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Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
International Journal for Multiscale Computational Engineering
Импакт фактор: 1.016 5-летний Импакт фактор: 1.194 SJR: 0.452 SNIP: 0.68 CiteScore™: 1.18

ISSN Печать: 1543-1649
ISSN Онлайн: 1940-4352

Выпуски:
Том 17, 2019 Том 16, 2018 Том 15, 2017 Том 14, 2016 Том 13, 2015 Том 12, 2014 Том 11, 2013 Том 10, 2012 Том 9, 2011 Том 8, 2010 Том 7, 2009 Том 6, 2008 Том 5, 2007 Том 4, 2006 Том 3, 2005 Том 2, 2004 Том 1, 2003

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.v3.i1.50
pages 59-70

Numerical Assessment of Theoretical Error Estimates in Coarse-Grained Kinetic Monte Carlo Simulations: Application to Surface Diffusion

Abhijit Chatterjee
Department of Chemical Engineering Center for Catalytic Science and Technology (CCST), University of Delaware, Newark, DE 19716
Dionisios G. Vlachos
Department of Chemical Engineering Center for Catalytic Science and Technology (CCST), University of Delaware, Newark, DE 19716-3110
Markos A. Katsoulakis
Department of Mathematics and Statistics University of Massachusetts, Amherst, MA 01003

Краткое описание

A coarse-grained kinetic Monte Carlo (CG-KMC) method was recently introduced as a hierarchical multiscale modeling tool for extending the length scales reached by stochastic simulations. Coarse-graining causes errors due to loss of degrees of freedom. To quantify these errors, theoretical error estimates derived using information loss theory are first presented. Simulations are subsequently carried out in the canonical ensemble for various combinations of key parameters suggested by theoretical estimates. Numerically evaluated errors are compared to theoretical error estimates to assess whether the latter can qualitatively capture the loss of information during coarse-graining. Finally, a standing wave example is presented to illustrate how these error estimates can be used to control accuracy in CG-KMC by employing adaptive meshes.


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