Developing Virtual Microstructures and Statistically Equivalent Representative Volume Elements for Polycrystalline Materials
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This chapter introduces computational methods for generating virtual material microstructures of engineering materials with heterogeneities. Microstructures of polycrystalline materials containing localized features such as annealing twins, particulates or precipitates, and subgrain phases are the focus of this discussion. The methods use data from characterization methods to provide 3D statistical distribution and correlation functions that serve as inputs to the virtual microstructure generation process. Computational methods infer 3D statistical descriptors from 2D surface data and use stereology or other optimization-based projection techniques for 2D to 3D development. The chapter reviews the DREAM.3D software package and discusses newly developed methods to incorporate twins, particles, and subgrain-scale phases. Finally, the microstructure-based SERVE is introduced in the realm of establishing microstructure-property relations.
S. Ghosh acknowledges the contributions of his graduate students, M. Pinz, G. Weber, and X. Tu, and postdoctoral researcher, Dr. A. Bagri, for their contributions to various aspects presented in this chapter. He also acknowledges the sponsorship of the Air Force Office of Scientific Research, Air Force Research Laboratories (Program Manager A. Sayir), and Office of Naval Research (Program Manager W. Nickerson). Computing support by the Homewood High Performance Compute Cluster (HHPC) and Maryland Advanced Research Computing Center (MARCC) is gratefully acknowledged.
- Cai B, Adams B, Nelson T (2007) Relation between precipitate-free zone width and grain boundary type in 7075-T7 Al alloy. Acta Mat 55(5):1543–1553Google Scholar
- Echlin MP, Lenthe WC, Pollock TM (2014) Three-dimensional sampling of material structure for property modeling and design. Integ Mat Manuf Innov 3(1):21Google Scholar
- Groeber MA, Jackson M (2014) DREAM.3D: a digital representation environment for the analysis of microstructure in 3D. Integr Mat Manuf Innov 3:5Google Scholar
- Jackson M (2018) DREAM.3D 6.4 Release. http://dream3d.bluequartz.net/?page_id=32
- Lenthe W (2017) Twin related domains in polycrystalline nickel-base superalloys: 3d structure and fatigue. PhD thesis, University of California- Santa BarbaraGoogle Scholar
- Parthasarathy TA, Rao SI, Dimiduk D (2004) A fast spreadsheet model for the yield strength of superalloys. In: Green KA, Pollock TM, Harada H, Howson TE, Reed RC, Schirra JJ, Walston S (eds) TMS (The Minerals, Metals & Materials Society), Superalloys, pp 887–896Google Scholar
- Pinz M, Weber G, Lenthe W, Uchic M, Pollock T, Woodward C, Ghosh S (2018) Microstructure and property based statistically equivalent representative volume elements for modeling subgrain γ −γ′ microstructures in Ni-based superalloys. Acta Mater 157:245–258Google Scholar
- Rollett AD, Robert C, Saylor D (2006) Three dimensional microstructures: statistical analysis of second phase particles in AA7075-T651. Mater Sci Forum 519–521:1–10Google Scholar