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D. W. Eastman et al.
measurable experimentally through the use of 2D digital image correlation (DIC)
surface strain mapping. The creation of strain maps allows for the quantification
of strain localization on the sample surface and provides insight into how local
microstructural features influence deformation, both of which can be used as explicit
benchmarks for CPFEM. Local measurements such as these are needed to inform
and benchmark CPFEM modeling efforts.
The procedure for performing DIC on the FIB microtensile samples included
tracking of circular markers, machined into the sample surface with the FIB. Femtosecond laser-machined specimens were speckled with 50 nm diameter alumina
particles and distortions in the speckle pattern recorded at successive stages of
deformation. VIC2D was used to analyze the captured images and make 2D strain
maps. Correlating the strain maps with EBSD orientation maps allowed us to
identify the features in the microstructure that were present when plastic strain
developed and how the plastic deformation spread throughout the sample. Further
insights were gained by calculating the Schmid factor and elastic modulus for each
grain with the TSL OIM software.
An example of the surface strain evolution of a sample with a 50 × 50 μm cross
section is shown in Fig. 10. The strain plotted on this map is the local axial strain
in the loading direction. The snapshots presented in this figure demonstrate how
the strain in the sample first starts to nucleate and then eventually concentrates in
one location in the sample as the test proceeds. The global strain that the sample
experiences is labeled at the corner of each image and can be used to determine
how much greater the local strain is at these local hotspots. This behavior captures
the heterogeneous distribution of strain in a polycrystalline sample and can provide
both a qualitative and quantitative benchmark for CPFEM simulations. Correlating
these strain maps with the orientation information obtained from EBSD allows one
to identify microstructural characteristics that influence deformation in the sample.
To further look at the deformation behavior of these samples, these strain maps
were correlated with orientation information obtained from EBSD to investigate
microstructural features that lead to deformation. A summary of results for the
sample shown in Fig. 10 is shown in Fig. 11. Starting from the top of Fig. 11
and working down, what is being presented for this sample are: (a) a 2D map of
the surface orientation data collected from EBSD with each grain and twin colored
according to its out of plane orientation, (b) a 2D map with each grain and twin
colored according to its Schmid factor calculated based on the sample loading
direction and the EBSD data, (c) a 2D map of each grain and twin colored according
to its Young’s modulus calculated along the sample loading direction from the
EBSD data and the stiffness constants of the material, and (d) an overlay of the
2D strain map from Fig. 12 on an outline of the grain boundaries determined from
the EBSD orientation data. Each map is accompanied by a scale for the information
plotted on the maps.
The information compiled in Fig. 11 indicates that, in this sample, the strain
hotspot shown in Fig. 11d formed in the grain at the center of the sample that is
denoted by a blue color in the elastic modulus map of Fig. 11c. This grain had a
relatively high Schmid factor of 0.45 (greater than 60% of grains within the sample)
D. W. Eastman et al.
measurable experimentally through the use of 2D digital image correlation (DIC)
surface strain mapping. The creation of strain maps allows for the quantification
of strain localization on the sample surface and provides insight into how local
microstructural features influence deformation, both of which can be used as explicit
benchmarks for CPFEM. Local measurements such as these are needed to inform
and benchmark CPFEM modeling efforts.
The procedure for performing DIC on the FIB microtensile samples included
tracking of circular markers, machined into the sample surface with the FIB. Femtosecond laser-machined specimens were speckled with 50 nm diameter alumina
particles and distortions in the speckle pattern recorded at successive stages of
deformation. VIC2D was used to analyze the captured images and make 2D strain
maps. Correlating the strain maps with EBSD orientation maps allowed us to
identify the features in the microstructure that were present when plastic strain
developed and how the plastic deformation spread throughout the sample. Further
insights were gained by calculating the Schmid factor and elastic modulus for each
grain with the TSL OIM software.
An example of the surface strain evolution of a sample with a 50 × 50 μm cross
section is shown in Fig. 10. The strain plotted on this map is the local axial strain
in the loading direction. The snapshots presented in this figure demonstrate how
the strain in the sample first starts to nucleate and then eventually concentrates in
one location in the sample as the test proceeds. The global strain that the sample
experiences is labeled at the corner of each image and can be used to determine
how much greater the local strain is at these local hotspots. This behavior captures
the heterogeneous distribution of strain in a polycrystalline sample and can provide
both a qualitative and quantitative benchmark for CPFEM simulations. Correlating
these strain maps with the orientation information obtained from EBSD allows one
to identify microstructural characteristics that influence deformation in the sample.
To further look at the deformation behavior of these samples, these strain maps
were correlated with orientation information obtained from EBSD to investigate
microstructural features that lead to deformation. A summary of results for the
sample shown in Fig. 10 is shown in Fig. 11. Starting from the top of Fig. 11
and working down, what is being presented for this sample are: (a) a 2D map of
the surface orientation data collected from EBSD with each grain and twin colored
according to its out of plane orientation, (b) a 2D map with each grain and twin
colored according to its Schmid factor calculated based on the sample loading
direction and the EBSD data, (c) a 2D map of each grain and twin colored according
to its Young’s modulus calculated along the sample loading direction from the
EBSD data and the stiffness constants of the material, and (d) an overlay of the
2D strain map from Fig. 12 on an outline of the grain boundaries determined from
the EBSD orientation data. Each map is accompanied by a scale for the information
plotted on the maps.
The information compiled in Fig. 11 indicates that, in this sample, the strain
hotspot shown in Fig. 11d formed in the grain at the center of the sample that is
denoted by a blue color in the elastic modulus map of Fig. 11c. This grain had a
relatively high Schmid factor of 0.45 (greater than 60% of grains within the sample)