Abstract

Abstract In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained to guide and validate them. For RANS-based CFD modeling approaches it is important to have representative ensemble average experimental results. For models that provide high fidelity local details such as LES-based CFD simulations, it is desirable to have precise individual experiment results. Making comparisons however is a challenge as it is impossible to directly compare local parameters between a given experiment and LES simulation. An optically accessible constant pressure flow rig (CPFR) is utilized to capture injection and reaction behavior with three optical diagnostic techniques: rainbow schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The benefit of these high-speed, simultaneous diagnostics is that local measurements can be made for every stage of a single injection event, observing both how much injections differ one from another, and also how such differences evolve temporally. The CPFR allows a sufficiently large number of repeated injection experiments to be performed for proper statistical analysis and ensemble convergence, while maintaining highly repeatable, nominally constant test conditions. Even given such stable conditions however, variations in local turbulent fuel-air mixing introduce a degree of variability which may manifest as significant differences in OH* and 2CP results. A statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the data set for discussion and analysis of shot-to-shot variation. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, lift-off length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each, are presented and discussed. While the results shown here can only postulate about the causation, the framework to characterize shot-to-shot variations could be leveraged to enable direct comparison with high-fidelity simulations without the need for averaging multiple realizations.

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