A Flexible and Efficient Output File Format for Grain-Scale Multiphysics Simulations

A Correction to this article was published on 21 September 2018

This article has been updated


Modern high-performing structural materials gain their excellent properties from the complex interactions of various constituent phases, grains, and subgrain structures that are present in their microstructure. To further understand and improve their properties, simulations need to take into account multiple aspects in addition to the composite nature. Crystal plasticity simulations incorporating additional physical effects such as heat generation and distribution, damage evolution, phase transformation, or changes in chemical composition enable the compilation of comprehensive structure–property relationships of such advanced materials under combined thermo-chemo-mechanical loading conditions. Capturing the corresponding thermo-chemo-mechanical response at the microstructure scale usually demands specifically adopted constitutive descriptions per phase. Furthermore, to bridge from the essential microstructure scale to the component scale, which is often of ultimate interest, a sophisticated (computational) homogenization scheme needs to be employed. A modular simulation toolbox that allows the problem-dependent use of various constitutive models and/or homogenization schemes in one concurrent simulation requires a flexible and adjustable file format to store the resulting heterogeneous data. Besides dealing with heterogeneous data, a file format suited for microstructure simulations needs to be able to deal with large (and growing) amounts of data as (i) the spatial resolution of routine simulations is ever increasing and (ii) more and more quantities are taken into account to characterize a material. To cope with such demands, a flexible and adjustable data layout based on HDF5 is proposed. The key feature of this data structure is the decoupling of spatial position and data, such that spatially variable information can be efficiently accommodated. For position-dependent operations, e.g., spatially resolved visualization, the spatial link is restored through explicit mappings between simulation results and their spatial position.

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Change history

  • 21 September 2018

    The correct copyright line for this article is “The Author(s) 2017. This article is an open access publication”, rather than “The Minerals, Metals & Materials Society 2017” (as in the original HMTL version of the article).


  1. 1.


  2. 2.


  3. 3.


  4. 4.


  5. 5.

    The volume element might be “representative” if it contains all important microstructural features and is of sufficient size.

  6. 6.

    In DAMASK, formally a Taylor homogenization scheme with one constituent is used that effectively just passes quantities from the constituent to the materialpoint level.


  1. 1.

    Folk M, Heber G, Koziol Q, Pourmal E, Robinson D (2011) An overview of the HDF5 technology suite and its applications, pp 36–47. doi:10.1145/1966895.1966900

  2. 2.

    Schmitz GJ (2016) Microstructure modeling in integrated computational materials engineering (ICME) settings: can HDF5 provide the basis for an emerging standard for describing microstructures?. JOM 68(1):77–83. doi:10.1007/s11837-015-1748-2

    Article  Google Scholar 

  3. 3.

    Roters F, Eisenlohr P, Kords C, Tjahjanto DD, Diehl M, Raabe D (2012) DAMASK: the Düsseldorf Advanced Material Simulation Kit for studying crystal plasticity using an FE based or a spectral numerical solver. In: Cazacu O (ed) Procedia IUTAM: IUTAM Symposium on Linking Scales in Computation: From Microstructure to Macroscale Properties. doi:10.1016/j.piutam.2012.03.001, vol 3. Elsevier, Amsterdam, pp 3–10

    Article  Google Scholar 

  4. 4.

    Jackson MA, Groeber MA, Uchic MD, Rowenhorst DJ, De Graef M (2014) h5ebsd: an archival data format for electron back-scatter diffraction data sets. Integr Mater Manuf Innov 3 (1):4. doi:10.1186/2193-9772-3-4

    Article  Google Scholar 

  5. 5.

    Groeber MA, Jackson MA (2014) DREAM.3D: A digital representation environment for the analysis of microstructure in 3D. Integr Mater Manuf Innov 3(1):5. doi:10.1186/2193-9772-3-5

    Article  Google Scholar 

  6. 6.

    Schroeder W, Martin K, Lorensen B (2006) The visualization toolkit, 4th edn, Kitware

  7. 7.

