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International Journal for Uncertainty Quantification

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ISSN Druckformat: 2152-5080

ISSN Online: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

Indexed in

STATISTICAL STRENGTH OF HIERARCHICAL CARBON NANOTUBE COMPOSITES

Volumen 1, Ausgabe 4, 2011, pp. 279-295
DOI: 10.1615/Int.J.UncertaintyQuantification.2011002456
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ABSTRAKT

In modeling and simulation of material failure, a major challenge lies in the computation of stress redistributions during the stochastic propagation of localized failures. In this study, an nth-order generalized local load sharing (GLLS) model is introduced to account for the complexity of such local interactions in an efficient way.The rule is flexible, covering a wide range of load sharing mechanisms between the equal load sharing and local load sharing types. A Monte Carlo simulation model employing various orders of this GLLS rule is used to study the effect of such load redistributions on the failure of a micron-scale carbon nanotube (CNT) fiber. These CNT fibers exhibit a hierarchical structure. At the lowest length scale are single- or multi-walled CNTs with nanoscale diameters (e.g., 1–10 nm), which are aligned and clustered to form small bundles at the next higher length scale (15–60 nm in diameter). Thousands of these CNT bundles aggregate and align to create CNT fibers with micron-scale diameters. The results of this study indicate that the mean strength of the CNT fibers reduces by approximately two-thirds of an order of magnitude when up-scaling from an individual CNT to a CNT fiber. This dramatic strength reduction occurs at three different stages of the up-scaling process: (1) from individual CNTs of length lt to CNT bundles of the same length; (2) from a CNT bundle of length lt to a CNT bundle of length lb(lb = 10lt); and (3) from CNT bundles of length lb to CNT fibers of the same length. The specific strength reductions during these three stages are provided in the paper. The computed fiber strengths are in the same general range as corresponding experimental values reported in the literature. The ability of the GLLS model to efficiently account for different mechanisms of load sharing, in combination with the multi-stage up-scaling Monte Carlo simulation approach, is expected to benefit the design and optimization of robust structural composites built up from carbon nanotubes.

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