Mechanical Failure of Ammonium Perchlorate Composite Propellants for the Development of Computational Mechanical Models

Predictive mechanical models are crucial tools necessary for the design of safe and reliable propellants because they can be used to understand propellant properties and behavior without relying on experimental testing, which is costly and time consuming. Such models require extensive validation from comprehensive experimental data in order to be reliable. Training models with detailed and multi-faceted data sets is essential to accurately capture the complex heterogeneous nature of propellant. However, many historical data sets lack detailed information about sample topography, especially the presence of defects, which often drive failure. This work presents comprehensive experimental tensile testing data sets of ammonium perchlorate (AP) composite propellant that capture the role of surface defects. This was accomplished using Digital Image Correlation (DIC) to track local strain data during testing. Furthermore, an optical profilometer was used to calculate surface roughness and to identify voids, cracks, particle distribution, and protrusions. Analysis revealed a relationship between the mechanical behavior of the propellant sample and its surface topography at two strain rates. A phase field cohesive zone fracture model was used to capture crack initiation and propagation. Model output was compared to the experimental data, showing agreement with key parameters such as Young's Modulus and maximum stress. The multi-faceted data set presented here was used to enhance the mechanical modeling accuracy by revealing how surface topography influences mechanical properties. Overall, the validated model can be used to improve prediction of mechanical failure in propellants.