|
Temperature-Dependent Material Database: DH36
|
Data collected as part of the Lightweight Innovations for Tomorrow (LIFT) Institute’s program entitled, Robust Distortion Control Methods and Implementation for Construction of Lightweight Metallic Structures, which was lead by Huntington Ingalls Industries - Ingalls Shipbuilding (HII-Ingalls) from 2016-2018. |
Charles R. Fisher, Daniel H. Bechetti, Jennifer K. Semple, Wei Zhang |
ICME
CWM
DH36
LIFT
Steel
Material Database
Welding
SYSWELD
Shipbuilding
|
5 years ago |
1 year ago |
2023-10-03 20:01:51 |
|
PRISMS-Fatigue Data - Fatigue resistance of aluminum alloy 7075-T6
|
This dataset contains four folders for each of the four applications described in the associated PRISMS-Fatigue manuscript. These include modeling the effects of crystallographic texture, grain morphology, free surface, and multiaxial states of strain on the fatigue resistance of aluminum alloy 7075-T6. Each of the folders contain the pre-processed microstructure data necessary to perform PRISMS-Plasticity crystal plasticity finite element method (CPFEM) simulations and the results of each of those simulations. All of the publication results can be entirely reproduced.
Please download the data using Globus so that four distinct folders are available.
Please see the PRISMS-Fatigue GitHub page: https://github.com/prisms-center/Fatigue.
UPDATES:
April 3, 2021: Files entitled "element_band_sets_#.p" were updated to work with changes to the Python scripts available on the GitHub. A Python error of "too many values to unpack" would occur when using the "volume_average_FIPs.py" script because of a change to the "generate_microstructures.py" script. This is now fixed. Also, some additional files are now included. |
Mohammadreza Yaghoobi, Krzysztof S. Stopka, Aaditya Lakshmanan, Veera Sundararaghavan, John E. Allison, David L. McDowell |
ICME
fatigue
high cycle fatigue
crystal plasticity
aluminum
PRISMS
microstructure-sensitive
finite element method
fatigue indicator parameters
multiaxial fatigue
fatigue modeling
extreme value statistics
Al7075-T6
|
4 years ago |
3 years ago |
2021-12-04 21:11:06 |
|
PRISMS-Fatigue Data - Effects of Boundary Conditions
|
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. |
Krzysztof S. Stopka, Mohammadreza Yaghoobi, John E. Allison, David L. McDowell |
ICME
crystal plasticity
PRISMS
microstructure-sensitive
finite element method
fatigue indicator parameters
fatigue modeling
extreme value statistics
Fatigue
Al 7075-T6
boundary conditions
|
4 years ago |
4 years ago |
2021-04-16 14:43:42 |
|
Temperature-Dependent Material Database: HSLA-65
|
Data collected as part of the Lightweight Innovations for Tomorrow (LIFT) Institute’s program entitled, Robust Distortion Control Methods and Implementation for Construction of Lightweight Metallic Structures, which was lead by Huntington Ingalls Industries - Ingalls Shipbuilding (HII-Ingalls) from 2016-2018. |
Charles R. Fisher, Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang |
ICME
CWM
LIFT
Steel
Material Database
Welding
SYSWELD
Shipbuilding
HSLA-65
|
4 years ago |
1 year ago |
2023-10-03 20:04:18 |
|
PRISMS-Fatigue Data - FIP Convergence
|
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 "Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response."
Please download the data using Globus or the Zipfile option so that four distinct folders are downloaded. These are entitled "Section_3", "Section_4", "Section_5", and "plots". There are eight 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. Users need to place these eight 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 four folders and eight Python scripts. Users will then execute the command "python PRISMS_FIP_convergence_1st_highest_FIP_analysis.py" (or the name of another one of the eight scripts) to run the scripts. The scripts can also be executed using an interactive version of Python.
DECEMBER 2023 UPDATE:
The digital microstructure models (i.e., SVEs) used in this manuscript were generated using DREAM.3D version 6.5.141, but the raw microstructure files are not currently available in the .dream3d format. They were instead exported from DREAM.3D as "orientation_#.txt" and "grainID_#.txt" files. As such, a DREAM.3D pipeline (in the .json format) was uploaded entitled "reread_using_grain_and_ori.json" that can be used to generate .dream3d versions of each model used in this work. A few notes on the use of this pipeline are detailed below:
• Filer #1: point to the “grainID_#.txt” file
o Also, specify your origin and resolution properly.
• Filter #4: you must MANUALLY enter the Tuples dimension as (number of grains in this SVE +1) here, otherwise the pipeline will crash.
• Filter #6: point to the “orientations_#.txt” file to read grain orientations. AS A NOTE, these are currently labeled as "EulerAngles" but the "orientations_#.txt" files actually represent orientations as Rodriques vectors.
