Epoxy systems for low temperature applications
Epoxy-based formulated products are finding increased utility in a wide variety of structural and electrical applications that are required to operate in low temperature environments. Cryogenic technology is accelerating the growth in these fields. This versatile thermosetting polymer offers many attractive features such as high mechanical strength, outstanding dielectric characteristics, excellent adhesive properties, very good chemical resistance and excellent thermal endurance. Such features make them materials of choice for high and medium voltage electrical apparatus that operate in below zero Celsius environments. At lower operating temperatures, many factors come into play affecting overall performance. Among these factors are: speed and effectiveness of cure, fracture toughness characteristics, and thermal expansion properties.
Electrical aging tests on epoxy insulators in GIS
Due to the relatively small insulator dimensions in gas-insulated switchgear (GIS), the electrical stressing is high by comparison to that of insulators for conventional switchgear. Aging tests on a large number of full-sized insulators in several vessels in an outdoor test station have been carried out to determine the stress limits. The tests, with voltages of several hundred kilovolts, last for several years. The aim is to work out conditions (by extrapolation) for a trouble-free switchgear operating life of at least 50 years. The most important test objects are postinsulators weighing 2 kg each. It has been confirmed that partial discharges have a major effect on the failure probability. The life curve obtained from the test results of six batches of partial-discharge-free insulators is compared with the required reliability data. >
Mining Words in the Minds of Second Language Learners: Learner-Specific Word Difficulty
While there have been many studies on measuring the size of learners’ vocabulary or the vocabulary they should learn, there have been few studies on what kind of words learners actually know. Therefore, we investigated theoretically and practically important models for predicting second language learners’ vocabulary and propose another model for this vocabulary prediction task. With the current models, the same word difficulty measure is shared by all learners. This is unrealistic because some learners have special interests. A learner interested in music may know special music-related terms regardless of their difficulty. To solve this problem, our model can define a learner-specific word difficulty measure. Our model is also an extension of these current models in the sense that these models are special cases of our model. In a qualitative evaluation, we defined a measure for how learner-specific a word is. Interestingly, the word with the highest learner-specificity was “twitter”. Although “twitter” is a difficult English word, some low-ability learners presumably knew this word through the famous micro-blogging service. Our qualitative evaluation successfully extracted such interesting and suggestive examples. Our model achieved an accuracy competitive with the current models.