Publications

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Traditional reactive flow modeling provides a computational representation of shock initiation of energetic materials. Most reactive flow models require ad hoc assumptions to obtain robust simulations, assumptions that result from partitioning energy and volume change between constituents in a reactive mixture. For example, most models assume pressure and/or temperature equilibrium for the mixture. Many mechanical insults to energetic materials violate these approximations. Careful analysis is required to ensure that the model assumptions and limitations are not exceeded. One limitation is that the shock to detonation transition is replicated only for strong planar shocks. Many models require different parameters to match data from thin pulse, ramp wave, or multidimensional loading, an approach that fails for complex loading. To accurately simulate reaction under non-planar shock impact scenarios a new formalism is required. The continuum mixture theory developed by Baer and Nunziato is used to eliminate ad hoc assumptions and limitations of current reactive flow models. This modeling paradigm represents the multiphase nature of reacting condensed/gas mixtures. Comparisons between simulations and data are presented.

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Scalable thermal runaway models for cook-off of energetic materials (EMs) require realistic temperature- and pressure-dependent chemical reaction rates. The Sandia Instrumented Thermal Ignition apparatus was developed to provide in situ small-scale test data that address this model requirement. Spatially and temporally resolved internal temperature measurements have provided new insight into the energetic reactions occurring in PBX 9501, LX-10-2, and PBXN-109. The data have shown previously postulated reaction steps to be incorrect and suggest previously unknown reaction steps. Model adjustments based on these data have resulted in better predictions at a range of scales.

The cookoff of energetic materials involves the combined effects of several physical and chemical processes. These processes include heat transfer, chemical decomposition, and mechanical response. The interaction and coupling between these processes influence both the time-to-event and the violence of reaction. The prediction of the behavior of explosives during cookoff, particularly with respect to reaction violence, is a challenging task. To this end, a joint DoD/DOE program has been initiated to develop models for cookoff, and to perform experiments to validate those models. In this paper, a series of cookoff analyses are presented and compared with data from a number of experiments for the aluminized, RDX-based, Navy explosive PBXN-109. The traditional thermal-chemical analysis is used to calculate time-to-event and characterize the heat transfer and boundary conditions. A reaction mechanism based on Tarver and McGuire's work on RDX{sup 2} was adjusted to match the spherical one-dimensional time-to-explosion data. The predicted time-to-event using this reaction mechanism compares favorably with the validation tests. Coupled thermal-chemical-mechanical analysis is used to calculate the mechanical response of the confinement and the energetic material state prior to ignition. The predicted state of the material includes the temperature, stress-field, porosity, and extent of reaction. There is little experimental data for comparison to these calculations. The hoop strain in the confining steel tube gives an estimation of the radial stress in the explosive. The inferred pressure from the measured hoop strain and calculated radial stress agree qualitatively. However, validation of the mechanical response model and the chemical reaction mechanism requires more data. A post-ignition burn dynamics model was applied to calculate the confinement dynamics. The burn dynamics calculations suffer from a lack of characterization of the confinement for the flaw-dominated failure mode experienced in the tests. High-pressure burning rates are needed for more detailed post-ignition studies. Sub-models for chemistry, mechanical response and burn dynamics need to be validated against data from less complex experiments. The sub-models can then be used in integrated analysis for comparison with experimental data taken during integrated tests.