H S Udaykumar

The sensitivity of heterogeneous energetic (HE) materials (propellants, explosives, and pyrotechnics) is critically dependent on their microstructure. Initiation of chemical reactions occurs at hot spots due to energy localization at sites of porosities and other defects. Emerging multi-scale predictive models of HE response to loads account for the physics at the meso-scale, i.e. at the scale of statistically representative clusters of particles and other features in the microstructure. Meso-scale physics is infused in machine-learned closure models informed by resolved meso-scale simulations. Since microstructures are stochastic, ensembles of meso-scale simulations are required to quantify hot spot ignition and growth and to develop models for microstructure-dependent energy deposition rates. We propose utilizing generative adversarial networks (GAN) to spawn ensembles of synthetic heterogeneous energetic material microstructures. The method generates qualitatively and quantitatively realistic microstructures by learning from images of HE microstructures. We show that the proposed GAN method also permits the generation of new morphologies, where the porosity distribution can be controlled and spatially manipulated. Such control paves the way for the design of novel microstructures to engineer HE materials for targeted performance in a materials-by-design framework.

Head-to-head comparisons are made between calculations and experimental data on shock-driven pore collapse in the transparent material, poly(methyl methacrylate) (PMMA). Simulations are performed using SCIMITAR3D, an Eulerian sharp-interface multi-material code, while plate impact experiments are visualized using ultra-high speed x-ray imaging. The experiments and simulations are conducted over a wide range of loading conditions; from low strength loading regimes where adiabatic shear banding predominates all the way up to the regime where hydrodynamic pore collapse is expected. PMMA is modeled using an isotropic rate-dependent plasticity model for the deviatoric stress response and a Tillotson equation of state for the pressure. Calculations are primarily done in 2D, to save computational effort, but a limited number of 3D calculations are also performed to assess the differences entailed by the dimensionality. The 2D calculations are in fairly good agreement with the experimental results, for the evolution of pore shape. 3D calculations, while quite computationally intense, indeed produce better agreement with experimental data. The computations also agree well with the experiments in delineating the loading strength at which a transition from the strength-dominated to hydrodynamics-dominated pore collapse occurs. This work provides confidence in the ability of Eulerian, sharp interface computational techniques to correctly represent and understand the mechanics of shock-loaded porous condensed phase materials over a range of loading conditions.