This work discusses new methodologies for identifying the grain boundaries in color images of metallic microstructures and the quantification of their grain topology. Grain boundaries have a large impact on the macro-scale material properties. Particularly, this work employs the experimental microstructure data of Titanium-Aluminum alloys, which can be used for various aerospace components owing to their outstanding mechanical performance in elevated temperatures. The grain topology of these metallic microstructures is quantified using the concept of shape moment invariants. In order to capture the grains using the shape moment invariants, it is necessary to identify the grain boundaries and separate them from their respective grains. We present two methodologies to detect the grain boundaries. The first method is the tolerance-based neighbor analysis. The second method focuses on creating three-dimensional space of pixel intensity values based on the three color channels and measuring the Euclidean distance to separate different grains. Additionally, since the grain boundaries may not possess the same material properties as the grain itself, this work investigates the effect of including the grain boundaries when determining the homogenized material properties of the given microstructure. To generate adequate statistical information, microstructures are reconstructed from the experimental data using the Markov Random Field (MRF) method. Upon separating the grains, we use the shape moment invariants to quantify the shapes of different grains. Using the shape moment invariants and the experimental material property values, three neural network functions are developed to investigate the effects of grain boundaries on material property predictions.
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Improved Formulae for Low-Frequency Ultrasonic Attenuation in Metals
A range of ultrasonic techniques associated with the nondestructive evaluation of metals involves the propagation of low-frequency elastic waves. Metals that are isotropic and homogeneous in the macroscopic length scale contain elastic heterogeneities, such as grain boundaries within the microstructures. Ultrasonic waves propagating through such microstructures get scattered from the grain boundaries. As a result, the propagating ultrasound attenuates. The mass density and the elastic anisotropy in each constituent grain govern the degree of heterogeneity in the polycrystalline aggregates. Existing elastodynamic models consider first-order scattering effects from grain boundaries. This paper presents the improved attenuation formulae, for the first time, by including the next order of grain scattering effects. Results from investigating 759 polycrystals reveal a positive correlation between the effects of higher-order scattering from grain boundaries and the degree of heterogeneity. Thus, higher-order grain scattering effects are now known. These results motivate further investigation into higher frequencies and strongly scattering alloys in the future.
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- Award ID(s):
- 2225215
- PAR ID:
- 10529350
- Publisher / Repository:
- Materials Evaluation
- Date Published:
- Journal Name:
- Materials Evaluation
- Volume:
- 82
- Issue:
- 6
- ISSN:
- 0025-5327
- Page Range / eLocation ID:
- 34 to 40
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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