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International Journal for Multiscale Computational Engineering

Publicou 6 edições por ano

ISSN Imprimir: 1543-1649

ISSN On-line: 1940-4352

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: 1.4 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: 1.3 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: 2.2 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: 0.00034 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: 0.46 SJR: 0.333 SNIP: 0.606 CiteScore™:: 3.1 H-Index: 31

Indexed in

ON THE STRENGTH RELIABILITY OF STATISTICALLY HETEROGENEOUS MATERIALS WITH MICROSTRUCTURE AT DIVERSE SCALES

Volume 12, Edição 3, 2014, pp. 249-255
DOI: 10.1615/IntJMultCompEng.2014008133
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RESUMO

The paper examines the effects of microstructure realized at diverse scales on the overall strength reliability of the material. Reliability, or more precisely indirect reliability evaluated herein through the spatial fluctuations of strength, is shown to depend strongly on the scale-wise distribution of heterogeneity as well as on the size of a specimen or structure. In particular, for a polycrystalline material with pores, the overall (indirect) strength reliability increases as (a) the average grain size decreases relevant to the that of the pores, (b) the variance of the grain size decreases relevant to that of the pores, and (c) the size of a specimen or structure or material building block decreases. Under certain conditions, it is possible to reach near-zero or even zero variance, implying perfect reliability. The major conclusion is that scales interact with each other and that affects the overall fluctuations in material properties, thus providing renewed opportunities for tailoring the reliability of materials. The major conclusion is amenable to experimental investigation and verification for different heterogeneity scenarios.

CITADO POR
  1. Kale Sohan, Ostoja–Starzewski Martin, Representing stochastic damage evolution in disordered media as a jump Markov process using the fiber bundle model, International Journal of Damage Mechanics, 26, 1, 2017. Crossref

  2. Si Wujun, Yang Qingyu, Wu Xin, A distribution-based functional linear model for reliability analysis of advanced high-strength dual-phase steels by utilizing material microstructure images, IISE Transactions, 49, 9, 2017. Crossref

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