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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: 0.554 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.2016016841
pages 389-413

IDENTIFYING MATERIAL PARAMETERS FOR A MICRO-POLAR PLASTICITY MODEL VIA X-RAY MICRO-COMPUTED TOMOGRAPHIC (CT) IMAGES: LESSONS LEARNED FROM THE CURVE-FITTING EXERCISES

Kun Wang
Department of Civil Engineering and Engineering Mechanics, Columbia University, 614 SW Mudd, Mail Code: 4709, New York, New York 10027, USA
WaiChing Sun
Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, USA
Simon Salager
UJF-Grenoble 1, Grenoble-INP, CNRS UMR 5521, 3SR Laboratory, 38041 Grenoble, France
SeonHong Na
Department of Civil Engineering and Engineering Mechanics, Columbia University, 614 SW Mudd, Mail Code: 4709, New York, New York 10027, USA
Ghonwa Khaddour
UJF-Grenoble 1, Grenoble-INP, CNRS UMR 5521, 3SR Laboratory, 38041 Grenoble, France

Краткое описание

Unlike a conventional first-order continuum model, the material parameters of which can be identified via an inverse problem conducted at material point that exhibits homogeneous deformation, a higher-order continuum model requires information from the derivative of the deformation gradient. This study concerns an integrated experimental-numerical procedure designed to identify material parameters for higher-order continuum models. Using a combination of micro-CT images and macroscopic stress-strain curves as the database, we construct a new finite element inverse problem which identifies the optimal value of material parameters that matches both the macroscopic constitutive responses and the meso-scale micropolar kinematics. Our results indicate that the optimal characteristic length predicted by the constrained optimization procedure is highly sensitive to the types and weights of constraints used to define the objective function of the inverse problems. This sensitivity may in return affect the resultant failure modes (localized vs. diffuse), and the coupled stress responses. This result signals that using the mean grain diameter alone to calibrate the characteristic length may not be sufficient to yield reliable forward predictions.


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