Reduction of Permittivity in Epoxy Nanocomposites at Low Nano-filler Loadings

Experimental studies reveal a reduction in the values of permittivity for epoxy nanocomposites; at low filler loadings as compared to neat epoxy over a wide frequency range. This permittivity reduction is attributed to the interaction dynamics between nanoparticles: and epoxy chains at the interface region and interestingly, this interaction has also been found to influence the glass transition temperatures (T-g) of the examined nanocomposite systems. Accordingly, a dual nanolayer interface model for an epoxy based nanocomposite system is analyzed to explain the obtained permittivity characteristics.

Accelerated Multistress Aging of Outdoor Polymeric Insulators

Multistress aging of outdoor composite polymeric insulators continues to be a topic of interest for power transmission research community. Aging due to dry conditions alone at elevated temperatures and electric stress in the presence of UV radiation environment probably has not been explored. This paper deals with long-term accelerated multistress aging under the above conditions on full-scale 11 kV distribution class composite silicone rubber insulators. To evaluate the long-term synergistic effect of electric stress, temperature and UV radiation on insulators, they were subjected to accelerated aging in a specially designed multistress-aging chamber for 12000 hours. Chemical, physical and electrical changes due to degradation have been assessed using various techniques. It has been found that the content of low molecular weight molecules and hydrophobicity reduced significantly. Also, due to oxidation and aging there is appreciable increase in surface roughness and weight percentage of oxygen. Study is under progress and only intermediate results are presented in this paper.

Studies on the Tracking and Erosion Resistance of RTV Silicone Rubber Nanocomposite

One of the problems associated with outdoor polymeric insulators is tracking and erosion of the weathershed which can directly influence the reliability of the power system. Flame retardants are added to the base material to enhance its tracking and erosion resistance. Hydroxide fillers are regarded as the best flame retardants. This paper deals with studies related to nano - sized magnesium dihydroxide (MDH) and micron-sized Alumina Trihydrate (ATH) fillers as flame retardants in RTV silicone rubber. Tracking and erosion resistance studies were carried out on MDH and ATH silicone rubber composites using an inclined plane tracking and erosion (IPT) resistance tester. The MDH filled (5% by wt) composites performed much better than ATH composites in terms of eroded mass, depth of erosion, width and length of erosion. The eroded mass of MDH composite is 49.8 % that of ATH composite which can be attributed to high surface area and higher thermal stability of MDH nanofillers.

Electrical Discharge Resistant Characteristics of Epoxy Nanocomposites

This paper reports the electrical discharge resistant characteristics of epoxy nanocomposite systems with SiO2 and Al2O3 nano-fillers. A comparative study is performed between unfilled epoxy systems, nanoparticle filled epoxy systems and a bimodal system containing both micrometer and nanometer sized fillers of the same material. The samples are exposed to surface discharges and the levels of surface degradation are analyzed through SEM and surface roughness measurements. Significant variations were observed in the electrical discharge resistant characteristics between the different composite systems and it is seen that the introduction of nano-fillers to epoxy is advantageous in improving the electrical discharge resistance of epoxy.

Interaction of guar gum with hydrophobic solids

The interaction of guar gum with the hydrophobic solids namely talc, mica and graphite has been investigated through adsorption, electrokinetic and flotation experiments. The adsorption densities of guar gum onto the above hydrophobic minerals show that they are more or less independent of pH. The adsorption isotherms of guar gum onto talc, mica and graphite indicate that the adsorption densities increase with increase in guar gum concentration and all the isotherms follow the as L1 type according to Giles classification. The magnitude of the adsorption density of guar gum onto the above minerals may be arranged in the following sequence: talc > graphite > mica The effect of particle size on the adsorption density of guar gum onto these minerals has indicated that higher adsorption takes place in the coarser size fraction, consequent to an increase in the surface face-to-edge ratio. In the case of the talc and mica samples pretreated with EDTA and the leached graphite sample, a decrease in the adsorption density of guar gum is observed, due to a reduction in the metallic adsorption sites. The adsorption densities of guar gum increase with decrease in sample weight for all the three minerals. Electrokinetic measurements have indicated that the isoelectric points (iep) of these minerals lie between pH 2-3, Addition of guar gum decreases the negative electrophoretic mobility values in proportion to the guar gum concentration without any observable shift in the iep values, resembling the influence of an indifferent electrolyte. The flotation recovery is diminished in the presence of guar gum for all the three minerals, The magnitude of depression follows the same sequence as observed in the adsorption studies. The floatability of EDTA treated talc and mica samples as well as the leached graphite sample is enhanced, complementing the adsorption data, Possible mechanisms of interaction between the hydrophobic minerals and guar gum are discussed.

ON THE UTILITY OF CANONICAL CORRELATION ANALYSIS FOR DOMAIN ADAPTATION IN MULTI-VIEW HEADPOSE ESTIMATION

The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.