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Menasche, David B.

Publications and source records attributed to Menasche, David B..

Four-dimensional microstructurally small fatigue crack growth in cyclically loaded nickel superalloy specimen

Here, we nondestructively image a low-solvus high refractory (LSHR) nickel base specimen microstructure during cyclic loading to characterize crack propagation during the microstructurally small crack (MSC) growth regime. Micro-computed tomography (uCT) is used to characterize the material density and identify crack interfaces, while high-energy diffraction microscopy (HEDM) provides snapshots of the microstructural orientation field changes. From these measurements, data are computationally reconstructed and coregistered to describe the specimen’s configuration before load, before crack nucleation, and throughout the crack propagation/loading process. An MSC forms at a FIB-cut notch, which was previously placed to concentrate stress at the center of the specimen gauge, and propagates along a facet parallel to the local {1 1 1} crystallographic plane. Analysis of available crystallographic slip directions and measured point-to-point disorientation axes indicate probable single and coplanar slip activity along FCC octahedral planes within this region. Similar analyses of other crack propagation facets reveal generally slower growth along directions favoring zig-zag cross and codirectional cross slip, which are often disfavored at room temperature.

36 MATERIALS SCIENCE↗

Deep learning approaches to semantic segmentation of fatigue cracking within cyclically loaded nickel superalloy

Improvements to synchrotron-based micro-computed tomography scanning capabilities have gifted researchers the ability to characterize 4D material thermomechanical responses more thoroughly than ever before. These advancements, however, have brought about new challenges in analyzing the resulting deluge of data. We report on a nickel-based superalloy specimen imaged 26 times in-situ during cyclic loading at Argonne National Laboratory Advanced Photon Source beamline 1ID, in order to monitor crack growth within the microstructure. Therefore, several deep learning approaches which utilize convolutional neural networks are implemented to segment crack features from reconstructed tomography scans. U-Net architecture implementations are found to be especially effective, achieving IoU = 0.995 +/- 0.004 and Matthews correlation coefficient scores of Φ = 0.826 +/- 0.085. These advancements broaden possibilities for scientists seeking to automate segmentation analyses of similar large datasets.

36 MATERIALS SCIENCE↗

AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization

In this work, we describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and far-field modalities are employed in situ to track evolution of the material orientation and stress–strain fields at six points during the mechanical test, and these data streams are registered with micro-computed tomography reconstructions which probe the material density. This data volume was matched to a multi-modal serial sectioning characterization of the specimen taken after loading, described in this article’s companion. Twenty-eight grains which were monitored throughout the experiment were selected to form the basis for AFRL AM Modeling Series Challenge 4, Microscale Structure-to-Properties.

36 MATERIALS SCIENCE↗

Quantifying intermediate-frequency heterogeneities of SOFC electrodes using X-ray computed tomography

The electrodes in solid oxide fuel cells (SOFCs) consist of three phases interconnected in three dimensions. The volume needed to describe quantitatively such microstructures depends on several lengths scales, which are functions of materials properties and fabrication methods. This work focuses on quantifying the volume needed to represent “intermediate frequency” heterogeneities in electrodes of a commercial SOFC using X-ray computed tomography (CT) over two different length scales. Electrode volumes of 150 x 150 x 9 μm 3 were extracted from a synchrotron-based micro-CT data set, with 13 μm 3 voxels. 13.6 x 19.8 x 19.4 μm 3 of the cathode and 26.3 x 24.8 x 15.7 μm 3 of the anode were extracted from laboratory nano-CT data sets, both with 65 3 nm 3 voxels. After comparing the variation across sub-regions for the greyscale values from the micro-CT, and for the phase fractions and triple phase boundary densities from the nano-CT, it was found that the sub-region length scales needed to yield statistically similar average values were an order of magnitude larger than those expected to capture the “high frequency” heterogeneity related to the discrete nature of the three phases in electrodes. In conclusion, the challenge of quantifying such electrodes using available experimental methods is discussed.

36 MATERIALS SCIENCE↗

Correlation of Thermally Induced Pores with Microstructural Features Using High Energy X-rays

Combined application of a near-field High Energy Diffraction Microscopy measurement of crystal lattice orientation fields and a tomographic measurement of pore distributions in a sintered nickel-based superalloy sample allows pore locations to be correlated with microstructural features. Furthermore, measurements were carried out at the Advanced Photon Source beamline 1-ID using an X-ray energy of 65 keV for each of the measurement modes. The nickel superalloy sample was prepared in such a way as to generate significant thermally induced porosity. A three-dimensionally resolved orientation map is directly overlaid with the tomographically determined pore map through a careful registration procedure. The data are shown to reliably reproduce the expected correlations between specific microstructural features (triple lines and quadruple nodes) and pore positions. With the statistics afforded by the 3D data set, we conclude that within statistical limits, pore formation does not depend on the relative orientations of the grains. The experimental procedures and analysis tools illustrated are being applied to a variety of materials problems in which local heterogeneities can affect materials properties.

36 MATERIALS SCIENCE↗