Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-28T21:54:43.822Z Has data issue: false hasContentIssue false
  • English
  • Français

Quantifying the Impact of Material-Model Error on Macroscale Quantities-of-Interest Using Multiscale a Posteriori Error-Estimation Techniques

Published online by Cambridge University Press:  20 July 2016

Judith A. Brown  and
Joseph E. Bishop
Judith A. Brown*
Affiliation:
Engineering Sciences Center, Sandia National Laboratories, Albuquerque, NM 87185, U.S.A.
Joseph E. Bishop
Affiliation:
Engineering Sciences Center, Sandia National Laboratories, Albuquerque, NM 87185, U.S.A.
*
*(Email: judbrow@sandia.gov)
Get access

Abstract

An a posteriori error-estimation framework is introduced to quantify and reduce modeling errors resulting from approximating complex mesoscale material behavior with a simpler macroscale model. Such errors may be prevalent when modeling welds and additively manufactured structures, where spatial variations and material textures may be present in the microstructure. We consider a case where a <100> fiber texture develops in the longitudinal scanning direction of a weld. Transversely isotropic elastic properties are obtained through homogenization of a microstructural model with this texture and are considered the reference weld properties within the error-estimation framework. Conversely, isotropic elastic properties are considered approximate weld properties since they contain no representation of texture. Errors introduced by using isotropic material properties to represent a weld are assessed through a quantified error bound in the elastic regime. An adaptive error reduction scheme is used to determine the optimal spatial variation of the isotropic weld properties to reduce the error bound.

Keywords

textureweldingelastic properties
Type
Articles
Information
MRS Advances , Volume 1 , Issue 40: Characterization and Modeling of Materials , 2016 , pp. 2789 - 2794
Copyright
Copyright © Materials Research Society 2016 This is a work of the U.S. Government and is not subject to copyright protection in the United States. 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Wei, H.L., Mazumder, J., DebRoy, T., Scientific Reports, 5, 16446 (2015).Google Scholar
Yadroitsev, I., Krakhmalev, P., Yadroitsava, I., Johansson, S., Smurov, I., J. Mater. Proc. Tech. 213, 606–613 (2013).Google Scholar
Unnikrishnan, R., Satish Idury, K.S.N., Ismail, T.P., Bhadauria, A., Shekhawat, S.K., Khatirkar, R.K., Sapate, S.G., Mater. Char. 93, 10–23 (2014).Google Scholar
Saeidi, K., Gao, X., Zhong, Y., Shen, Z.J., Mater. Sci. Eng. A 625, 221–229 (2015).Google Scholar
Bouche, G., Béchade, J.L., Mathon, M.H., Allais, L., Gourgues, A.F., Nazé, L., J. Nuclear Mat. 277, 91–98 (2000).Google Scholar
Oden, J.T., Prudhomme, S., J. Comp. Phys. 182, 496–515 (2002).Google Scholar
Zohdi, T., Oden, J., Rodi, G., Comput. Methods in Appl. Mech. Eng. 138(1-4), 273–298 (1996).Google Scholar
Oden, J., Prudhomme, S., Hammerand, D., Kuczma, M., Comput. Methods in Appl. Mech. Eng. 190(49-50), 6663–6684 (2001).CrossRefGoogle Scholar
Romkes, A., Oden, J., Vemaganti, K., Mechanics of Materials 38(8-10), 859–872 (2006).CrossRefGoogle Scholar
Oden, J., Vemaganti, K., J. Comp. Phys. 164(1), 22–47 (2000).Google Scholar
Vemaganti, K., Oden, J., Comput. Methods in Appl. Mech. Eng. 190(46-47), 6089–6124(2001).Google Scholar
Ledbetter, H., Physica Status Solidi (a) 85, 89–96 (1984).Google Scholar
Bishop, J., Emery, J., Field, R., Weinberger, C., Littlewood, D., Comput. Methods in Appl. Mech. Eng. 287, 262–289 (2015).Google Scholar
Sierra/Solid Mechanics 4.22 User’s Guide, Technical Report SAND2011-7597, Sandia National Laboratories, 2011.Google Scholar