Statistically advanced, self-similar, radial probability density functions of atmospheric and under-expanded hydrogen jets

Abstract

used to separate the turbulent and pure air data, and thusly estimate intermittency. Beta-distributions (four parameters) are used to accurately represent the turbulent distribution moments. This combination of measured intermittency and four-parameter beta-distributions constitutes a new, simple approach to model scalar mixing. Comparisons between global moments from the data and moments calculated using the proposed model show excellent agreement. This was attributed to the high quality of the measurements which reduced the width of the correctly identified, noiseaffected pure air distribution, with respect to the turbulent mixing distribution. The ignitability of the atmospheric jet is determined using the flammability factor calculated from both kernel density estimated (KDE) PDFs and PDFs generated using the newly proposed model. Agreement between contours from both approaches is excellent. Ignitability of the under-expanded jet is also calculated using KDE PDFs. Contours are compared with those calculated by applying the atmospheric model to the under-expanded jet. Once again, agreement is excellent. This work demonstrates that self-similar scalar mixing statistics and ignitability of atmospheric jets can be accurately described by the proposed model. This description can be applied with confidence to under-expanded jets, which are more realistic of leak and fuel injection scenarios.Abstract This paper presents improved statistical insight regarding the self-similar scalar mixing process of atmospheric hydrogen jets and the downstream region of underexpanded hydrogen jets. Quantitative planar laser Rayleigh scattering imaging is used to probe both jets. The self-similarity of statistical moments up to the sixth order (beyond the literature established second order) is documented in both cases. This is achieved using a novel self-similar normalization method that facilitated a degree of statistical convergence that is typically limited to continuous, pointbased measurements. This demonstrates that image-based measurements of a limited number of samples can be used for self-similar scalar mixing studies. Both jets exhibit the same radial trends of these moments demonstrating that advanced atmospheric self-similarity can be applied in the analysis of under-expanded jets. Self-similar histograms away from the centerline are shown to be the combination of two distributions. The first is attributed to turbulent mixing. The second, a symmetric Poisson-type distribution centered on zero mass fraction, progressively becomes the dominant and eventually sole distribution at the edge of the jet. This distribution is attributed to shot noise-affected pure air measurements, rather than a diffusive superlayer at the jet boundary. This conclusion is reached after a rigorous measurement uncertainty analysis and inspection of pure air data collected with each hydrogen data set. A threshold based upon the measurement noise analysis is

Ignition and flame characteristics of cryogenic hydrogen releases

“…The maximum ignition distance ( ) depends on the hydrogen pressure, temperature, and leak diameter. Depending on the local fuel mass fraction, an ignition kernel formed at a particular location could propagate towards the release source leading to a sustained jet flame [21][22]. In the current study, the maximum ignition distance at which a sustained jet flame could be The scatter plot of maximum ignition distance for all of the test cases now collapses, with a linear dependence on the effective diameter.…”

Research on Characteristics of Hydrogen Dynamic Leakage and Combustion at High Pressure

“…And experimental data on changes of stagnation parameters over time in the process of dynamic leakage of hydrogen were lacking. Studies on the propagation law of flame upstream and downstream in the turbulent hydrogen jet were rare, and systematic quantitative analysis of flame propagation velocity was lacking [21][22][23][24][25]. This paper focuses on the weak points of current research.…”