A Framework for Quantifying Effects of
Characterization Error on the Predicted
Local Elastic Response in Polycrystalline
Materials
Noah Wade, Michael D. Uchic, Amanda Criner, and Lori Graham-Brady
1 Introduction
Advances in integrated computational materials engineering (ICME) are fundamentally dependent on acquisition of quality microstructural material information
in three dimensions (3D). DeHoff emphasized the importance of characterizing
microstructures in 3D in 1983, and since then a number of other authors have
illustrated the benefits of collecting detailed 3D microstructural data sets [1, 2].
This recognition has spurred the development of a whole suite of tools and methods
for collecting data across many different length scales [3], which in turn has led to
the development of more integrated material property-structure relationships. While
simplified microstructures are commonly applied to computational models [4], more
recent advances in computational power and automated sectioning techniques have
allowed the ICME community to begin exploring property-structure relationships
which were previously unattainable. This has encouraged significant investment of
equipment and time in collecting detailed 3D microstructures.
One example of this has been the development of focused ion beam (FIB) milling
within a scanning electron microscope (SEM) for rapid collection of 3D electron
backscatter diffraction (EBSD) data sets. Many papers have been published about
the development and advantages of this technique [5–11]. Uchic et al. highlighted
one of the main advantages of FIB-SEM as filling a critical length-scale gap between
mechanical serial sectioning and electron tomography [12], and this technology has
N. Wade · L. Graham-Brady ()
Department of Civil Engineering, Johns Hopkins University, Baltimore, MD, USA
e-mail: nwade2@jhu.edu; lori@jhu.edu
M. D. Uchic · A. Criner
Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson AFB,
Dayton, OH, USA
e-mail: micheal.uchic@us.af.mil; amanda.criner.1@us.af.mil
© Springer Nature Switzerland AG 2020
S. Ghosh et al. (eds.), Integrated Computational Materials Engineering (ICME),
https://doi.org/10.1007/978-3-030-40562-5_8
223
Characterization Error on the Predicted
Local Elastic Response in Polycrystalline
Materials
Noah Wade, Michael D. Uchic, Amanda Criner, and Lori Graham-Brady
1 Introduction
Advances in integrated computational materials engineering (ICME) are fundamentally dependent on acquisition of quality microstructural material information
in three dimensions (3D). DeHoff emphasized the importance of characterizing
microstructures in 3D in 1983, and since then a number of other authors have
illustrated the benefits of collecting detailed 3D microstructural data sets [1, 2].
This recognition has spurred the development of a whole suite of tools and methods
for collecting data across many different length scales [3], which in turn has led to
the development of more integrated material property-structure relationships. While
simplified microstructures are commonly applied to computational models [4], more
recent advances in computational power and automated sectioning techniques have
allowed the ICME community to begin exploring property-structure relationships
which were previously unattainable. This has encouraged significant investment of
equipment and time in collecting detailed 3D microstructures.
One example of this has been the development of focused ion beam (FIB) milling
within a scanning electron microscope (SEM) for rapid collection of 3D electron
backscatter diffraction (EBSD) data sets. Many papers have been published about
the development and advantages of this technique [5–11]. Uchic et al. highlighted
one of the main advantages of FIB-SEM as filling a critical length-scale gap between
mechanical serial sectioning and electron tomography [12], and this technology has
N. Wade · L. Graham-Brady ()
Department of Civil Engineering, Johns Hopkins University, Baltimore, MD, USA
e-mail: nwade2@jhu.edu; lori@jhu.edu
M. D. Uchic · A. Criner
Materials and Manufacturing Directorate, Air Force Research Laboratory, Wright-Patterson AFB,
Dayton, OH, USA
e-mail: micheal.uchic@us.af.mil; amanda.criner.1@us.af.mil
© Springer Nature Switzerland AG 2020
S. Ghosh et al. (eds.), Integrated Computational Materials Engineering (ICME),
https://doi.org/10.1007/978-3-030-40562-5_8
223