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2, 5-Dimethylfuran (DMF) has been receiving increasing interest as a potential alternative fuel to fossil fuels, owing to the recent development of new production technology. However, the influence of DMF properties on the in-cylinder fuel spray and its evaporation, subsequent combustion processes as well as emission formation in current gasoline direct injection (GDI) engines is still not well understood, due to the lack of comprehensive understanding of its physical and chemical characteristics. To better understand the spray characteristics of DMF and its application to the IC engine, the fuel sprays of DMF and gasoline were investigated by experimental and computational methods. The shadowgraph and Phase Doppler Particle Analyzer (PDPA) techniques were used for measuring spray penetration, droplet velocity and size distribution of both fuels.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.