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Generalized Predictions of Particle-Vane Retention Probability in Gas Turbine Engines
Author(s) -
Matthew Ellis,
Nicholas Bojdo,
Stephen CoveyCrump,
M. Jones,
Antonio Filippone,
Alison Pawley
Publication year - 2021
Publication title -
journal of turbomachinery
Language(s) - English
Resource type - Journals
eISSN - 1528-8900
pISSN - 0889-504X
DOI - 10.1115/1.4051108
Subject(s) - mechanics , particle (ecology) , range (aeronautics) , deposition (geology) , nozzle , dimensionless quantity , particle deposition , computational fluid dynamics , probability density function , particle number , materials science , environmental science , statistical physics , physics , mathematics , thermodynamics , statistics , volume (thermodynamics) , geology , composite material , sediment , paleontology , oceanography
The ingestion of airborne particulate into aircraft engines is an undesirable consequence of their operation, particularly in and out of arid locations that leads to reduced time between overhaul. Predicting the maintenance burden in environments rich in airborne particulate is made difficult by the large number of parameters that influence the likelihood of retention of the particles on nozzle guide vanes. In this contribution, we propose a new, reduced-order model that can predict the probability of particle retention as a function of a reduced set of independent variables relating to both the carrier gas flow and particle. Two-dimensional CFD simulations of particle deposition are performed on the General Electric E3 nozzle guide vane using the existing, energy-based fouling of gas turbines (EBFOG) particle deposition model. Results from the model are compared with experimental observations of particle deposition and show good agreement with the mass fraction retained by a vane. We introduce a function that allows the probability of retention to be calculated for a range of engine operating states and architectures by defining a new dimensionless parameter, the generalized thermal Stokes number. This parameter normalizes the thermal response of a particle for all gas and particle softening temperatures allowing the retention probability function to be applied universally. Finally, we demonstrate a practical use of this model by showing its use in calculating the accumulation factor for a particle size distribution.

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