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The partial melting of ingested ice crystals can lead to ice accretion in aircraft compressors, but accurately measuring the relatively small fraction of liquid water content in such flows is challenging. Probe-based methods for detecting liquid water content are not suitable for deployment within turbofan engines, and thus alternatives are sought. Recent research has described approaches based on passive microwave sensing. We present here an approach based on active microwave transmission and reflection, employing a vector network analyzer. Utilization of both transmission and reflection provides additional data over and above emission or transmission only, and permits a more controllable environment than passive sensing approaches. The paper specifically addresses the question of whether such an approach is viable within the context of representative icing wind tunnel and engine flow conditions.

In-cylinder flow motion has a significant effect on mixture preparation and combustion. Therefore, it is vital that CFD engine simulations are capable of accurately predicting the in-cylinder velocity fields. High-speed planar Particle Image Velocimetry (PIV) experiments have been performed on a single-cylinder GDI optical engine in order to validate CFD simulations for a range of engine conditions. Novel metrics have been developed to quantify the differences between experimental and simulated velocity fields in both alignment and magnitude. The Weighted Relevance Index (WRI) is a variation of the standard Relevance Index that accounts for the local velocity magnitudes to provide a robust comparison of the alignment between two vector fields. Similarly, the Weighted Magnitude Index (WMI) quantifies the differences in the local magnitudes of the two velocity fields.

A significant number of historical engine powerloss events have recently been attributed to ingestion of high altitude ice crystals, prompting regulators to expand engine certification envelopes to incorporate ‘ice crystal icing’ conditions. There has been a resulting effort by OEMs and academia to develop analytical and semi-empirical models for the phenomenon, partly through use of rig testing. The current study presents results and analysis of experiments conducted in the National Research Council’s Research Altitude Test Facility (RATFac). The experiments used a simplified compressor stator vane test article, designed to produce data to build semi-empirical models and validate an existing ice crystal icing code. Accretion growth rates, extracted from backlit shadowgraphy, are presented as a function of test condition, and the algorithm of a new image processing technique using Canny filtering is discussed.

Numerous turbofan power-loss events have occurred in high altitude locations in the presence of ice crystals. It is theorized that ice crystals enter the engine core, partially melt in the compressor and then accrete onto stator blade surfaces. This may lead to engine rollback, or shed induced blade damage, surge and/or flameout. The first generation of ice crystal icing predictive models use a single flow field where there is no accretion to calculate particle trajectories and accretion growth rates. Recent work completed at the University of Oxford has created an algorithm to automatically detect the edge of accretion from experimental video data. Using these accretion profiles, numerical simulations were carried out at discrete points in time using a manual meshing process.