This data set consists of over 6000 microstructure volumes and their associated local responses after three cycles of cyclic loading. These results were obtained through a novel localization protocol and were employed to evaluate the high cycle fatigue (HCF) resistance of 12 different polycrystalline microstructures [Priddy2016_Dissertation, Priddy2017_LocalizationHCF, Paulson2017_HomogenizationHCF].
Data Set Details
- 12 distinct alpha-titanium microstructures
- 500 instantiations (material volume elements or MVEs) per microstructure generated using DREAM.3D [Groeber2014_DREAM3D]
- each microstructure has different crystallographic texture inspired by literature [Peters1984_TextureFatigueTi,Wang2003_HexTexture,Lutjering2007_TiBook,Tromans2011_ElasticAnisotropyHCP] and prior experimental characterizations [Smith2016_RankTiHCF]
- each MVE is 21x21x21 voxels
- each voxel has a side length of 10e-6 meters
- materials knowledge system (MKS) protocols in conjunction with numerical scheme to integrate crystal plasticity framework [Priddy2016_Dissertation, Priddy2017_LocalizationHCF] developed by McDowell and co-workers [Smith2013_CyclicPlasticityTi]
- 3 cycles of fully reversed cyclic loading (R = -1)
- 0.5% applied strain amplitude (roughly 60-67% of the strain until yielding depending on the MVE)
- displacement-controlled periodic boundary conditions
- averaged strain tensor in each MVE has only one non-zero component (11, 22 and 33 components associated with x-, y- and z-direction loading, respectively)
- total strain, stress, plastic strain and various fatigue indicator parameters (FIPs) are provided for the minimum and maximum of the 3rd loading cycle
The image below displays an example MVE (colored by grain-ID) and a (0001) pole figure for each microstructure
Data Set Format
In this section, the contents of “data_localizationSPL.zip” are discussed in detail. Note that microstructures are referred to by informal monikers in this dataset. The formal labels [Paulson2016_BulkProperties, Paulson2017_HomogenizationHCF] and associated informal monikers are given as follows: A – actual, B – basaltrans, C – dice, D – innerdonut, E – outerdonut, F – random, G – trans, H – doubledonut, I – BaTrTr, J – DdTr, K – DiTr, L – OdTr.
The file, “data_localizationSPL.zip,” contains two folders, “field_quant” and “fip.” Each file in “field_quant” is titled “mks_alphaTi_#dir_IDval_##_sn###_step####.vtk,” where # denotes the loading direction (X, Y or Z), ## denotes the microstructure label, ### denotes the MVE number and #### denotes the step in the cyclic loading. Each .vtk file is human readable and contains the following arrays:
- coordinates of the edges of the voxels in each 21x21x21 MVE are defined
- grain-IDs are listed for all 9261 voxels
- Bunge-Euler angle triplets (in degrees) are listed for all 9261 voxels
- The stress tensor components (MPa) are tabulated for all 9261 voxels. The rows identify the voxels and the columns identify the components (11, 12, 13, 21, 22, 23, 31, 32, 33)
- The elastic strain tensor components are tabulated for all 9261 voxels. The rows identify the voxels and the columns identify the components (11, 12, 13, 21, 22, 23, 31, 32, 33)
Each file in “fip” is titled “mks_alphaTi_#dir_IDval_##_sn### Estimated_step####.vtk” where # denotes the loading direction (X, Y or Z), ## denotes the microstructure label, ### denotes the MVE number, and #### denotes the step in the cyclic loading. Each .vtk file is human readable and contains the following arrays:
- coordinates of the edges of the voxels in each 21x21x21 MVE are defined
- raw Fatemi-Socie (F-S) fatigue indicator parameters (FIPs) [McDowell2010_ModelFatigueCrack] as estimated using the novel localization protocol [Priddy2016_Dissertation, Priddy2017_LocalizationHCF] are listed for all 9261 voxels
- volume averaged FS-FIPs (over 8 voxels in a cube) as estimated using the novel localization protocols are listed for all 9261 voxels
- The plastic strain tensor components are tabulated for all 9261 voxels. The rows identify the voxels and the columns identify the components (11, 12, 13, 21, 22, 23, 31, 32, 33)
[Priddy2016_Dissertation] M.W. Priddy. “Exploration of forward and inverse protocols for property optimization of Ti-6Al-4V”. PhD thesis. Georgia Institute of Technology, 2016.
