Application of Computer Vision Techniques to Identify Spray Primary Breakup Structures in High-Speed Flow

Accurate analysis of the spray formation process is of utmost importance because it governs the fuel injector performance in air-breathing engines. Historically, optical diagnostic measurements in this region have been limited, hindering progress in understanding the underpinning physics. Due to the rapid growth in computer power, first principle simulations of the primary breakup process are now available, providing access to the full spatiotemporal fields. This data is essential to investigate the physical instability modes. However, it typically relies on subjective criteria to identify the emerging structures in the spray formation process. Since computer vision tools are known to help automate such classification tasks, this work focuses on developing a framework that can be applied to help identify critical regions during the breakup process. The emerging spray structures identified and tracked include the well-known lobes, ligaments, and droplets that arise during the fuel injection process. Analysis shows that our approach yields promising results providing helpful statistics of the fundamental breakup dynamics for engineering analysis.