A Three-Dimensional Flame Reconstruction Method for SI Combustion Based on Two-Dimensional Images and Geometry Model

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. The reconstruction results of deep learning modeling can reveal more accurate flame structure details. The fierce variation in the late stage of the statistic velocity curve was found to be a sign indicating the end of the flame development, which might be suitable as a robust and quick criterion in massive image data analysis.