Fast predicting the trajectory of chip-like particles by integrating a discrete element method model with a computational fluid dynamics-based aerodynamic database

Abstract

The accumulation of ice within aircraft engines poses a significant safety concern, necessitating effective and accessible methods to predict ice particle shedding trajectories. This study develops a novel method by integrating the discrete element method with a computational fluid dynamics (CFD)-based aerodynamic database, aiming to accurately predict the trajectories of chip-like ice particles under various conditions. The accuracy of the CFD-based aerodynamic database is validated through a quantitative comparison with experimental data, and the predicted trajectories align well with the experimental trajectories under varied conditions following a database-independence analysis. The results indicate that aerodynamic coefficients are independent of both the relative velocity and the scaling factor (k) for chip-like particles. Moreover, the initial angle of attack significantly influences the translational and rotational dynamics of chip-like particles. Furthermore, the chip-like ice particles released closer to the engine inlet exhibit a more uniform distribution of landing points, whereas those released at longer distances from the engine inlet tend to converge toward the central area of the engine. The methodology developed in this paper is expected to be a promising tool for fast predicting the trajectories of chip-like particles, thereby enhancing engine protection against ice impacts and improving overall operational safety.