Unsupervised Machine Learning for Evaluation of Aging in Explosive Pressed Pellets
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
This project is an evaluation of the changes in the dimensional geometry of pressed explosive powder pellets when stored for prolonged periods under unmonitored storage conditions. Through the application of Structural Health Monitoring (SHM) techniques, questions to be answered by this investigation are what, if any, effect has the long-term storage of the pellets had on their physical attributes and, if changes have occurred, are the resulting differences of significant magnitude to affect the performance of the pellets. This resulting report includes a summary of the relevant background information, explanation of the SHM approach used to analyze the available data, presentation and discussion of the results, concluding remarks, and an accompanying appendix containing the MATLAB program developed for the project.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- 89233218CNA000001
- OSTI ID:
- 1484618
- Report Number(s):
- LA-UR--18-31299
- Country of Publication:
- United States
- Language:
- English
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