Abstract:
There is a common
requirement in the process, oil and gas turbine industries for high
performance axial flow compressors operating over a wide range of mass flow rate and
rotational
speed at high efficiency. The trends have been for higher blade loadings
(greater pressure rise per stage) and higher efficiency which are increasingly achieved
through sophisticated Computational Fluid Dynamics designs. These trends, however,
tend to
mitigate against stable operating flow range (reduced surge margin), which can
often lead to
performance compromises. The objective of this work is to investigate the
possibility of using alternative means to gain ow range by better use of variable
geometry, which may permit design objectives to be better achieved. Variable
geometry of the type envisaged is already often employed to overcome part-speed
operating problems, but it proposed here that there may be additional benefits from their
more
intelligent control.
The
operation of axial compressors with a wide operating range is limited by
instabilities, which cause a full breakdown of the flow, which is surge. These
instabilities, which are caused by high incidence and subsequent stalling of stages occur
due to different
phenomena at part and full speed operation. The problem at part-speed
is that the front
stages are often heavily stalled and rear stages choked, whereas at high
speeds, the front stages are operating close to choke and the rear stages tend to be
stalling. Optimisation of the design to full load conditions can often provide part-speed
problems and to achieve the acceptable performance, variable geometry over the front
region of the compressor is sometimes used to modify the flow angles and avoid stage
stall and
subsequent surge. To-date, such variable settings follow some schedule
established
by analysis and experiment whereas this work presents a methodology of
setting blade rows using an optimisation procedure and investigates the likelihood of
performance benefits being obtained by a control technique which reacts° to these
changing conditions.
The construction of the numerical method
presented in this thesis was done with an
emphasis upon its intended contribution towards a eventual online control application.
Therefore, a practical approach has been employed in the development of the
compressor modelling techniques used in the work. Specifically, a highly empirical
one-dimensional
performance prediction code was constructed, employing successful
correlations taken from the literature. This was
coupled to a surge prediction method
that has been shown in the
past to function more than satisfactorily in a multistage
environment.
Finally, the predicted stage and overall performance (including the surge
point) characteristics were passed to a optimisation program, which allowed these
simulated conditions to be
investigated.
It is
hoped that the work presented has illustrated the potential (from a aerodynamic
performance point of view) of such a control technique to offer additional freedom in
the
operation of a multistage axial flow compressor. Moreover, the numerical
modelling techniques have been developed enough to envisage (at least in part) their
simple integration within a practical system. Clearly, some further investigations are
required to take this work forward and the next logical step would be to improve the
empirical rules with which the blade performance is predicted. A experimental
programme would also be of great advantage, for example in the study of how the
deviation
angle for a given blade row varies over time (operating hours) in a real
machine due to
ageing and fouling. This would allow better estimates of the stage work
during long term operation so that the optimiser could adapt to the slowly degrading
performance of the blades. Finally, it is important to verify the simulated results with
measured data, taken at the same optimal stator vane settings as given by the program.
This must be carried out before it can be
applied to a real application, although a limited
study of this nature is presented in chapter 6.