Dataset: PRISMS-Fatigue Data - Effects of Boundary Conditions




Files
2,765
635.14 GB
Samples
0
in dataset
Workflows
0
documented
Views
1,343
total views
Downloads
325
total downloads
Published
Apr 15, 2021
5 years ago

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2765 files across 4 type(s)

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Published
Published: 5 years ago
Views
1,343
Downloads
325
Total Size
635.14 GB
Description

This data set contains the DREAM.3D generated microstructures, crystal plasticity finite element method (CPFEM) input files for PRISMS-Plasticity, PRISMS-Plasticity raw simulation results, and individual plots for the manuscript entitled "Effects of boundary conditions on microstructure-sensitive fatigue crystal plasticity analysis."

Please download the data using Globus or the Zipfile option so that four distinct folders are downloaded. These are entitled "paper_#2_section_3", "paper_#2_section_4", "paper_#2_section_5", and "simulation_files_only". There are two Python scripts available at the PRISMS-Fatigue GitHub page (https://github.com/prisms-center/Fatigue) in the "applications" folder that will generate the results plots of this manuscript. These two scripts are entitled "PRISMS_effects_of_BCs_compile_FIPs.py" and "PRISMS_effects_of_BCs_local_and_stress_strain.py". Users need to place these two scripts in the same directory as the four folders of this data set. Using a command prompt window, users will then navigate to the directory that contains these folders and two Python scripts. Users will then execute the command "python PRISMS_effects_of_BCs_compile_FIPs.py" or "python PRISMS_effects_of_BCs_local_and_stress_strain.py" to run the scripts. The scripts can also be executed using an interactive version of Python.

NOTE: If the entire data set is too large to download, users can download the folder entitled "simulation_files_only" that contains only the CPFEM input files to recreate the results of the manuscript.

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Citations
Dataset citation data unavailable.
Paper
Krzysztof S. Stopka, Mohammadreza Yaghoobi, John E. Allison, David L. McDowell
Integrating Materials and Manufacturing Innovation 2021 10.1007/s40192-021-00219-2
47
cited by
Funding
KSS and DLM are grateful for the support from the Office of Naval Research under grant number N00014-18-1-2784. MY and JEA are grateful for the support from the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award #DE-SC0008637 as part of the Center for PRedictive Integrated Structural Materials Science (PRISMS Center) at University of Michigan. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562, through the allocation TG-MSS160003. This research was supported in part through research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at the Georgia Institute of Technology, Atlanta, Georgia, USA.