The development and application of an automatic boundary segmentation methodology to evaluate the vaporizing characteristics of diesel spray under engine-like conditions

Studying the vaporizing characteristics of diesel spray could greatly help to reduce engine emission and improve performance. The high-speed schlieren imaging method is an important optical technique for investigating the macroscopic vaporizing morphological evolution of liquid fuel, and pre-combustion constant volume combustion bombs are often used to simulate the high pressure and high temperature conditions occurring in diesel engines. Complicated background schlieren noises make it difficult to segment the spray region in schlieren spray images. To tackle this problem, this paper develops a vaporizing spray boundary segmentation methodology based on an automatic threshold determination algorithm. The methodology was also used to quantify the macroscopic characteristics of vaporizing sprays including tip penetration, near-field and far-field angles, and projected spray area and spray volume. The spray boundary segmentation methodology was realized in a MATLAB-based program. Comparisons were made between the spray characteristics obtained using the program method and those acquired using a manual method and the Hiroyasu prediction model. It is demonstrated that the methodology can segment and measure vaporizing sprays precisely and efficiently. Furthermore, the experimental results show that the spray angles were slightly affected by the injection pressure at high temperature and high pressure and under inert conditions. A higher injection pressure leads to longer spray tip penetration and a larger projected area and volume, while elevating the temperature of the environment can significantly promote the evaporation of cold fuel.