Low-Order Prediction of Mineral Dust Sticking Probability in Turboshaft Engines

Matthew Ellis, Nicholas Bojdo, Antonino Filippone, Alison Pawley, Merren Jones

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Rotorcraft operations in arid environments can result in the ingestion of large quantities of dust particles into turboshaft engines, where they can melt and deposit on high pressure turbine nozzle guide vanes. This can result in reduced engine life-span and in worst case scenarios, in-flight engine failure. Predicting the extent and rate at which this damage occurs has proven difficult owing to the wide range of variables relating to the dust cloud, engine and most importantly, the properties of the particulate encountered. Whilst significant work has been carried out to model the particle deposition process for both volcanic ash and coal fly-ash, there is scarce similar work for the different types of mineral dusts rotorcraft encounter. In this contribution, we assess the suitability of two opposing numerical approaches for use in a generalised, reduced-order deposition model of individual mineral particles depositing on a vane. Both models are seen to be heavily reliant upon empirical inputs, be this the thermo-mechanical properties of the particles such as their yield strength, or currently unknown experimentally determined constants. An alternative approach is therefore proposed whereby the particle yield strength is correlated using existing relationships to the Vickers hardness of the grain, a property more amenable to empirical determination. The results obtained represent the current applicability limits of the two models based upon existing empirical data and thus highlight the need for further experimentation relating to both the thermo-mechanical properties and probabilities of adhesion for both individual mineral grains and mineral dust blends.
Original languageEnglish
Title of host publication76th Vertical Flight Society (VFS) Annual Forum
Publication statusAccepted/In press - 6 Dec 2019

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