Characterization of bubble dynamics in the nozzle flow of aviation fuels via computer vision tools

Abstract

Bubble breakup and associated gaseous cavitation inception triggered by a single bubble injected into the flow of aviation fuel flowing in a converging–diverging nozzle are characterized by employing advanced computer vision (CV) algorithms. The obtained statistics from CV blob detection analysis provide unprecedented quantitative data from non-intrusive imaging techniques and reveal valuable insights regarding the kinematics of the bubble spatial–temporal evolution, breakup, and gaseous cavitation inception mechanisms in aviation fuels. A distinct constant velocity of the bubble before its breakup and constant group velocity of the resulting void cloud after the breakup are observed despite the continuous streamwise variation in fluid velocity in the nozzle. It is found that though the initial bubble size plays an essential role in the resulting void fraction variation after the breakup, it does not play a role in the bubble breakup location nor the resulting bubble terminal velocity before and void group velocity after the breakup. We define a unique dimensionless number, σb, that is able to distinguish between the breakup dynamic parameters for different fuels and flow regimes. Linear dependence is observed between the breakup location and σb. The obtained results shed some light on the kinematic evolution of a group of nonspherical cavities and will prove useful in modeling complex fuel cavitation mechanisms.