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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2019

Nonlinear Resonant Ultrasound Spectroscopy for Predicting Sensitivity to Initiation in Granular High Explosives

Abstract Nonlinear Resonant Ultrasound Spectroscopy (NRUS) is a technique that can measure bulk nonlinear coefficients of the nonlinear elastic modulus for a material. NRUS has been used to identify damage in a variety of granular materials including rocks and concrete. Some energetic materials, such as Pentaerythritol Tetranitrate (PETN), are commonly fielded as pressed granular compacts. It is well known that the sensitivity to initiation of these materials is heavily dependent on their microstructure, and that microstructure changes naturally (becomes damaged) over time. In this study, we examine the use of NRUS to identify changes in microstructure between pristine and thermally aged PETN pellets. In particular, we examine the relationship between the bulk hysteretic nonlinearity, α , of the pellets and time spent at temperature, powder specific surface area (SSA), and sensitivity to initiation. We find that, in general, α does not increase uniformly for all pellets within a single thermal aging condition. However, when the pellets are test fired to determine sensitivity to initiation, there is a strong correlation between α and firing voltage threshold. NRUS‐measured α has the added benefit that the measurements can be made in situ and on benchtop scales.

Schulze, Peter↗
DOE OSTI2019

Linear Regression Based Multi-fidelity Surrogate for Disturbance Amplification in Multi-phase Explosion

When simulations are very expensive and many are required, as for optimization or uncertainty quantification, a way to reduce cost is using surrogates. With multiple simulations to predict the quantity of interest, some being very expensive and accurate (high-fidelity simulations) and others cheaper but less accurate (low-fidelity simulations), it may be worthwhile to use multifidelity surrogates (MFSs). Moreover, if we can afford just a few high-fidelity simulations or experiments, MFS becomes necessary. Co-Kriging, which is probably the most popular MFS, replaces both low-fidelity and high-fidelity simulations by a single MFS. A recently proposed linear regression–based MFS (LR-MFS) offers the option to correct the LF simulations instead of correcting the LF surrogate in the MFS. When the low-fidelity simulation is cheap enough for use in an application, such as optimization, this may be an attractive option. Here, we explore the performance of LR-MFS using exact and surrogate-replaced low-fidelity simulations. The concern studied is a cylindrical dispersal of 100-μ m-diameter solid particles after detonation and the quantity of interest is a measure of the amplification of the departure from axisymmetry. We find very substantial accuracy improvements for this problem using the LR-MFS with exact low-fidelity simulations. Inspired by these results, we also compare the performance of co-Kriging to the use of Kriging to correct exact low-fidelity simulations and find a similar accuracy improvement when simulations are directly used. For this problem, further improvements in accuracy are achievable by taking advantage of inherent parametric symmetries. These findings may alert users of MFSs to the possible advantages of using exact low-fidelity simulations when this is affordable.

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