An Approach for Robust Design of Reactive Power Metal Mixtures Based on Non-deterministic Micro-scale Shock Simulation

Abstract

In this paper, we propose a method for the robust design of materials involving processes that are computationally intensive and selectively random. The material system considered is a reactive particle metal mixture (RPMM) composed of aluminum and iron oxide (Al+Fe2O3). Shock simulations of discrete energetic particle mixtures are performed to predict the system’s mechanical and thermal behavior that will be used by a designer of the mixture to achieve robust micro-scale reaction initiation. The method used to predict the behavior of the material system is the robust concept exploration method with error margin index (RCEM-EMI). An error margin index is a mathematical construct indicating the location of mean system performance and the spread of this performance considering both variability in design variables and models of the system. Variability in responses of a model may be due to system variation that cannot be easily parameterized in terms of noise factors. Furthermore, lack of data, due to the cost of simulations and experiments, leads to uncertain parameters in empirical models. System response variability and parameter uncertainty in an empirical model are estimated in a computationally efficient manner to formulate the error margin indices, which are then leveraged to search for ranged sets of design specifications. Finally, the RCEM-EMI is illustrated for designing a RPMM.