• Filter #15: write a new .dream3d file. |
Krzysztof S. Stopka, Mohammadreza Yaghoobi, John E. Allison, David L. McDowell |
ICME
fatigue
crystal plasticity
PRISMS
microstructure-sensitive
finite element method
fatigue indicator parameters
extreme value statistics
|
3 years ago |
1 year ago |
2023-12-30 16:17:26 |
|
PRISMS-Plasticity TM: An open-source rapid texture evolution analysis pipeline
|
The data base includes the input files for four different types of simulation. The first example is the evolution of texture during uniaxial compression of a polycrystalline OFHC copper sample with initial random texture. In the second example, the effect of the addition of rare earth elements to Mg is investigated by simulating the texture evolution in Mg-3Y alloy during rolling. The importance of twinning on the texture evolution of Mg alloys is highlighted in a third example, in which the evolution of texture in extruded Mg alloy ZK60A sample is captured during the uniaxial compression along the extrusion direction. Finally, the simulation inputs to generate results for "Application to machine learning frameworks" is presented. Also, the Jupyter Notebook to generate the results for Machine learning applications are also included. |
Mohammadreza yaghoobi, John E. Allison, Veera Sundararaghavan |
Twinning
PRISMS-Plasticity
ICME
Texture
Machine learning
Crystal plasticity
PRISMS-Plasticity TM
|
2 years ago |
2 years ago |
2023-04-26 18:09:53 |
|
Measuring and Modeling Microsegregation in High Pressure Die Cast Mg-Al Alloys
|
Grain Size, secondary phase (beta-Mg12Al12) volume fraction, and microsegregation was investigated as a function of aluminum content and through-thickness location in high pressure die cast (HPDC) Mg-Al and Mg-Al-Mn alloys. The experimental data was used to provide an empirical model for grain size and to calibrate a model used to predict the solidification front velocity dependent partition coefficients (which were found to deviate from the equilibrium partition coefficient near the surface the the plate where the cooling rate is higher). The model, in addition to an understanding of the distribution of externally solidified crystals throughout the HPDC component, can be used to predict the phase fractions and local microsegregation in Mg-Al alloys.
This work explores three different "regions of interest"
*edge is defined as the region less than 50 µm from the plate casting surface, EPMA scans were taken parallel to this surface, approximately 10 µm from the surface
*near edge is defined as the region 100 to 300 µm from the plate casting surface
*center is the region at least 500 µm from the casting surface, EPMA scans were taken near mid-thickness
The following scripts have been provided:
*EPMA_Analysis.nb was used to construct the microsegregation profiles using the weighted interval rank and sort (WIRS) technique
*Forward_Model_final.nb was used to run the EPMA forward model simulation and calculate the least squares difference between the experimental microsegregation profiles and the simulated results
*kv_solver_final.nb is used to predict the local velocity dependent partition coefficient given the alloy content, cooling rate, and local concentration of externally solidified crystals
*PhaseSeparationAlgorithm_Final.m was used to calculate the fraction of secondary phases from SEM images
The native language the .nb extension is Mathematica. The native language for the .m extension is Matlab. If a txt file of these scripts would be useful for you (so that it can be modified to work with a different platform), please feel free to contact the corresponding author.
Please feel free to contact the corresponding author with any questions or to ask for clarification:
Dr. Tracy Berman
email: tradiasa@umich.edu |
Tracy Berman, Zhenjie Yao, Erin Deda, Larrry Godlewski, Mei Li, John Allison |
ICME
magnesium alloy
microsegregation
solidification
high pressure die casting
HPDC
|
3 years ago |
1 day ago |
2025-07-09 14:41:03 |
|
Temperature-Dependent Material Database: HSLA-80
|
Data collected as part of the Lightweight Innovations for Tomorrow (LIFT) Institute’s program entitled, Robust Distortion Control Methods and Implementation for Construction of Lightweight Metallic Structures, which was lead by Huntington Ingalls Industries - Ingalls Shipbuilding (HII-Ingalls) from 2016-2018. |
Charles R. Fisher, Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang |
ICME
CWM
LIFT
Steel
Material Database
Welding
SYSWELD
Shipbuilding
HSLA-80
|
2 years ago |
1 year ago |
2023-10-03 20:06:18 |
|
PRISMS-Fatigue: Surface roughness and notch effects
|
This data set contains the DREAM.3D generated microstructures and PRISMS-Plasticity raw simulation results for the manuscript entitled "Microstructure-Sensitive Modeling of Surface Roughness and Notch Effects on Extreme Value Fatigue Response." |
Krzysztof S. Stopka, Mohammadreza Yaghoobi |
ICME
crystal plasticity
PRISMS
microstructure-sensitive
finite element method
fatigue modeling
Fatigue
Al 7075-T6
fatigue indicator parameter
|
2 years ago |
2 years ago |
2022-09-08 22:11:36 |
|
Temperature-Dependent Material Database: HSLA-100
|
Data collected as part of the Lightweight Innovations for Tomorrow (LIFT) Institute’s program entitled, Robust Distortion Control Methods and Implementation for Construction of Lightweight Metallic Structures (Round 2), which was lead by Huntington Ingalls Industries - Ingalls Shipbuilding (HII-Ingalls) from 2018-2019. |
Charles R. Fisher, Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang |
ICME
CWM
LIFT
Steel
Material Database
Welding
SYSWELD
Shipbuilding
HSLA-100
|
2 years ago |
1 year ago |
2023-10-03 20:08:10 |
|
Temperature-Dependent Material Database: HY-80
|
Data collected as part of the Lightweight Innovations for Tomorrow (LIFT) Institute’s program entitled, Robust Distortion Control Methods and Implementation for Construction of Lightweight Metallic Structures (Round 2), which was lead by Huntington Ingalls Industries - Ingalls Shipbuilding (HII-Ingalls) from 2018-2019. |
Charles R. Fisher, Justin E. Norkett, Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang |
ICME
CWM
LIFT
Steel
Material Database
Welding
SYSWELD
Shipbuilding
HY-80
|
1 year ago |
1 year ago |
2023-10-03 19:54:52 |
|
Temperature-Dependent Materials Database: HY-100
|
Data collected as part of the Lightweight Innovations for Tomorrow (LIFT) Institute’s program entitled, Robust Distortion Control Methods and Implementation for Construction of Lightweight Metallic Structures (Round 2), which was lead by Huntington Ingalls Industries - Ingalls Shipbuilding (HII-Ingalls) from 2018-2019. |
Charles R. Fisher, Justin E. Norkett, Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang |
ICME
CWM
LIFT
Steel
Material Database
Welding
SYSWELD
Shipbuilding
HY-100
|
1 year ago |
1 year ago |
2024-02-26 17:44:49 |