Aerodynamic shape optimization of rotary wing aircraft components using advanced multiobjective evolutionary algorithms
Claudio Comis Da Ronco · 2012
The aim of this Doctoral Thesis, sponsored by AgustaWestland, is the design and development of a multi-objective optimization procedure that involves the application of the GeDEA-II, a powerful and time-saving evolutionary algorithm recently developed by the author at the University of Padova, able to perform multi-objective optimization analyses with the general approach of the Pareto frontier search. When compared to other state-of-the-art multi-objective evolutionary algorithms, it features novel crossover and mutation operators, and demonstrated superior performance. This optimizer supervises an automatic optimization loop involving the CFD commercial and free, open source solvers, respectively Fluent® and OpenFOAM®. Altair Hyperworks package is chosen as the free-form-deformation parameterization engine. The test cases chosen to demonstrate the strength of the procedure implemented concern the aerodynamic optimization of the AgustaWestland ERICA nose region, and the optimization of the intake 1 of the AW101 helicopter, that is really challenging problems from both the engineering and the industrial point of view. Starting from the the geometry elaboration and proceeding to the results discussion, each step of the optimization procedure is described in details, with particular focus on the automatic optimization loop, directly programmed by the author in both UNIX/Linux and Windows environments. The results obtained surely demonstrate the effectiveness of the multiobjective approach chosen to carry out this work. Furthermore, some suggestions for future improvements and developments are provided, with the purpose to increase the strength of the discussed multi-objective optimization tool.