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This study characterized uranium metal dust cloud combustion using absorption spectroscopy, imaging, and broadband emission measurements. Other metals were similarly combusted to establish correlations between results from this study and those found in the literature. It was determined that the burn temperature of uranium was limited to the volatilization temperature of uranium dioxide. Combustion behavior was similar to that of other refractory metals in terms of burn time and the observation of exploding particle behavior. [ABSTRACT FROM AUTHOR]

The reactivity of titanium and boron mixtures under detonation initiation in air is examined experimentally in a constant volume blast chamber. Fine powder mixtures and mechanical alloys are pressed into compacts and are ignited using an HMX-based explosive initiated with both single point and triple point detonator configurations. Transient pressure measurements, optical imaging, pyrometry, and spectroscopy are performed to analyse the reaction. All mixtures show no significant enhancement in the primary blast wave strength, indicating a relatively slow reaction. However, measurable increases in overpressure are generated due to Ti and/or B reaction. It is found that Ti/2B mechanical alloys significantly outperform blended powder mixtures in generating larger overpressures, yielding energy releases of 45 % and 20 %, respectively. Triple point initiation of the mechanical alloys further enhances the overpressure generation when compared to single point initiation of the alloys, increasing the energy yield. The overpressure of blended powders is also exceeded by a TiB2 compound, suggesting that the intermetallic reaction may be less critical than previously thought. Detonation merging at the plane of interaction between explosive and Ti/2B material is shown to significantly enhance conversion. Spectroscopic measurements show the appearance of BO2 emission relatively late after detonation in the most reactive Ti/2B reactive mechanical alloys, and it appears strongest in system that show greatest reactivity. [ABSTRACT FROM AUTHOR]

An experimental investigation of film cooling jet structure using two-dimensional particle image velocimetry (PIV) has been completed for cylindrical, simple angle (=35 deg) film cooling holes. The PIV measurements are coupled with detailed film cooling effectiveness distributions on the flat plate obtained using a steady state, pressure sensitive paint (PSP) technique. Both the flow and surface measurements were performed in a low speed wind tunnel where the freestream turbulence intensity was varied from 1.2% to 12.5%. With this traditional film cooling configuration, the blowing ratio was varied from 0.5 to 1.5 to compare the jet structure of relatively low and high momentum cooling flows. Velocity maps of the coolant flow (in the streamwise direction) are obtained on three planes spanning a single hole: centerline, 0.25D, and 0.5D (outer edge of the film cooling hole). From the seeded jets, time averaged, mean velocity distributions of the film cooling jets are obtained near the cooled surface. In addition, turbulent fluctuations are obtained for each flow condition. Combining the detailed flow field measurements obtained using PIV (both instantaneous and time averaged) with detailed film cooling effectiveness distributions on the surface (PSP) provides a more complete view of the coolant jet-mainstream flow interaction. Near the edge of the film cooling holes, the turbulent mixing increases, and as a result the film cooling effectiveness decreases. Furthermore, the PIV measurements show the increased mixing of the coolant jet with the mainstream at the elevated freestream turbulence level resulting in a reduction in the jet to effectively protect the film cooled surface. [ABSTRACT FROM AUTHOR]

Detailed film-cooling effectiveness distributions are obtained on a flat plate using the pressure sensitive paint (PSP) technique. The applicability of the PSP technique is expanded to include a coolant-to-mainstream density ratio of 1.4. The effect of density ratio on the film-cooling effectiveness is coupled with varying blowing ratio (M=0.25-2.0), freestream turbulence intensity (Tu=1-12.5%), and film hole geometry. The effectiveness distributions are obtained on three separate flat plates containing either simple angle, cylindrical holes, simple angle, fanshaped holes (α=10 deg), or simple angle, laidback, fanshaped holes (α=10 deg and γ=10 deg). In all three cases, the film-cooling holes are angled at θ=35 deg from the mainstream flow. Using the PSP technique, the combined effects of blowing ratio, turbulence intensity, and density ratio are captured for each film-cooling geometry. The detailed film-cooling effectiveness distributions, for cylindrical holes, clearly show that the effectiveness at the lowest blowing ratio is enhanced at the lower density ratio (DR=1). However, as the blowing ratio increases, a transition occurs, leading to increased effectiveness with the elevated density ratio (DR=1.4). In addition, the PSP technique captures an upstream shift of the coolant jet reattachment point as the density ratio increases or the turbulence intensity increases (at moderate blowing ratios for cylindrical holes). With the decreased momentum of the shaped film-cooling holes, the greatest film-cooling effectiveness is obtained at the lower density ratio (DR=1.0) over the entire range of blowing ratios considered. In all cases, as the freestream turbulence intensity increases, the film effectiveness decreases; this effect is reduced as the blowing ratio increases for all three film hole configurations. [ABSTRACT FROM AUTHOR]

Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline. [ABSTRACT FROM AUTHOR]