Machine learning to analyze images of shocked materials for precise and accurate measurements
- Massachusetts Institute of Technology (MIT), Cambridge, MA (United States)
- Nevada National Security Site, North Las Vegas, NV (United States)
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
A supervised machine learning algorithm, called locally adaptive discriminant analysis (LADA), has been developed to locate boundaries between identifiable image features that have varying intensities. LADA is an adaptation of image segmentation, which includes techniques that find the positions of image features (classes) using statistical intensity distributions for each class in the image. In order to place a pixel in the proper class, LADA considers the intensity at that pixel and the distribution of intensities in local (nearby) pixels. This paper presents the use of LADA to provide, with statistical uncertainties, the positions and shapes of features within ultrafast images of shock waves. We demonstrate the ability to locate image features including crystals, density changes associated with shock waves, and material jetting caused by shock waves. This algorithm can analyze images that exhibit a wide range of physical phenomena because it does not rely on comparison to a model. LADA enables analysis of images from shock physics with statistical rigor independent of underlying models or simulations.
- Research Organization:
- Nevada Test Site (NTS), Mercury, NV (United States); Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA); US Department of the Navy, Office of Naval Research (ONR); USDOE Laboratory Directed Research and Development (LDRD) Program
- Grant/Contract Number:
- AC52-06NA25396; AC52-06NA25946; N00014-16-1-2090; N00014-15-1-2694.; 25946-3183
- OSTI ID:
- 1390321
- Alternate ID(s):
- OSTI ID: 1390398
- Report Number(s):
- DOE/NV/25946-3183
- Journal Information:
- Journal of Applied Physics, Vol. 122, Issue 10; ISSN 0021-8979
- Publisher:
- American Institute of Physics (AIP)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Single-Shot Multi-Frame Imaging of Cylindrical Shock Waves in a Multi-Layered Assembly
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journal | March 2019 |
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