An approach to support the computational aerodynamic design process is presented
and demonstrated through the application of a novel multi-objective variant of
the Tabu Search optimization algorithm for continuous problems to the
aerodynamic design optimization of turbomachinery blades. The aim is to improve
the performance of a specific stage and ultimately of the whole engine. The
integrated system developed for this purpose is described. This combines the
optimizer with an existing geometry parameterization scheme and a well-
established CFD package. The system’s performance is illustrated through case
studies – one two-dimensional, one three-dimensional – in which flow
characteristics important to the overall performance of turbomachinery blades
are optimized. By showing the designer the trade-off surfaces between the
competing objectives, this approach provides considerable insight into the
design space under consideration and presents the designer with a range of
different Pareto-optimal designs for further consideration. Special emphasis is
given to the dimensionality in objective function space of the optimization
problem, which seeks designs that perform well for a range of flow performance
metrics. The resulting compressor blades achieve their high performance by
exploiting complicated physical mechanisms successfully identified through the
design process. The system can readily be run on parallel computers,
substantially reducing wall-clock run times – a significant benefit when
tackling computationally demanding design problems. Overall optimal performance
is offered by compromise designs on the Pareto trade-off surface revealed
through a true multi-objective design optimization test case. Bearing in mind
the continuing rapid advances in computing power and the benefits discussed,
this approach brings the adoption of such techniques in real-world engineering
design practice a ste