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International Journal for Multiscale Computational Engineering

Erscheint 6 Ausgaben pro Jahr

ISSN Druckformat: 1543-1649

ISSN Online: 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

A Stochastic Nonlocal Model for Materials with Multiscale Behavior

Volumen 4, Ausgabe 4, 2006, pp. 501-520
DOI: 10.1615/IntJMultCompEng.v4.i4.70
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ABSTRAKT

Integral-type nonlocal mechanics is employed to model the macroscale behavior of multiscale materials, with the associated nonlocal kernel representing the interactions between mesoscale features. The nonlocal model is enhanced by explicitly considering the spatial variability of subscale features as stochastic contributions resulting in a stochastic characterization of the kernel. By appropriately representing the boundary conditions, the nonlocal boundary value problem (BVP) of the macroscale behavior is transformed into a system of equations consisting of a classical BVP together with two Fredholm integral equations. The associated integration kernels can be calibrated using either experimental measurements or micromechanical analysis. An efficient and computationally expedient representation of a resulting stochastic kernel is achieved through its polynomial chaos decomposition. The coefficients in this decomposition are evaluated from statistical samples of the disturbance field associated with a random distribution of microcracks. The new model is shown to be capable of predicting nonlocal features, such as the size effect and boundary effect, of the behavior of materials with random microstructures.

REFERENZIERT VON
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