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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.

One major drawback of spark-ignition direct-injection (SIDI) engines is increased particulate matter (PM) emissions at high load, due to increased wall wetting and a reduction in available mixture preparation time when compared to port-fuel injection (PFI). It is therefore necessary to understand the mechanics behind injection strategies which are capable of reducing these emissions while also maintaining the performance and efficiency of the engine. Splitting the fuel delivery into two or more injections is a proven way of working towards this goal, however, many different injection permutations are possible and as such there is no clear consensus on what constitutes an ideal strategy for any given objective. In this study, the effect of the timing of the first and second injections for an evenly split dual injection strategy are investigated in an optical SIDI engine running at 1200 RPM with an unthrottled intake.