Microstructural characterization of composite high explosives (HEs) has become increasingly important over the last several decades in association with the development of high fidelity mesoscale modeling and an improved understanding of ignition and detonation processes. HE microstructure influences not only typical material properties (e.g., thermal, mechanical) but also reactive behavior (e.g., shock sensitivity, detonation wave shape). A detailed nondestructive 3D examination of the microstructure has generally been limited to custom-engineered samples or surrogates due to poor contrast between the composite constituents. Highly loaded (>90 wt%) HE composites such as plastic-bonded explosives (PBX) are especially difficult. Here, we present efforts to improve measurement quality by using single and dual-energy microcomputed X-ray tomography and state-of-the-art image processing techniques to study a broad set of HE materials. Some materials, such as PBX 9502, exhibit suitable contrast and resolution for an automatic segmentation of the HE from the polymer binder and the voids. Other composite HEs had varying levels of success in segmentation. Post-processing techniques that used commercially available algorithms to improve the segmentation quality of PBX 9501 as well as zero-density defects such as cracks and voids could be easily segmented for all samples. Aspects of the materials that lend themselves well to this type of measurement are discussed.
Yeager, John D., et al. "Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives." Materials, vol. 13, no. 20, Oct. 2020. https://doi.org/10.3390/ma13204517
Yeager, John D., Kuettner, Lindsey A., Duque, Amanda L., Hill, Larry G., & Patterson, Brian M. (2020). Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives. Materials, 13(20). https://doi.org/10.3390/ma13204517
Yeager, John D., Kuettner, Lindsey A., Duque, Amanda L., et al., "Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives," Materials 13, no. 20 (2020), https://doi.org/10.3390/ma13204517
@article{osti_2325070,
author = {Yeager, John D. and Kuettner, Lindsey A. and Duque, Amanda L. and Hill, Larry G. and Patterson, Brian M.},
title = {Microcomputed X-Ray Tomographic Imaging and Image Processing for Microstructural Characterization of Explosives},
annote = {Microstructural characterization of composite high explosives (HEs) has become increasingly important over the last several decades in association with the development of high fidelity mesoscale modeling and an improved understanding of ignition and detonation processes. HE microstructure influences not only typical material properties (e.g., thermal, mechanical) but also reactive behavior (e.g., shock sensitivity, detonation wave shape). A detailed nondestructive 3D examination of the microstructure has generally been limited to custom-engineered samples or surrogates due to poor contrast between the composite constituents. Highly loaded (>90 wt%) HE composites such as plastic-bonded explosives (PBX) are especially difficult. Here, we present efforts to improve measurement quality by using single and dual-energy microcomputed X-ray tomography and state-of-the-art image processing techniques to study a broad set of HE materials. Some materials, such as PBX 9502, exhibit suitable contrast and resolution for an automatic segmentation of the HE from the polymer binder and the voids. Other composite HEs had varying levels of success in segmentation. Post-processing techniques that used commercially available algorithms to improve the segmentation quality of PBX 9501 as well as zero-density defects such as cracks and voids could be easily segmented for all samples. Aspects of the materials that lend themselves well to this type of measurement are discussed.},
doi = {10.3390/ma13204517},
url = {https://www.osti.gov/biblio/2325070},
journal = {Materials},
issn = {ISSN MATEG9},
number = {20},
volume = {13},
place = {Switzerland},
publisher = {MDPI AG},
year = {2020},
month = {10}}
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