Numerical Assessment of Cavitation Damage in Fluid Machinery: High-Pressure Fuel Injectors and Water-jet Pumps

Doktorsavhandling, 2025

Cavitation erosion poses a significant challenge in high-pressure fuel injectors and water-jet propulsion systems, affecting performance and durability. This thesis presents a numerical investigation into cavitation erosion mechanisms using Computational Fluid Dynamics (CFD) methodologies, incorporating turbulence modeling, cavitation closure models, and erosion prediction techniques.

For high-pressure fuel injectors, both static and dynamic lift conditions were examined. The findings highlight that surface deviations significantly affect vapor collapse dynamics and erosion patterns, emphasizing the importance of incorporating multi-hole simulations and real-world geometries for accurate predictions. Additionally, the study demonstrates that transient needle motion, specifically wobbling effects, alters cavitation-induced pressure loads, influencing erosion distribution. A comparison of thermodynamic models showed that the Perturbed-Chain Statistical Associating Fluid Theory with Compressible Vapor (PC-SAFT\&CV) model predicts vapor collapse and erosion localization more accurately than the Tait Equation of State with Incompressible Vapor (Tait\&IV) approach.

In water-jet propulsion systems, a RANS-based cavitation erosion assessment framework was developed using the Schnerr-Sauer cavitation model. The study reveals that operating conditions, such as inlet velocity and pressure variations, significantly affect cavitation behavior and erosion risk distribution. While the numerical predictions capture high-risk cavitation collapse regions, RANS-based approaches exhibit limitations in resolving transient cavitation structures.

This research contributes to the development of predictive erosion assessment methodologies for industrial applications. Key contributions include an erosion risk assessment framework applicable to both fuel injectors and water-jet propulsion systems, insights into thermodynamic effects and transient needle motion on cavitation erosion, and the implementation of computationally efficient RANS-based assessment tools.