    Tasan CC, Hoefnagels JPM, Diehl M, Yan D, Roters F, Raabe D (2014) Strain localization and damage in dual phase steels investigated by coupled in-situ deformation experiments-crystal plasticity simulations. Int J Plast 63:198–210. doi:10.1016/j.ijplas.2014.06.004

    Article  CAS  Google Scholar 

  8. 8.

    Moulinec H, Suquet P (1994) A fast numerical method for computing the linear and nonlinear properties of composites. Comptes rendus de l’Académie des sciences. Série II, Mécanique, physique, chimie, astronomie 318:1417–1423

    Google Scholar 

  9. 9.

    Eisenlohr P, Diehl M, Lebensohn RA, Roters F (2013) A spectral method solution to crystal elasto-viscoplasticity at finite strains. Int J Plast 46:37–53. doi:10.1016/j.ijplas.2012.09.012

    Article  Google Scholar 

  10. 10.

    Alankar A, Eisenlohr P, Raabe D (2011) A dislocation density-based crystal plasticity constitutive model for prismatic slip in α-titanium. Acta Mater 59(18):7003–7009. doi:10.1016/j.actamat.2011.07.053

    Article  CAS  Google Scholar 

  11. 11.

    Wang H, Wu PD, Wang J, Tomé C.N. (2013) A crystal plasticity model for hexagonal close packed (HCP) crystals including twinning and de-twinning mechanisms. Int J of Plast 49:36–52. doi:10.1016/j.ijplas.2013.02.016

    Article  CAS  Google Scholar 

  12. 12.

    Peirce D, Asaro RJ, Needleman A (1983) Material rate dependence and localized deformation in crystalline solids. Acta Metall 31(12):1951–1976. doi:10.1016/0001-6160(83)90014-7

    Article  CAS  Google Scholar 

  13. 13.

    Shanthraj P, Sharma L, Svendsen B, Roters F, Raabe D (2016) A phase field model for damage in elasto-viscoplastic materials. Computer Methods in Applied Mechanics and Engineering 312:167–185. doi:10.1016/j.cma.2016.05.006

    Article  Google Scholar 

  14. 14.

    Tjahjanto DD, Eisenlohr P, Roters F (2010) A novel grain cluster-based homogenization scheme. Model Simul Mater Sci Eng 18:015006. doi:10.1088/0965-0393/18/1/015006

    Article  CAS  Google Scholar 

  15. 15.

    Tjahjanto DD, Eisenlohr P, Roters F (2015) Multiscale deep drawing analysis of dual-phase steels using grain cluster-based RGC scheme. Model Simul Mater Sci Eng 23:045005. doi:10.1088/0965-0393/23/4/045005

    Article  Google Scholar 

  16. 16.

    Eisenlohr P, Roters F (2008) Selecting sets of discrete orientations for accurate texture reconstruction. Comput Mater Sci 42(4):670–678. doi:10.1016/j.commatsci.2007.09.015

    Article  CAS  Google Scholar 

  17. 17.

    Ma A, Roters F, Raabe D (2007) A dislocation density based consitutive law for BCC materials in crystal plasticity FEM. Comput Mater Sci 39:91–95. doi:10.1016/j.commatsci.2006.04.014

    Article  CAS  Google Scholar 

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This research was carried out in the project TCMPrecipSteel of the SPP 1713 Strong coupling of thermo-chemical and thermo-mechanical states in applied materials of the Deutsche Forschungsgemeinschaft (DFG). The support of G. Heber from the HDF Group in designing the data structure is gratefully acknowledged.


Open Access Funding provided by Max Planck Society.

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Correspondence to Martin Diehl.

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Diehl, M., Eisenlohr, P., Zhang, C. et al. A Flexible and Efficient Output File Format for Grain-Scale Multiphysics Simulations. Integr Mater Manuf Innov 6, 83–91 (2017). https://doi.org/10.1007/s40192-017-0084-5

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  • Crystal plasticity
  • Heterogeneous data
  • Microstructures
  • HDF5
  • XDMF