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Title: Predicting grid-size-dependent fracture strains of DP980 with a microstructure-based post-necking model

Abstract

Ductile fracture is a local phenomenon, and it is well established that fracture strain levels depend on both stress triaxiality and the resolution (grid size) of strain measurements. Two-dimensional plane strain post-necking models with different representative volume element (RVE) sizes are used to predict the size-dependent fracture strain of a commercial dual-phase steel, DP980. The models are generated from the actual microstructures, and the individual phase flow properties and literature-based individual phase damage parameters for the Johnson-Cook model are used for ferrite and martensite. A monotonic relationship is predicted: the smaller the model size, the higher the fracture strain. Thus, a general framework is developed to quantify the size-dependent fracture strains for multiphase materials. In addition to the RVE sizes, the influences of intrinsic microstructure features, i.e., the flow curve and fracture strains of the two constituent phases, on the predicted fracture strains also are examined. Application of the derived fracture strain versus RVE size relationship is demonstrated with large clearance trimming simulations with different element sizes.

Authors:
ORCiD logo; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1390413
Report Number(s):
PNNL-SA-123112
Journal ID: ISSN 0376-9429; VT0505000
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
International Journal of Fracture
Additional Journal Information:
Journal Volume: 207; Journal Issue: 2; Journal ID: ISSN 0376-9429
Publisher:
Springer
Country of Publication:
United States
Language:
English

Citation Formats

Cheng, G., Hu, X. H., Choi, K. S., and Sun, X. Predicting grid-size-dependent fracture strains of DP980 with a microstructure-based post-necking model. United States: N. p., 2017. Web. doi:10.1007/s10704-017-0229-8.
Cheng, G., Hu, X. H., Choi, K. S., & Sun, X. Predicting grid-size-dependent fracture strains of DP980 with a microstructure-based post-necking model. United States. doi:10.1007/s10704-017-0229-8.
Cheng, G., Hu, X. H., Choi, K. S., and Sun, X. Sat . "Predicting grid-size-dependent fracture strains of DP980 with a microstructure-based post-necking model". United States. doi:10.1007/s10704-017-0229-8.
@article{osti_1390413,
title = {Predicting grid-size-dependent fracture strains of DP980 with a microstructure-based post-necking model},
author = {Cheng, G. and Hu, X. H. and Choi, K. S. and Sun, X.},
abstractNote = {Ductile fracture is a local phenomenon, and it is well established that fracture strain levels depend on both stress triaxiality and the resolution (grid size) of strain measurements. Two-dimensional plane strain post-necking models with different representative volume element (RVE) sizes are used to predict the size-dependent fracture strain of a commercial dual-phase steel, DP980. The models are generated from the actual microstructures, and the individual phase flow properties and literature-based individual phase damage parameters for the Johnson-Cook model are used for ferrite and martensite. A monotonic relationship is predicted: the smaller the model size, the higher the fracture strain. Thus, a general framework is developed to quantify the size-dependent fracture strains for multiphase materials. In addition to the RVE sizes, the influences of intrinsic microstructure features, i.e., the flow curve and fracture strains of the two constituent phases, on the predicted fracture strains also are examined. Application of the derived fracture strain versus RVE size relationship is demonstrated with large clearance trimming simulations with different element sizes.},
doi = {10.1007/s10704-017-0229-8},
journal = {International Journal of Fracture},
issn = {0376-9429},
number = 2,
volume = 207,
place = {United States},
year = {2017},
month = {7}
}

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