Predicting Cavitation Erosion Propensity and Severity in Fuel Injection Systems

The objective of this work is to identify computational metrics that can characterize the erosive potential of cavitation within injector orifices. While a commonly employed cavitation erosion metric, namely the maximum local pressure, was found to describe single impact events, no additional information could be determined regarding the material erosion process. To improve representation of the incubation period, a new metric was derived based on the cumulative energy absorbed by the solid material from repeated hydrodynamic impacts. The stored energy metric was then implemented into CONVERGE. Large eddy simulations for turbulent cavitating flow through channel geometries were performed, where the multiphase and multi-component flow was represented using a homogeneous mixture modeling approach. Through comparison against available experimental data, the stored energy metric was found to accurately predict the influence of flow conditions on the incubation period before material erosion. Additionally, detailed analysis of cavitation cloud collapse events highlighted the strong correlation between cloud collapse mechanisms and their erosive potential.