Effect of viscosity and surface tension on breakup and coalescence of bicomponent sprays

This work deals with an experimental study of the breakup characteristics of liquids with different surface tension and viscosity from a hollow cone hydraulic injector nozzle induced by pressure-swirl. The experiments were conducted at Reynolds numbers Re-p=9500-23,000. The surface tension and viscosity of the surrogate fuels were altered from 72 to 30 mN/m and 1.1 to 1.6 mN s/m(2), respectively. High speed photography and Phase Doppler Particle Anemometry were utilized to study the atomization process. Velocity and drop size measurements of the spray using PDPA in both axial and radial directions indicate a dependency on surface tension. However, these effects are dominant only at low Reynolds numbers and are negligible at high Reynolds number. Downstream of the nozzle, coalescence of droplets due to collision was also found to be significant and the diameters were compared for different liquids. For viscous fluids up to 1.6 cP, the independent effects of viscosity and injection pressure are studied. In general, the spray cone angle increases with increase in pressure. At high pressures, an increase in viscosity leads to higher drop sizes following primary and secondary breakup compared to water. This study will extend our understanding of surrogate fuel film breakup and highlight the importance of long and short wavelength instabilities. (C) 2013 Elsevier Ltd. All rights reserved

Classification of road damage due to earthquakes

Earthquakes cause massive road damage which in turn causes adverse effects on the society. Previous studies have quantified the damage caused to residential and commercial buildings; however, not many studies have been conducted to quantify road damage caused by earthquakes. In this study, an attempt has been made to propose a new scale to classify and quantify the road damage due to earthquakes based on the data collected from major earthquakes in the past. The proposed classification for road damage due to earthquake is called as road damage scale (RDS). Earthquake details such as magnitude, distance of road damage from the epicenter, focal depth, and photographs of damaged roads have been collected from various sources with reported modified Mercalli intensity (MMI). The widely used MMI scale is found to be inadequate to clearly define the road damage. The proposed RDS is applied to various reported road damage and reclassified as per RDS. The correlation between RDS and earthquake parameters of magnitude, epicenter distance, hypocenter distance, and combination of magnitude with epicenter and hypocenter distance has been studied using available data. It is observed that the proposed RDS correlates well with the available earthquake data when compared with the MMI scale. Among several correlations, correlation between RDS and combination of magnitude and epicenter distance is appropriate. Summary of these correlations, their limitations, and the applicability of the proposed scale to forecast road damages and to carry out vulnerability analysis in urban areas is presented in the paper.

Entropy Constrained Exemplar-based Image Inpainting

Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques