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. Through a comparison between automatically detected and manually selected primary particles from extensive datasets, five key image-processing parameters of the self-subtraction level, negative Laplacian shape parameter, maximum and minimum diameter of primary particles, and CHT sensitivity are optimised. From the analysis of the size distribution and mean diameter of primary particles, it is found that the automatic method is much more dependent upon the minimum primary particle diameter and CHT sensitivity than the other three parameters. With the optimised set values, the new particle detection code shows a good agreement with the results from the manual method.

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In-flame soot sampling based on the thermophoresis of particles and subsequent transmission electron microscope (TEM) imaging has been conducted in a diesel engine to study size, shape and structure of soot particles within the reacting diesel jet. A direct TEM sampling is pursued, as opposed to exhaust sampling, to gain fundamental insight about the structure of soot during key formation and oxidation stages. The size and shape of soot particles aggregate structure with stretched chains of spherical-like primary particles is currently an unknown for engine soot modelling approaches. However, the in-flame sampling of soot particles in the engine poses significant challenges in order to extract meaningful data. In this paper, the engine modification to address the challenges of high-pressure sealing and avoiding interference with moving valves and piston are discussed in detail. Of particular interest is the uncertainty caused by a selection of the on-grid locations for transmission electron microscope imaging and cycle-to-cycle fluctuations of the engine combustion. Marked variations are observed in the number and projected area of soot particles depending on these variations; however, their impacts on the size of aggregates and primary particles is found to be minor. Also, the morphology of soot particles appears not to be sensitive to the exposure duration of the grid to the sooting flame; however, the duration is ultimately limited by soot over-loading. Two different injection pressures are selected to test the usefulness of the in-flame soot sampling in a diesel engine and the results show that a decrease in the size of soot aggregates and primary particles with increasing injection pressure exceeds the uncertainty.

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The current understanding of soot particle morphology in diesel engines and their dependency on the fuel injection timing and pressure is limited to those sampled from the exhaust. In this study, a thermophoretic sampling and subsequent transmission electron microscope imaging were applied to the in-flame soot particles inside the cylinder of a working diesel engine for various fuel injection timings and pressures. The results show that the number count of soot particles per image decreases by more than 80% when the injection timing is retarded from −12 to −2 crank angle degrees after the top dead center. The late injection also results in over 90% reduction of the projection area of soot particles on the TEM image and the size of soot aggregates also become smaller. The primary particle size, however, is found to be insensitive to the variations in fuel injection timing. For injection pressure variations, both the size of primary particles and soot aggregates are found to decrease with increasing injection pressure, demonstrating the benefits of high injection velocity and momentum. Detailed analysis shows that the number count of soot particles per image increases with increasing injection pressure up to 130 MPa, primarily due to the increased small particle aggregates that are less than 40 nm in the radius of gyration. The fractal dimension shows an overall decrease with the increasing injection pressure. However, there is a case that the fractal dimension shows an unexpected increase between 100 and 130 MPa injection pressure. It is because the small aggregates with more compact and agglomerated structures outnumber the large aggregates with more stretched chain-like structures.