Observational analysis predicts sealing performance in engines based on annulus swirl and purge, suggesting a new method for efficiency.
Physically-informed low-order models are important in the engine design process. The Ingress Wave Model uses a single, empirically-correlated parameter to physically link the shear-driven unsteadiness in the cavity with the swirl in the annulus. In this paper, newly-collected and existing experimental data from three facilities and rim seal geometries demonstrated that this unsteadiness is a linear function of the annulus swirl, with the superposition of purge creating a weak, secondary effect. The novel introduction of the linear correlation enables predictions of sealing effectiveness across the entire engine operating range from just two data points. A larger set of data is shown to improve the accuracy and robustness. Here the method is validated by data collected at low technology readiness level (TRL). The methodology could be applied to data collected from a high TRL demonstrator engine or computational fluid dynamics. This will reduce the number of demonstrator experiments (and associated costs) during design iterations. This paper provides an original scaling methodology in the practical context of the engine design process, including the effects of density. Aero-engines operate with a significant purge-mainstream density ratio (DR), due to differences in the temperatures of the two streams. The methodology incorporates predictions of DR and is further validated against data collected at DR = 1 and 1.5. The model demonstrates that neglecting DR will provide significantly underpredicted rim seal performance.
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Vella et al. (2025) studied this question.
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