The design of a new aero-engine compressor is a complex
task: design objectives are almost always conflicting, the
design space is large, nonlinear and highly constrained, and
the effects of some geometrical changes can be difficult to
predict.
Computational fluid dynamics (CFD) is now widely used
in real-world applications and especially in the design of turbomachinery.
However, the large design space and the time
required for the numerical simulation of the whole turbomachine
make the use of CFD in the early phases of the design
process infeasible: preliminary design relies on a number of
physical and empirical relations, still quite similar to those
used in the early history of turbomachinery design.
In this study, 87 independent parameters were used to
define the geometry of a 7-stage compressor, the performance
of which was evaluated using proprietary design
codes for mean-line, multi-stage analysis. The effects on
efficiency and surge margin of changing 44 design variables
were analysed and their optimal values found by means
of deterministic (gradient-based) and meta-heuristic (Tabu
Search [TS]) optimisation methods.
The results show clearly how the use of meta-heuristic
optimisation tools can improve the preliminary design of
turbomachinery, allowing a more thorough but still rapid
exploration of the design space to identify the most promising
regions that will then be verified and further analysed
with higher fidelity tools.
The results also reveal the impact of introducing various
constraints into the design process, highlighting the effects
of design decomposition
