INFLUENCE OF ATMOSPHERIC HUMIDITY ON THE ABRASIVE WEAR OF METALS.

A pin-on-disc apparatus has been used to obtain continuous simultaneous measurements of the wear and friction (sliding force) behaviour of metals on bonded silicon carbide abrasive paper under conditions of controlled humidity. Iron, mild steel, and copper exhibit qualitatively similar wear behaviour; the wear rate decreases progressively with the number of passes over the same track. In contrast, the wear rate of titanium remains constant. Variation in atmospheric humidity has little effect on the wear rates of copper or titanium, although a slight effect was found in mild steel and iron. Refs.

INFLUENCE OF ATMOSPHERIC COMPOSITION ON THE ABRASIVE WEAR OF TITANIUM AND Ti-6Al-4V.

A pin-on-disc apparatus has been used to investigate the wear and friction (sliding force) behavior of metals on bonded silicon carbide and alumina papers under conditions of controlled atmospheric composition. The wear rates of both commercial purity titanium and the alloy Ti-6%Al-4%V tested in air were found to remain constant with time, in contrast with the behavior of other metals tested under similar conditions, which exhibited a progressive decrease in wear rate with increasing number of passes along the same track. It is proposed that the concentration of interstitial nitrogen and oxygen in the worn metal surface, which largely determines its mechanical properties, strongly influences both the ductility of the abraded material and the force of adhesion between the metal and the abrasive particles. Parallels are drawn between abrasive wear and machining to illustrate the importance of oxygen at the interface between workpiece and tool surfaces.

Atmospheric turbulence mitigation using complex wavelet-based fusion

Restoring a scene distorted by atmospheric turbulence is a challenging problem in video surveillance. The effect, caused by random, spatially varying, perturbations, makes a model-based solution difficult and in most cases, impractical. In this paper, we propose a novel method for mitigating the effects of atmospheric distortion on observed images, particularly airborne turbulence which can severely degrade a region of interest (ROI). In order to extract accurate detail about objects behind the distorting layer, a simple and efficient frame selection method is proposed to select informative ROIs only from good-quality frames. The ROIs in each frame are then registered to further reduce offsets and distortions. We solve the space-varying distortion problem using region-level fusion based on the dual tree complex wavelet transform. Finally, contrast enhancement is applied. We further propose a learning-based metric specifically for image quality assessment in the presence of atmospheric distortion. This is capable of estimating quality in both full-and no-reference scenarios. The proposed method is shown to significantly outperform existing methods, providing enhanced situational awareness in a range of surveillance scenarios. © 1992-2012 IEEE.