In this research, damping properties for composite materials were evaluated using logarithmic decrement method to study the effect of reinforcements on the damping ratio of the epoxy matrix. Three stages of composites were prepared in this research. The first stage included preparing binary blends of epoxy (EP) and different weight percentages of polysulfide rubber (PSR) (0%, 2.5%, 5%, 7.5% and 10%). It was found that the weight percentage 5% of polysulfide was the best percentage, which gives the best mechanical properties for the blend matrix. The advantage of this blend matrix is that; it mediates between the brittle properties of epoxy and the flexible properties of a blend matrix with the highest percentage of PSR. The second stage included reinforcing the best blend matrix of epoxy-polysulfide (the blend matrix with the best percentage of polysulfide resulted from the previous stage), by different volume percentages of short fibers (Carbon& Glass) separately and randomly. The volume percentages of fibers were (2.5%, 5%, 7.5%, and 10%). The third stage included reinforcing the blend composites with highest percentages of carbon and glass fiber, by different weight percentages of nano-particles (Red mud& Fly ash) separately. The weight percentages of particles were (0.5%, 1%, 1.5%, and 2%). The experimental results showed that blending polysulfide rubber with epoxy increased the damping ratio. As for reinforcement materials, they decreased the damping ratio, where glass fiber composites have significantly higher damping ratio than other composites.
A number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V col
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