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International Journal for Multiscale Computational Engineering

Published 6 issues per year

ISSN Print: 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

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MULTISCALE MODEL CALIBRATION BY INVERSE ANALYSIS FOR NONLINEAR SIMULATION OF MASONRY STRUCTURES UNDER EARTHQUAKE LOADING

Volume 18, Issue 2, 2020, pp. 241-263
DOI: 10.1615/IntJMultCompEng.2020031740
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ABSTRACT

The prediction of the structural response of masonry structures under extreme loading conditions, including earthquakes, requires the use of advanced material descriptions to represent the nonlinear behavior of masonry. In general, micro- and mesoscale approaches are very computationally demanding; thus at present they are used mainly for detailed analysis of small masonry components. Conversely macroscale models, where masonry is assumed as a homogeneous material, are more efficient and suitable for nonlinear analysis of realistic masonry structures. However, the calibration of the material parameters for such models, which is generally based on physical testing of entire masonry components, remains an open issue. In this paper, a multiscale approach is proposed, in which an accurate mesoscale model accounting for the specific masonry bond is utilized in virtual tests for the calibration of a more efficient macroscale representation assuming energy equivalence between the two scales. Since the calibration is performed offline at the beginning of the analysis, the method is computationally attractive compared to alternative homogenization techniques. The proposed methodology is applied to a case study considering the results obtained in previous experimental tests on masonry components subjected to cyclic loading, and on a masonry building under pseudo-dynamic conditions representing earthquake loading. The results confirm the potential of the proposed approach and highlight some critical issues, such as the importance of selecting appropriate virtual tests for model calibration, which can significantly influence accuracy and robustness.

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