1 research outputs found
Exploring the fitness landscape of a realistic turbofan rotor blade optimization
Aerodynamic shape optimization has established itself as a valuable tool in
the engineering design process to achieve highly efficient results. A central
aspect for such approaches is the mapping from the design parameters which
encode the geometry of the shape to be improved to the quality criteria which
describe its performance. The choices to be made in the setup of the
optimization process strongly influence this mapping and thus are expected to
have a profound influence on the achievable result. In this work we explore the
influence of such choices on the effects on the shape optimization of a
turbofan rotor blade as it can be realized within an aircraft engine design
process. The blade quality is assessed by realistic three dimensional
computational fluid dynamics (CFD) simulations.
We investigate the outcomes of several optimization runs which differ in
various configuration options, such as optimization algorithm, initialization,
number of degrees of freedom for the parametrization. For all such variations,
we generally find that the achievable improvement of the blade quality is
comparable for most settings and thus rather insensitive to the details of the
setup.
On the other hand, even supposedly minor changes in the settings, such as
using a different random seed for the initialization of the optimizer
algorithm, lead to very different shapes. Optimized shapes which show
comparable performance usually differ quite strongly in their geometries over
the complete blade.
Our analyses indicate that the fitness landscape for such a realistic
turbofan rotor blade optimization is highly multi-modal with many local optima,
where very different shapes show similar performance