Multilevel-Multiphase Optimization of Composite Rotor Blade with Surrogate Model
Jieun Ku, Vitali V. Volovoi, Dewey H. Hodges · 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference · 2007
Issues raised in the authors’ previous works are further explored, introducing a multilevel, multiphase approach with a surrogate model. Previous approaches did not show a clear indication of the communication between global and local levels because both levels reached the optimal solution without iteration between levels. To guarantee the need for an iterative process, the blade model was changed, and surrogate models were embedded in the procedure to ensure the communication between global and local levels. Concomitantly, values of the design variables were forced to stay in the feasible design space. Candidate surrogate models include Kriging, and linear and quadratic Response Surface Regression (RSM). These models are compared and the most suitable surrogate model was adopted to finalize the iterative process of the methodology. The new example is the Elastic Articulation (EA) rotor system which is the rotor system of the Generic Georgia Tech Helicopter. The EA rotor is a soft-in-plane bearingless rotor with 10% effective flapping hinge offset and forward sweep. To ensure the dynamic stability of such a system, the methodology utilizes high-fidelity blade structural analysis tools DYMORE and VABS, which reduces the computation time by allowing hierarchical decomposition of the problem. This separates the local (cross-sectional) sub-problem, with constraints on local quantities as maximum stresses, from the global optimization, with constraints on global parameters such as on the Autorotation Index (AI). The procedure is implemented using MATLAB as the overall optimizer.