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Burning aluminized propellants eject reacting molten aluminum drops with a broad size distribution. Prior to this work, in situ measurement of the drop size statistics and other quantitative flow properties was complicated by the narrow depth-of-focus of microscopic videography. Here, digital in-line holography (DIH) is demonstrated for quantitative volumetric imaging of the propellant plume. For the first time, to the best of our knowledge, in-focus features, including burning surfaces, drop morphologies, and reaction zones, are automatically measured through a depth spanning many millimeters. By quantifying all drops within the line of sight, DIH provides an order of magnitude increase in the effective data rate compared to traditional imaging. This enables rapid quantification of the drop size distribution with limited experimental repetition.

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This work presents measurements of liquid drop deformation and breakup time behind approximately conical shock waves and evaluates the predictive capabilities of low-order models and correlations developed using planar shock experiments. A conical shock was approximated by firing a bullet at Mach 4.5 past a vertical column of water drops with a mean initial diameter of [Formula: see text]. The time-resolved drop position and maximum transverse dimension were characterized using backlit stereo images taken at 500 kHz. The gas density and velocity fields experienced by the drops were estimated using a Reynolds-averaged Navier–Stokes simulation of the bullet. Classical correlations predict drop breakup times and deformation in error by a factor of 3 or more. The Taylor analogy breakup (TAB) model predicts deformed drop diameters that agree within the confidence bounds of the ensemble-averaged experimental values using a dimensionless constant [Formula: see text] compared to the accepted value [Formula: see text]. Results demonstrate existing correlations are inadequate for predicting the drop response to the three-dimensional relaxation of the flowfield downstream of a conical-like shock and suggest the TAB model results represent a path toward improved predictions.