This project aims to investigate the process of fragmentation (break up on impact) of mineral particles entering turbomachinery. Aero engines operating in desert environments are susceptible to damage by particles of naturally-occurring mineral dust, which are drawn into the engine in the air it uses to generate thrust. These particles range in size and mineralogy, which affects how easily they are carried by the flow and how quickly they melt in the high temperature, high pressure, high velocity environment of rotating turbomachinery. Predicting the damage done to engines by these particles requires an accurate understanding of their properties, such as their melting point, diameter, density, and concentration. However, if we rely on measurements these properties by simply sampling the dust in the ambient air, we have to assume that these properties remain the same throughout the engine. Unfortunately, this is not the case.

Fragmentation is one way that the particles undergo change in the engine. Other ways include melting, agglomeration with other particles, and chemical reactions. The damage done to engine components by mineral dust is relatively well known, but the risk of the damage occurring in a given environment is less well known due to the huge variation in particle properties. This PhD project will conduct experiments to understand better the physics of particle fragmentation, and to build mathematical models that can predict the changes to the particle size distribution and composition for different engines. This will be achieved through several objectives:
a. To characterise all physical and chemical processes acting on foreign environmental dust as it passes through the fan, compressor, combustor and turbine stages of a gas turbine engine.
b. To identify existing models of particle fragmentation, phase change and reaction in the literature
c. To conduct experimental research to simulate physico-chemical processes in gas turbine engines to develop new stochastic models of particle fracture as a function of mineralogy.
d. To build a program to predict probability density functions of key particle properties along the engine gas path, and validate with existing test data in partnership with industrial collaborators.
e. To implement physico-chemistry based models into a predictive tool for online engine health prognostics, in combination with engine gas path analysis software
f. To validate the software with by conducting Monte Carlo simulations with a pre-existing in-house flight performance code (FLIGHT )

The outcome of this PhD will be a novel tool that can predict, with a degree of confidence, the properties of mineral contaminant dust entering a given gas turbine engine stage. This can be used by airline operators, engine manufacturers, and researchers to develop more accurate component life and engine performance predictions and new mitigation strategies to ultimately reduce the enormous maintenance burden of operating in dusty environments.

This research sits in the following EPSRC research areas:
Statistics and applied probability
Fluid dynamics and aerodynamics
Performance and inspection of mechanical structures and systems
Particle technology