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Abstract
A parallel evolutionary strategy is coupled to a comprehensive analysis tool, RCAS, for rotorcraft optimization and design. The evolutionary structure is based on the Covariance Matrix Adaptation Evolution Strategy, CMA-ES, which has proven to be aviable optimization method for rotorcraft problems. Computational efficiency tests show that for a 8 core optimization, the parallel implementation of CMA-ES, pCMA-ES, can result in a significant speedup over the serial counterpart. The pCMA-ES is applied to two active device optimizations problems. First, a previously conducted uniform inflow optimization of an active trailing-edge flap deployment schedule is revisited and optimized using free-wake inflow. Next, the optimization of individual blade control, IBC, through an active pitch link is performed. Single harmonic and mixed harmonic inputs are optimized in amplitude and phase with fitness functions defined by rotor performance and hub vibrations. The optimization shows that mixed harmonic inputs can increase the performance gains compared to what single harmonics can accomplish. Furthermore, IBC is shown to be an effective method of controlling specific hub vibrations.

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  Parallel Evolutionary Optimization for Rotorcraft Design

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