No abstract

In this work, the effective parameters in liquid polysulfide curing system were optimized by D-optimal design method. Five main components in the formulation, carbon black, vulcanizing agents (MnO 2 , Na 2 Cr 2 O 7 , and PbO 2 ), CaCO 3 , fumed silica, and chlorinated paraffin, were selected. Mechanical and chemical properties of the samples were investigated. The results showed that tensile strength, hardness, viscosity, and optimum cure time (t 90 ) presented a suitable coordination with reduced quadratic model. For elongation at break and swelling tests, reduced two-factor interaction (2FI), and for peel strength, a linear model showed the best correlation. To achieve the desirable properties for liquid polysulfide sealants used in fuel tanks, an optimized amount of the above components in the formulation were used. Finally, MnO 2 curing system, compared with Na 2 Cr 2 O 7 and PbO 2 , was selected as the best choice.

For industrial applications of engineering polymers such as polyurethane, polyamides and polyesters, the addition of suitable reinforcing inorganic fillers is a practical and convenient method to achieve the desirable mechanical and chemical properties. In this study, the mechanical, chemical and morphological properties of cast polyurethane samples containing barium sulphate, calcium carbonate, kaolin and quartz fillers were investigated. In the formulation of these samples, the ranges of inorganic filler were 0-40 phr. The results of mechanical property tests, such as tear resistance, tensile strength, elongation at break, Young's modulus, hardness and abrasion resistance, were evaluated. The chemical resistance of the samples was determined against xylene and methyl ethyl ketone. The chemical resistance of the filled cast polyurethane was determined by the solubility parameters of polymer/solvent. Finally, the experimental results and SEM images showed that samples containing 30 phr calcium carbonate produced the best results.

S:Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.