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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

Indexed in

Studies of Nanotube-Based Aluminum Composites Using the Bridging Domain Coupling Method

Volume 5, Issue 6, 2007, pp. 447-459
DOI: 10.1615/IntJMultCompEng.v5.i6.20
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ABSTRACT

In this article, after performing verification of the bridging domain coupling method in a three-dimensional application, we employ this coupling method to study Young's moduli and failure strengths of nanotube-based aluminum composites. In the multiscale model of nanocomposites, the nanotubes and their surrounding areas, i.e., the interaction zones, are modeled via molecular dynamics, while the other regions are modeled via the finite element method. Three types of nanotubes are considered as inclusions: single-walled carbon nanotubes (SWNTs), multiwalled carbon nanotubes (MWNTs), and SWNT bundles. Although all types of nanotube inclusions can reinforce nanocomposites, MWNTs play the most significant role compared to the other two inclusions. In addition, SWNT bundles are better inclusions than SWNTs for reinforcing nanocomposites.

CITED BY
  1. Xiao Shaoping, Ni Jun, Yang Weixuan, Nelsen Cory, Modeling and Simulation of Carbon Nanotube Based Composites and Devices, in Handbook of Micromechanics and Nanomechanics, 2013. Crossref

  2. Silvestre Nuno, Faria Bruno, Canongia Lopes José N., Compressive behavior of CNT-reinforced aluminum composites using molecular dynamics, Composites Science and Technology, 90, 2014. Crossref

  3. Sadeghirad Alireza, Su Ninghai, Liu Feng, Mechanical modeling of graphene using the three-layer-mesh bridging domain method, Computer Methods in Applied Mechanics and Engineering, 294, 2015. Crossref

  4. Breugnot A., Lambert S., Villard P., Gotteland P., A Discrete/continuous Coupled Approach for Modeling Impacts on Cellular Geostructures, Rock Mechanics and Rock Engineering, 49, 5, 2016. Crossref

  5. Iacobellis Vincent, Radhi Ali, Behdinan Kamran, A bridging cell multiscale modeling of carbon nanotube-reinforced aluminum nanocomposites, Composite Structures, 202, 2018. Crossref

  6. Rong Y., He H.P., Zhang L., Li N., Zhu Y.C., Molecular dynamics studies on the strengthening mechanism of Al matrix composites reinforced by grapnene nanoplatelets, Computational Materials Science, 153, 2018. Crossref

  7. Reshetniak V. V., Aborkin A. V., Aluminum–Carbon Interaction at the Aluminum–Graphene and Aluminum–Graphite Interfaces, Journal of Experimental and Theoretical Physics, 130, 2, 2020. Crossref

  8. Patel Pramod Rakt, Sharma Sumit, Tiwari S. K., Molecular Dynamics Simulation of Single-Wall Carbon Nanotube Aluminum Composite, in Recent Advances in Computational Mechanics and Simulations, 2021. Crossref

  9. Huang Jun, Wu Yu, Huang Lixin, Evaluation of the mechanical properties of graphene-based nanocomposites incorporating a graded interphase based on isoparametric graded finite element model, Composite Interfaces, 28, 6, 2021. Crossref

  10. Xiao Shaoping, Deierling Phillip, Attarian Siamak, El Tuhami Ahmed, Machine learning in multiscale modeling of spatially tailored materials with microstructure uncertainties, Computers & Structures, 249, 2021. Crossref

  11. Iacobellis Vincent, Behdinan Kamran, Multiscale Methods for Lightweight Structure and Material Characterization, in Advanced Multifunctional Lightweight Aerostructures; Design, Development, and Implementation, 2021. Crossref

  12. Ding Hairong, Lu Yunxiang, Xie Yaoming, Liu Honglai, Schaefer Henry F., The Energy Difference between the Triply-Bridged and All-Terminal Structures of Co4(CO)12, Rh4(CO)12, and Ir4(CO)12: A Difficult Test for Conventional Density Functional Methods, Journal of Chemical Theory and Computation, 11, 3, 2015. Crossref

  13. El Tuhami Ahmed, Xiao Shaoping, Multiscale Modeling of Metal-Ceramic Spatially Tailored Materials via Gaussian Process Regression and Peridynamics, International Journal of Computational Methods, 19, 10, 2022. Crossref

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