Computational Prediction of Probabilistic Ignition Behavior of PBXs from Microstructural Stochasticity
Min Zhou (Georgia Institute of Technolog), Ananda Barua (Georgia Institute of Technology), Seokpum Kim (Georgia Institute of Technology), Yasuyuki Horie (Air Force Research Lab)
Eringen Medal Symposium in honor of G. Ravichandran
Tue 4:20 - 5:40
Salomon 001
An approach is developed to computationally predict and quantify the stochasticity of the ignition process in polymer-bonded explosives (PBXs) under impact loading. The method involves subjecting sets of statistically similar microstructure samples to identical overall loading and characterizing the statistical distribution of the ignition response of the samples. Specific quantities predicted based on basic material properties and microstructure attributes include the critical time to ignition at given load intensity and the critical impact velocity below which no ignition occurs. The analyses carried out focus on the influence of random microstructure geometry variations on the critical time to ignition at given load intensity and the critical impact velocity below which no ignition occurs. Results show that the probability distribution of the time to criticality (tc) follows the Weibull distribution. This probability distribution is quantified as a function of microstructural attributes including grain volume fraction, grain size, specific binder-grain interface area, and the stochastic variations of these attributes. The relations reveal that the specific binder-grain interface area and its stochastic variation have the most influence on the critical time to ignition and the critical impact velocity below which no ignition is observed. Finally, it is shown that the probability distribution in the Weibull form can be reduced to an ignition threshold relation similar to the James relation in the v-t space.