| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Dynamic Behavior of Materials X
|
| Presentation Title |
Evaluation of Microstructural Heterogeneity in Cast-cured Explosive Composites |
| Author(s) |
John Yeager, Matthew Santoso, Addison Wisniewski, Matthew Stuthers, Jesus Mares, Christopher Molek |
| On-Site Speaker (Planned) |
John Yeager |
| Abstract Scope |
Plastic-bonded explosives are granular composites generally containing micron scale explosive particles at 50+ volume percent loading within a polymer matrix. Mesoscale simulations of dynamic behavior of explosives often require realistic microstructures, particularly the actual particle size and spatial distributions. Such data is difficult to acquire and interpret due to similar physical and chemical makeup of the explosive and polymer, necessitating advanced image analysis techniques to classify the components. Here, we examine a typical cast-cured explosive with high filler content (~75 volume percent) using microcomputed X-ray tomography to evaluate microstructural heterogeneity as a function of distance from the as-cast surface. We quantify the heterogeneity using several types of algorithmic and machine learning approaches to classify the components into either explosive crystal, polymer binder, or void (air). Advantages of each technique will be discussed in terms of a ground truth evaluation, computational time, ease of use, and generalizability to other explosive formulations. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Characterization, Machine Learning, Composites |