Title: Hierarchical top-down bottom-up calibration with consideration for uncertainty and inter-scale discrepancy of Peierls stress of bcc Fe

Abstract

A hierarchical multiscale model of plasticity in single crystal bcc Fe, framed at the mesoscale pertaining to a statistically representative set of dislocations for each slip system, relies on specification of a set of parameters which are informed using both bottom-up (BU) (atomistic) and top-down (TD) (experimental) information. We term this specification process a 'connection' between BU and TD pathways to inform the mesoscale model. The connection is considered in the presence of error, uncertainty, and discrepancy between the models. Furthermore, we expand upon a previously developed reconciled TD and BU calibration method to account for anticipated discrepancy between information from different length scales. The results of a previously formulated likelihood-based connection test of the multiscale model suggest a 'missing link' may be responsible for part of the inter-scale discrepancy. In this case, this link is assumed to be a relation between the unit-process (single dislocation line) of coordinated kink-pair nucleation on a screw dislocation segment and the many-body dislocation process which manifests in the onset of experimentally observed plastic deformation in a single crystal. A physics-informed discrepancy layer is formulated to improve the connection in the presence of additional persistent uncertainties. This physics-informed hypothesis testing is demonstrated as anmore » alternative to fully data-driven search methods, particularly applicable to datasets of limited size that are often encountered in such multiscale material modeling applications. Discrete dislocation dynamics simulations are used to investigate the effect of the Peierls stress on straight screw dislocations and in the operation of Frank–Read sources. Discussion concerns the critical role of uncertainty quantification in providing a basis for this form of incremental hypothesis testing.« less

Authors:

Tallman, Aaron E.  ^[1];

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• Search DOE PAGES for ORCID "0000-0002-0369-9721"

Swiler, Laura P. ^[2]; Wang, Yan  ^[3];

• Search DOE PAGES for author "Wang, Yan"
• Search DOE PAGES for ORCID "0000-0001-9324-4191"

McDowell, David L. ^[3]

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+ Show Author Affiliations

1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
3. Georgia Institute of Technology, Atlanta, GA (United States)

Publication Date:

Mon Jun 10 00:00:00 EDT 2019

Research Org.:

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:

USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:

1770105

Report Number(s):

LA-UR-19-21125
Journal ID: ISSN 0965-0393

Grant/Contract Number:  

89233218CNA000001; NA0003525

Resource Type:

Accepted Manuscript

Journal Name:

Modelling and Simulation in Materials Science and Engineering

Additional Journal Information:

Journal Volume: 27; Journal Issue: 6; Journal ID: ISSN 0965-0393

Publisher:

IOP Publishing

Country of Publication:

United States

Language:

English

Subject:

42 ENGINEERING; Multiscale modelling