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Title: Learning local, quenched disorder in plasticity and other crackling noise phenomena

Abstract

When far from equilibrium, many-body systems display behavior that strongly depends on the initial conditions. A characteristic such example is the phenomenon of plasticity of crystalline and amorphous materials that strongly depends on the material history. In plasticity modeling, the history is captured by a quenched, local and disordered flow stress distribution. While it is this disorder that causes avalanches that are commonly observed during nanoscale plastic deformation, the functional form and scaling properties have remained elusive. In this paper, a generic formalism is developed for deriving local disorder distributions from field-response (e.g., stress/strain) timeseries in models of crackling noise. We demonstrate the efficiency of the method in the hysteretic random-field Ising model and also, models of elastic interface depinning that have been used to model crystalline and amorphous plasticity. We show that the capacity to resolve the quenched disorder distribution improves with the temporal resolution and number of samples.

Authors:
 [1]
  1. West Virginia Univ., Morgantown, WV (United States). Dept. of Mechanical & Aerospace Engineering, Dept. of Physics; Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Mechanical Engineering
Publication Date:
Research Org.:
Johns Hopkins Univ., Baltimore, MD (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1439912
Alternate Identifier(s):
OSTI ID: 1501822
Grant/Contract Number:  
SC0014109
Resource Type:
Published Article
Journal Name:
npj Computational Materials
Additional Journal Information:
Journal Volume: 4; Journal Issue: 1; Journal ID: ISSN 2057-3960
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Papanikolaou, Stefanos. Learning local, quenched disorder in plasticity and other crackling noise phenomena. United States: N. p., 2018. Web. doi:10.1038/s41524-018-0083-x.
Papanikolaou, Stefanos. Learning local, quenched disorder in plasticity and other crackling noise phenomena. United States. doi:10.1038/s41524-018-0083-x.
Papanikolaou, Stefanos. Thu . "Learning local, quenched disorder in plasticity and other crackling noise phenomena". United States. doi:10.1038/s41524-018-0083-x.
@article{osti_1439912,
title = {Learning local, quenched disorder in plasticity and other crackling noise phenomena},
author = {Papanikolaou, Stefanos},
abstractNote = {When far from equilibrium, many-body systems display behavior that strongly depends on the initial conditions. A characteristic such example is the phenomenon of plasticity of crystalline and amorphous materials that strongly depends on the material history. In plasticity modeling, the history is captured by a quenched, local and disordered flow stress distribution. While it is this disorder that causes avalanches that are commonly observed during nanoscale plastic deformation, the functional form and scaling properties have remained elusive. In this paper, a generic formalism is developed for deriving local disorder distributions from field-response (e.g., stress/strain) timeseries in models of crackling noise. We demonstrate the efficiency of the method in the hysteretic random-field Ising model and also, models of elastic interface depinning that have been used to model crystalline and amorphous plasticity. We show that the capacity to resolve the quenched disorder distribution improves with the temporal resolution and number of samples.},
doi = {10.1038/s41524-018-0083-x},
journal = {npj Computational Materials},
number = 1,
volume = 4,
place = {United States},
year = {2018},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1038/s41524-018-0083-x

Citation Metrics:
Cited by: 2 works
Citation information provided by
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