The demand for petroleum based fuel has grown in an extensive way because of the increasing industrialization and the growth in transportation sector. This growth has a direct effect on the economy and remains a monopoly in the fuel trade. Bio-fuels are available in a larger volume across the world due to the advantage that they can be directly blended with the petroleum fuels and the results obtained are better when compared to the standard values of neat diesel fuel. Such kind of bio-fuels can be extracted from lemon fruit and its availability is abundance across globe. This work aims in introducing a new bio-fuel called as Lemon Essential Oil (LEO) which can be obtained through steam distillation process of lemon rinds. A 20% LEO is blended with diesel (LEO20+ Diesel80) and it is fed as fuel to the engine. The various properties of LEO are examined and they are compared to mineral diesel. The experimental investigation revelaed that brake thermal efficiency of LEO20 is marginally higher than diesel at higher loads. Also significant reduction is observed for carbon monoxide, unburned hydrocarbon and smoke emissions. However, the oxides of nitrogen in LEO20 is comparatively higher than petroleum diesel at rated power output. Furthermore, the in-cylinder gas pressure of LEO20 is followed the similar trend with diesel fuel. In addition, higher heat release rate is also observed for LEO20 from the tested results. Hence, the present research work is showed that the 20% of Lemon Essential Oil could be partial substitute for conventional diesel engine in near future.

This study addressed the use of activated flux SiO2 for the gas tungsten arc (GTA) welding of super-austenitic stainless steel plates of 5 mm thickness. Trials were carried out to investigate the effect of flux and the welding current to determine the depth of penetration. Bead-on-plate trials were carried out on the AISI 904L with and without flux. It was inferred from the macrostructure studies that with a welding current of 180 A, complete penetration could be achieved using flux-assisted GTA welding. The optimal process parameters were validated by conducting the experimental investigations to ascertain the structure–property relationships of flux-assisted GTA weldment. Experimental results corroborated that the average tensile strength and impact toughness of SiO2 flux-assisted GTA weldments of AISI 904L were observed as 553 MPa and 49.3 J. It was inferred from the studies that defect-free welds of super-austenitic stainless steel could be obtained on employing flux-assisted GTA welding process.

This article addresses the weldability, microstructure and mechanical properties of the multi-pass pulsed current gas tungsten arc welding (PCGTAW) of Inconel X750. PCGTA welding was accomplished using two fillers, namely ERNiCrCoMo-1 and ERNiCrMo-3. Interfacial and weld microstructures were characterized using optical and scanning electron microscopy techniques. Migrated grain boundaries (MGBs) were dominating at the fusion zone of both the weldments. Post-weld heat treatment (PWHT) was carried out on the weldments at 705 degrees C for 22 h and air cooled to assess the microstructural changes and its impact on the mechanical properties. Tensile studies corroborated that all the tensile failures occurred at the fusion zone for both the as-welded and the PWHT samples. Fascinatingly, the weldments after subjected to PWHT resulted in improved tensile strength and the joint efficiency of ERNiCrCoMo-1 and ERNiCrMo-3 weldments improved to 82.2% and 72.5%. However, ERNiCrMo-3 weldments exhibited better impact toughness than ERNiCrCoMo-1 weldments. The structure-property relationships of the weldments are also discussed in the present investigation. (C) 2015 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

Image Enhancement is a preliminary step in basic image processing routines in general and is a crucial step in infrared (IR) images in specific. In most of the IR images, the target and the background fall into almost similar intensity levels. In order to increase the contrast of the target from its background, the preprocessing step is mandatory. In this paper, we proposed a fuzzy based approach for enhancing the infrared images so that the target can be detected in normal and cluttered images. The proposed method is robust and the experimental results show the efficacy of the proposed method.

Person identification plays a major role in any secured and safety system. Face is one of the major biometric explored by many researchers for human identification. The problem becomes more complex by means of any occlusion of objects, due to different illumination, expression and pose. We propose a novel pattern recognition approach for face detection in this paper. The approach presented is an amalgamation of artificial neural networks and fuzzy set theory. The proposed method runs in two phases and fuses the results for better performance and accuracy. The proposed method has been tested on BioID dataset and got 94% accuracy.