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31.
Gregory N. Morscher Hee Mann Yun James A. DiCarlo 《Journal of the American Ceramic Society》2007,90(10):3185-3193
The tensile mechanical properties of ceramic matrix composites (CMC) in directions off the primary axes of the reinforcing fibers are important for the architectural design of CMC components that are subjected to multiaxial stress states. In this study, two-dimensional (2D)-woven melt-infiltrated (MI) SiC/SiC composite panels with balanced fiber content in the 0° and 90° directions were tensile loaded in-plane in the 0° direction and at 45° to this direction. In addition, a 2D triaxially braided MI SiC/SiC composite panel with a higher fiber content in the ±67° bias directions compared with the axial direction was tensile loaded perpendicular to the axial direction tows (i.e., 23° from the bias fibers). Stress–strain behavior, acoustic emission, and optical microscopy were used to quantify stress-dependent matrix cracking and ultimate strength in the panels. It was observed that both off-axis-loaded panels displayed higher composite onset stresses for through-thickness matrix cracking than the 2D-woven 0/90 panels loaded in the primary 0° direction. These improvements for off-axis cracking strength can in part be attributed to higher effective fiber fractions in the loading direction, which in turn reduces internal stresses on weak regions in the architecture, e.g., minicomposite tows oriented normal to the loading direction and/or critical flaws in the matrix for a given composite stress. Both off-axis-oriented panels also showed relatively good ultimate tensile strength when compared with other off-axis-oriented composites in the literature, both on an absolute strength basis as well as when normalized by the average fiber strength within the composites. Initial implications are discussed for constituent and architecture design to improve the directional cracking of SiC/SiC CMC components with MI matrices. 相似文献
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The study of collective user behaviours in social networking sites has become an increasing important topic in social media mining. Understanding such behaviours has its potential to extract actionable patterns that can be beneficial to develop effective marketing strategies, optimise user experiences and maximise website revenues. With the rapid development of micro-blogging, Twitter has become a richer source of intelligence that can be used to study collective user behaviour, due to its efficient and meaningful user-to-user interactions. However, the classical statistical methods have some drawbacks in bridging the gap between user-generated data and human analysts who mostly use linguistic terms to analyse data and model/summarise knowledge learned. To address this gap, this work proposes a new approach, which employs the mass assignment theory-based fuzzy association rules algorithm (MASS-FARM), for the first time, to extract useful interaction behaviour of Twitter users. The influential factors (including activity time, number of friends/followers and the number of tweets) are represented as fuzzy granules, and the associations amongst are studied by employing MASS-FARM. The collective user behaviours are analysed in the Reply category and the Non-Reply category, respectively. The applicability and usefulness of the proposed method are demonstrated via an empirical study on a collected Twitter data set. The derived results are also discussed and compared with existing works. 相似文献
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刘青宜 《自动化与仪器仪表》2014,(2):68-69
引入测量系统分析(MAS)技术,对实验仪器设备进行测评分析,判断仪器是否合格,保障了仪器设备的精确性,并以实验室四架天平为例,检验了此方法的可行性。 相似文献
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