[Priddy2017_LocalizationHCF] Matthew W. Priddy, Noah H. Paulson, Surya. R. Kalidindi, David L. McDowell “Strategies for rapid parametric assessment of microstructure sensitive fatigue for HCP systems”. In Prep. (2017).
[Paulson2017_HomogenizationHCF] Noah H. Paulson, Matthew W. Priddy, David L. McDowell, Surya R. Kalidindi “Data-driven reduced-order models for rank-ordering the high cycle fatigue performance of polycrystalline microstructures”. In Prep (2017).
[Groeber2014_DREAM3D] Michael A. Groeber and Michael A. Jackson. “DREAM.3D: A Digital Representation Environment for the Analysis of Microstructure in 3D”. In: Integr. Mater. Manuf. Innov. 3.1 (2014), p. 5. issn: 2193-9772. doi: 10.1186/2193-9772-3-5. url: http://www.immijournal.com/content/3/1/5.
[Peters1984_TextureFatigueTi] M. Peters, A. Gysler, and G. Lütjering. “Influence of texture on fatigue properties of Ti-6Al-4V”. In: Metall. Trans. A 15.8 (1984), pp. 1597–1605. issn:1543-1940. doi:10.1007/BF02657799. url: http://dx.doi.org/10.1007/BF02657799.
[Wang2003_HexTexture] Y N Wang and J C Huang. “Texture analysis in hexagonal materials”. In:Mater. Chem. Phys. 81.1 (2003), pp. 11–26. issn: 0254-0584. doi: http://dx.doi.org/10.1016/S0254- 0584(03)00168- 8. url: http://www.sciencedirect.com/science/article/pii/S0254058403001688.
[Lutjering2007_TiBook] G. Lütjering and J.C. Williams. Titanium. Engineering Materials and Processes. Springer Berlin Heidelberg, 2007. isbn: 9783540730361. url: https://books.google.com/books?id=41EqJFxjA4wC.
[Tromans2011_ElasticAnisotropyHCP] Desmond Tromans. “Elastic anisotropy of HCP metal crystals and polycrystals”. In: Int. J. Res. Rev. Appl. Sci 6.4 (2011), pp. 462–483. url: http://www.arpapress.com/volumes/vol6issue4/ijrras%7B%5C_%7D6%7B%5C_%7D4%7B%5C_%7D14.pdf.
[Smith2016_RankTiHCF] Benjamin D Smith, Donald S Shih, and David L McDowell. “Fatigue hot spot simulation for two Widmanstätten titanium microstructures”. In: Int. J. Fatigue 92, Part 1 (2016), pp. 116–129. issn: 0142-1123. doi: http://dx.doi.org/10.1016/j.ijfatigue.2016.05.002. url: //www.sciencedirect.com/science/article/pii/S0142112316300883.
[Smith2013_CyclicPlasticityTi] B.D. Smith, D. Shih, and D.L. McDowell. “Cyclic Plasticity Experiments and Polycrystal Plasticity Modeling of Three Distinct Ti Alloy Microstructures”. In: Int. J. Plast. (2013). issn: 07496419. doi: 10.1016/j.ijplas.2013.10.004.
[Paulson2017_BulkProperties] Noah H. Paulson, Matthew W. Priddy, David L. McDowell, Surya R. Kalidindi “Reduced-order structure-property linkages for polycrystalline microstructures based on 2-point statistics”. In: Acta Mater. 129 (2017), pp. 428–438. doi: http://dx.doi.org/10.1016/j.actamat.2017. 03.009.
[McDowell2010_ModelFatigueCrack] D.L. McDowell and F.P.E. Dunne. Microstructure-sensitive computational modeling of fatigue crack formation". In: Int. J. Fatigue 32.9 (2010), pp. 1521-1542. issn: 0142-1123. doi: http://dx.doi.org/10.1016/j.ijfatigue.2010.01.003. url: http://www.sciencedirect.com/science/article/pii/S0142112310000162.
DREAM.3D for synthetic microstructure generation ABAQUS for property evaluations
NSF GOALI CMMI-1333083
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