow Properties of Pongamia Biodiesel

Amit Sarin* , Meetu Singh**, Neerja***, N.P. Singh****
* Associate Professor and Head, Department of Physical Sciences, IK Gujral Punjab Technical University, Jalandhar, Punjab, India.
** Research Scholar, IK Gujral Punjab Technical University, Jalandhar, Punjab, India
*** Assistant Professor, Department of Physics and Electronics, DAV College, Amritsar, Punjab, India.
**** Dean, IK Gujral Punjab Technical University, Jalandhar, Punjab, India.
Sarin, A., Singh, M., Neerja and Singh, N.P., (2017). Effect of Monoglycerides, Water and Soap Contamination on the Low Temperature Flow Properties of Pongamia Biodiesel. i-manager’s Journal on Future Engineering and Technology, 12(3), 21-27. https://doi.org/10.26634/jfet.12.3.13433

Abstract

Biodiesels are the promising fuels to secure the energy needs and environment. Transesterification is the process typically followed to synthesize biodiesels from the respective oil and this process may transcend minor contaminants during production. These contaminants, include monoglycerides (MG), soap traces, water traces, and other unsaponifiable matter, which adversely affects the low temperature flow properties which may lead to the gum formation and declines the performance of engine. The present research paper investigated the influence of monoglycerides, water and soap contamination with variable concentration on the low temperature flow properties, viz. Cloud Point (CP), Pour Point (PP), and Cold Filter Plugging Point (CFPP) of Pongamia biodiesel with standard testing methods. This study reveals the limit of contamination level upto which the response of low temperature flow properties need utmost action to eradicate the negative effect for better outcomes. The CP was increased from -1 oC and reaches 4 oC with 10000 ppm of MG with varying concentrations of soap and water (ppm). However, PP was increased to maximum of reaches 0 oC from -6 oC, for the different blends of contaminants. However, CFPP was increased from -2 oC to 2 oC with varying contamination. Had these points were increased by minor level, but study recommends the proper care to be taken during the pre and post transesterification.

Research Paper

Characterization of PMMA Based Nano-Composite Polymer Gel Electrolytes Containing Ammonium Thiocyanate for Advanced Electrochemical Devices

Dr. Rajiv Kumar*
*Assistant Professor, Department of Physics, Goswami Ganesh Dutt Sanatan Dharam (G.G.D.S.D.) College, Hariana, Punjab, India.
Kumar, R., (2017). Characterization of PMMA Based Nano-Composite Polymer Gel Electrolytes Containing Ammonium Thiocyanate for Advanced Electrochemical Devices. i-manager’s Journal on Future Engineering and Technology, 12(3), 28-34. https://doi.org/10.26634/jfet.12.3.13435

Abstract

Non-aqueous nano-composite polymer gel electrolytes using Ethylene Carbonate (EC), Ammonium Thiocyanate (NH4SCN), Polymethylmethacrylate (PMMA), and Nano-sized Fumed Silica (SiO2) have been synthesized and characterized by ionic conductivity, pH, viscosity, and Differential Scanning Calorimetry (DSC) studies. Liquid electrolytes were prepared by dissolving NH4SCN in ethylene carbonate, then gel electrolytes were obtained by adding PMMA (wt.% of liquid electrolytes) along with continuous stirring. Nano-composite polymer gel electrolytes were then prepared by adding fumed silica in polymer gel electrolytes. The increase in conductivity with the addition of salt has been explained to be due to an increase in free ions concentration by dissociation of salt which is supported by pH measurements. With the addition of PMMA, the conductivity of the electrolytes decreases, that has been explained due to an increase in viscosity of the electrolytes. The conductivity again shows an increase by small amount, when nano-sized fumed silica was added to gel electrolytes, which is due to facilitation of free ions between high conducting interfacial layers formed by fumed silica. The thermal stability of nano-composite polymer gel electrolytes has been checked by DSC studies. The conductivity of nano-composite polymer gel electrolytes does not show much change over 30-100o C temperature range and also remains constant with time, which is desirable for advanced electrochemical devices like proton batteries, fuel cells, supercapacitors, and other electrochromic devices.

Research Paper

Prediction of Critical Heat Flux In Pool Boiling Using Nanofluids

N. K. Chavda*
Associate Professor, Department of Mechanical Engineering, A.D. Patel Institute of Technology (ACVM Institution), Gujarat, India.
Chavda, N.K., (2017). Prediction of Critical Heat Flux in Pool Boiling Using Nanofluids. i-manager’s Journal on Future Engineering and Technology, 12(3), 35-43. https://doi.org/10.26634/jfet.12.3.13436

Abstract

Critical heat flux is one of the significant factors during pool boiling to observe in order to reduce the risk of damaging or melting of metal. Increasing value of critical heat flux, not only increases the functionality of various thermal systems, but also ensure their safety. Out of the various methods available, one of the recent methods to increase the critical heat flux is application of various nanofluids. The enhancement in critical heat flux in pool boiling using nanofluid depends on different parameters. Thus it requires extensive experimentation to propose the appropriate nanofluid for the same. In the present paper, critical heat flux have been experimentally evaluated using various water based nanofluids, such as Al2O3, CuO, and TiO2 having 0.1% to 1.0% volume concentration when two types of test heaters with different diameters are used. On the basis of the experimental results, fifty different ANN models using various ANN architectures, such as FFN, CFB, EBP, FFDD, GR, and RB have been developed and trained considering four input parameters, such as type of nanoparticle, concentration of nanoparticle, test heater material, and test heater diameter to predict the critical heat flux. The trained ANN models have been used to simulate the critical heat flux value and errors in prediction have been calculated in terms of MSE, NMSE, MARD, MRE, and AAE. The ANN model C8 (Elman back propagation having eight neurons of hidden layer), which yields global minimum value of error in prediction is proposed as the suitable ANN model for the case.