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International Journal for Multiscale Computational Engineering

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ISSN Печать: 1543-1649

ISSN Онлайн: 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

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UNSTEADY ANALYSIS OF A HETEROGENEOUS MATERIAL USING THE MULTISCALE SEAMLESS-DOMAIN METHOD

Том 16, Выпуск 3, 2018, pp. 245-266
DOI: 10.1615/IntJMultCompEng.2018025509
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Краткое описание

We present an unsteady analysis using the Seamless-Domain Method (SDM), which is a multiscale modeling technique. The SDM has previously been applied to steady-state problems to demonstrate that complicated behavior in a heterogeneous structure can be represented with relatively few points. In this article, an unsteady analysis is carried out using SDM in the space–time domain. This domain is assumed to be composed of repeating units called "space– time unit cells," which are discretized by coarse-grained points (CPs). The first step is a local analysis of the space–time domain consisting of multiple unit cells, which derives the space–time interpolation functions. The next step is a global analysis to obtain the variable distribution in the entire global domain using the interpolation functions. This two-scale analysis with respect to both space and time is computationally efficient, resulting in highly accurate solutions at low computational cost. A method that improves the computational accuracy by searching the optimum set of "reference CPs" given in the interpolation is also presented. We consider an example problem of two-dimensional thermal diffusion in a heterogeneous structure, and compute the solution using unsteady SDM and a conventional finite-difference method. The solutions are compared in terms of computational accuracy and time.

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