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The major challenge of the post-processing of soot aggregates in transmission electron microscope (TEM) images is the detection of soot primary particles that have no clear boundaries, vary in size within the fractal aggregates, and often overlap with each other. In this study, we propose an automated detection code for primary particles implementing the Canny Edge Detection (CED) and Circular Hough Transform (CHT) on pre-processed TEM images for particle edge enhancement using unsharp filtering as well as image inversion and self-subtraction. The particle detection code is tested for soot TEM images obtained at various ambient and injection conditions, and from five different combustion facilities including three constant-volume combustion chambers and two diesel engines.

Methods for detection of the spatial position and timing of diesel ignition with improved accuracy are demonstrated in an optically accessible constant-volume chamber at engine-like pressure and temperature conditions. High-speed pressure measurement using multiple transducers, followed by triangulation correction for the speed of the pressure wave, permits identification of the autoignition spatial location and timing. Simultaneously, high-speed Schlieren and broadband chemiluminescence imaging provides validation of the pressure-based triangulation technique. The combined optical imaging and corrected pressure measurement techniques offer improved understanding of diesel ignition phenomenon. Schlieren imaging shows the onset of low-temperature (first-stage) heat release prior to high-temperature (second-stage) ignition. High-temperature ignition is marked by more rapid pressure rise and broadband chemiluminescence.