Power spectrum analysis (PSA) is a fast, non-destructive, sensitive method for examining commercial off-the-shelf ( COTS ) electronic components. These features make PSA attractive for both component screening and surveillance in support of component reliability efforts. Current analysis methods limit the utility of PSA due to the need to manually examine the results of analysis to identify anomalous parts. This study demonstrates the development and application of a workflow to automate the screening of COTS electronic components. Further, this study demonstrates the use of multivariate algorithms to assess aging of Zener diodes. These workflows can be readily extended to other components, combining the benefits of PSA and multivariate analysis to screen and evaluate COTS electronic components.
In this work, a high-throughput experimental setup was used to characterize initiation threshold and growth to detonation in the explosives hexanitrostilbene (HNS) and pentaerythritol tetranitrate (PETN). The experiment sequentially launched an array of laser-driven flyers to shock samples arranged in a 96-well microplate geometry, with photonic Doppler velocimetry diagnostics to characterize flyer velocity and particle velocity at the explosive–substrate interface. Vapor-deposited films of HNS and PETN were used to provide numerous samples with various thicknesses, enabling characterization of the evolution of growth to detonation. One-dimensional hydrocode simulations were performed with reactions disabled to illustrate where the experimental data deviate from the predicted inert response. Prompt initiation was observed in 144 μm thick HNS films at flyer velocities near 3000 m/s and in 125 μm thick PETN films at flyer velocities near 2400 m/s. This experimental setup enables rapid quantification of the growth of reactions in explosive materials that can reach detonation at sub-millimeter length scales. These data can subsequently be used for parameterizing reactive burn models in hydrocode simulations, as discussed in Paper II [D. E. Kittell, R. Knepper, and A. S. Tappan, J. Appl. Phys. 131, 154902 (2022)].
Reichardt, Thomas A.; Eaton, Samuel W.; Kulp, Thomas J.; DeJong, Stephanie D.; Ray, Will R.; Karnowski, Tom K.; Wetherington, Randall W.; Willis, Michael W.; Marcillo, Omar M.; Maceira, Monica M.; Chai, Chengping C.; Cardenas, Edna C.; Watson, Scott W.; Chichester, David C.; Gammans, Christine G.; Krebs, John K.; d'Entremont, Brian d.
Van Benthem, Mark H.; Keller, Timothy J.; Gillispie, Gregory D.; DeJong, Stephanie D.
This work presents a novel method of performing PARAFAC2 factorization of three-way data using a compact representation of that data. In the standard PARAFAC2 algorithm, two modes of the data are recovered directly during the decomposition while the third mode is returned as a transformation matrix, which is then used to rotate sets of orthogonal third-mode basis factors into interpretable factors. In our new method, the data are first decomposed into a core matrix and orthogonal factor loading matrices in the first two modes as well as sets of orthogonal factors in the third mode (as in standard PARAFAC2). The core matrix is then decomposed using a the standard PARAFAC2 strategy to produce transformation matrices in all three modes. The algorithm is particularly useful for very large data sets and essentially permits imposition of nonnegativity in all three modes.
Additive manufacturing via selective laser melting can result in variable levels of internal porosity both between build plates and within components from the same build. In this investigation, sample porosity levels were compared to tensile properties for 176 samples spanning eight different build plates. Sample porosity was measured both by Archimedes density, which provided an estimation of overall porosity, and by observation of voids in the fracture surface, which provided an estimation of the porosity at the failure plane. The porosity observed at the fracture surface consistently demonstrated higher porosity than that suggested by Archimedes density. The porosity values obtained from both methods were compared against the mechanical results. Sample porosity appears to have some correlation to the ultimate tensile strength, yield strength, and modulus, but the strongest relationship is observed between porosity and ductility. Three different models were used to relate the fracture surface porosity to the ductility. The first method was a simple linear regression analysis, while the other two models have been used to relate porosity to ductility in cast alloys. It is shown that all three models fit the data well over the observed porosity ranges, suggesting that the models taken from casting theory can extend to additively manufactured metals. Finally, it is proposed that the non-destructive Archimedes method could be used to estimate an approximate sample ductility through the use of correlations realized here. Such a relationship could prove useful for design and for a deeper understanding of the impact of pores on tensile behavior.