Abstract:
A turbofan engine fying through adverse weather conditions will experience a change
in its performance. One of the most common examples of these hostile conditions
is the case of ice crystals ingestion. Identifying these performance variations would
lead to a detection strategy, that could be used to inform the pilots about the flying conditions, enhancing their decision making capability. In order to be able to
understand which are the key features of the engine behaviour during ice ingestion,
it is necessary to model and simulate such phenomenon.
In literature there are some examples of engine and compressor performance modelling during ice ingestion, but they are either incapable of producing transient or
full engine simulations, or impose very strict assumptions to the particles behaviour.
The objective of this PhD is to develop a gas turbine performance model for the
simulation of engine performance during ice particles ingestion and analyse the engine behaviour in those conditions, to identify its key characteristics.
The method was generated by coupling an engine simulation tool internally available
at Cranfield UTC and a newly developed code capable of modelling the ice particles
evolution. The engine simulation tool splits the engine core into a compression side,
modelled using 1D Euler equations with source terms to account for the influence of
bleeds, compressors and combustion chamber, and an expansion side, modelled via
quasi steady state matching. The ice particles code adopts a Lagrangian approach,
introducing a certain amount of ice particles at de ned time steps and modelling
their behaviour until they completely evaporate in the engine. The influence of the
particles on the engine performance is taken into account by source terms in the Euler equations and a new mass equation has been added to model the water vapour
that is being introduced into the main ow. The model takes into consideration also
the possibility of ice particles accretion on the compressor stator vanes.
The results have been compared with in-flight data, showing promising results in
capturing the expected trends in shaft rotational speed as well as pressure and temperature at the high pressure compressor outlet.