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Title: Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Abstract

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVEmore » of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.« less

Authors:
 [1];  [2];  [2];  [1]
  1. Georgia Institute of Technology, Atlanta, GA (United States)
  2. University of Michigan, Ann Arbor, MI (United States)
Publication Date:
Research Org.:
Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE); US Department of the Navy, Office of Naval Research (ONR); National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1976779
Alternate Identifier(s):
OSTI ID: 1834241
Grant/Contract Number:  
SC0008637; N00014-18-1-2784; ACI-1548562; -SC0008637
Resource Type:
Accepted Manuscript
Journal Name:
Acta Materialia
Additional Journal Information:
Journal Volume: 224; Journal Issue: C; Journal ID: ISSN 1359-6454
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 42 ENGINEERING; fatigue; crystal plasticity; microstructure-sensitive; computational modeling; finite element method; extreme value statistics

Citation Formats

Stopka, Krzysztof S., Yaghoobi, Mohammadreza, Allison, John E., and McDowell, David L. Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response. United States: N. p., 2021. Web. doi:10.1016/j.actamat.2021.117524.
Stopka, Krzysztof S., Yaghoobi, Mohammadreza, Allison, John E., & McDowell, David L. Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response. United States. https://doi.org/10.1016/j.actamat.2021.117524
Stopka, Krzysztof S., Yaghoobi, Mohammadreza, Allison, John E., and McDowell, David L. Sat . "Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response". United States. https://doi.org/10.1016/j.actamat.2021.117524. https://www.osti.gov/servlets/purl/1976779.
@article{osti_1976779,
title = {Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response},
author = {Stopka, Krzysztof S. and Yaghoobi, Mohammadreza and Allison, John E. and McDowell, David L.},
abstractNote = {Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.},
doi = {10.1016/j.actamat.2021.117524},
journal = {Acta Materialia},
number = C,
volume = 224,
place = {United States},
year = {Sat Nov 27 00:00:00 EST 2021},
month = {Sat Nov 27 00:00:00 EST 2021}
}

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