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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

Adaptive Model Selection Procedure for Concurrent Multiscale Problems

Volume 5, Issue 5, 2007, pp. 369-386
DOI: 10.1615/IntJMultCompEng.v5.i5.20
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ABSTRACT

An adaptive method for the selection of models in a concurrent multiscale approach is presented. Different models from a hierarchy are chosen in different subdomains of the problem domain adaptively in an automated problem simulation. A concurrent atomistic to continuum (AtC) coupling method [27], based on a blend of the continuum stress and the atomistic force, is adopted for the problem formulation. Two error indicators are used for the hierarchy of models consisting of a linear elastic model, a nonlinear elastic model, and an embedded atom method (EAM) based atomistic model. A nonlinear indicator , which is based on the relative error in the energy between the nonlinear model and the linear model, is used to select or deselect the nonlinear model subdomain. An atomistic indicator is a stress-gradient-based criterion to predict dislocation nucleation, which was developed by Miller and Acharya [6]. A material-specific critical value associated with the dislocation nucleation criterion is used in selecting and deselecting the atomistic subdomain during an automated simulation. An adaptive strategy uses limit values of the two indicators to adaptively modify the subdomains of the three different models. Example results are illustrated to demonstrate the adaptive method.

CITED BY
  1. Aubertin Pascal, Réthoré Julien, de Borst René, Energy conservation of atomistic/continuum coupling, International Journal for Numerical Methods in Engineering, 78, 11, 2009. Crossref

  2. Luo Xiao-Juan, Stylianopoulos Triantafyllos, Barocas Victor H., Shephard Mark S., Multiscale computation for bioartificial soft tissues with complex geometries, Engineering with Computers, 25, 1, 2009. Crossref

  3. Fish Jacob, Li Aiqin, Yavari Fazel, Adaptive generalized mathematical homogenization framework for nanostructured materials, International Journal for Numerical Methods in Engineering, 83, 8-9, 2010. Crossref

  4. Fackeldey Konstantin, Krause Rolf, Multiscale coupling in function space-weak coupling between molecular dynamics and continuum mechanics, International Journal for Numerical Methods in Engineering, 79, 12, 2009. Crossref

  5. Delalondre Fabien, Smith Cameron, Shephard Mark S., Collaborative software infrastructure for adaptive multiple model simulation, Computer Methods in Applied Mechanics and Engineering, 199, 21-22, 2010. Crossref

  6. McDowell David L., A perspective on trends in multiscale plasticity, International Journal of Plasticity, 26, 9, 2010. Crossref

  7. Fan Rong, Yuan Zheng, Fish Jacob, Adaptive Two-Scale Nonlinear Homogenization, International Journal for Computational Methods in Engineering Science and Mechanics, 11, 1, 2010. Crossref

  8. An Introduction to Integrated Computational Materials Engineering (ICME), in Integrated Computational Materials Engineering (ICME) for Metals, 2012. Crossref

  9. Iacobellis Vincent, Behdinan Kamran, Multiscale coupling using a finite element framework at finite temperature, International Journal for Numerical Methods in Engineering, 92, 7, 2012. Crossref

  10. Panchal Jitesh H., Kalidindi Surya R., McDowell David L., Key computational modeling issues in Integrated Computational Materials Engineering, Computer-Aided Design, 45, 1, 2013. Crossref

  11. Jebahi Mohamed, Dau Frédéric, Charles Jean-Luc, Iordanoff Ivan, Multiscale Modeling of Complex Dynamic Problems: An Overview and Recent Developments, Archives of Computational Methods in Engineering, 23, 1, 2016. Crossref

  12. Ofir Yoav, Givoli Dan, DtN-based mixed-dimensional coupling using a Boundary Stress Recovery technique, Computer Methods in Applied Mechanics and Engineering, 287, 2015. Crossref

  13. DeCarlo Erin C., Mahadevan Sankaran, Variable Coupling and Time Step Selection among Multiple Disciplinary Models, 2018 AIAA Modeling and Simulation Technologies Conference, 2018. Crossref

  14. Horstemeyer M. F., Multiscale Modeling: A Review, in Practical Aspects of Computational Chemistry, 2009. Crossref

  15. To Albert C., Liu Wing Kam, Olson Gregory B., Belytschko Ted, Chen Wei, Shephard Mark S., Chung Yip-Wah, Ghanem Roger, Voorhees Peter W., Seidman David N., Wolverton Chris, Chen J. S., Moran Brian, Freeman Arthur J., Tian Rong, Luo Xiaojuan, Lautenschlager Eric, Challoner A. Dorian, Materials integrity in microsystems: a framework for a petascale predictive-science-based multiscale modeling and simulation system, Computational Mechanics, 42, 4, 2008. Crossref

  16. Budarapu Pattabhi Ramaiah, Zhuang Xiaoying, Rabczuk Timon, Bordas Stephane P.A., Multiscale modeling of material failure: Theory and computational methods, in Advances in Crystals and Elastic Metamaterials, Part 2, 52, 2019. Crossref

  17. Tadmor E. B., Legoll F., Kim W. K., Dupuy L. M., Miller R. E., Finite-Temperature Quasi-Continuum, Applied Mechanics Reviews, 65, 1, 2013. Crossref

  18. Elkhodary Khalil I., Steven Greene M., Tang Shan, Belytschko Ted, Liu Wing K., Archetype-blending continuum theory, Computer Methods in Applied Mechanics and Engineering, 254, 2013. Crossref

  19. Bibliography, in Discrete‐Continuum Coupling Method to Simulate Highly Dynamic Multi‐Scale Problems, 2015. Crossref

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