Metal Dust Cloud Distribution Characterization Through Image Analysis

With the increasing development of metal additive manufacturing technology, the present need for accurate explosivity testing of high density and exotic metal powders is under active research. The accuracy of such tests depends upon the uniformity of the dust dispersion within the testing chambers during ignition. There is a need for further research to understand the dust cloud dispersion process in order to determine the best time for ignition. This study explores a methodology of using high-speed footage and image analysis to characterize the uniformity of a dust cloud temporally that future applications may build upon. This thesis consisted of the experimental methods used to generate a dust cloud for image acquisition and an in-depth study of processing pixel data in MATLAB to determine points of highest dust cloud uniformity. The image analysis process was applied to the generated footage and the results were assessed through visual means. The analysis was also applied to dust cloud footage generated by Lawrence Livermore National Laboratory on a transparent replica of a modified ANKO 20-L explosivity testing apparatus. The image analysis methodology proved to offer a promising means of determining dust distribution uniformity as it relates to the timing of explosivity ignition