Optimization of Aircraft Wake Alleviation Schemes Through an Evolution Strategy
Philippe Chatelain (Chair of Computational Science, ETH Zurich)
Mattia Gazzola (Chair of Computational Science, ETH Zurich)
Stefan Kern (Chair of Computational Science, ETH Zurich)
Petros Koumoutsakos (Chair of Computational Science, ETH Zurich)
We investigate schemes to accelerate the decay of aircraft trailing vortices. These structures are susceptible to several instabilities that lead to their eventual destruction. We employ an Evolution Strategy to design a lift distribution and a lift perturbation scheme that minimize the wake hazard as proposed by Crouch et al. (2001). The performance of a scheme is measured as the reduction of the mean rolling moment that would be induced on a following aircraft; it is computed by means of a Direct Numerical Simulation using a parallel vortex particle code. We find a configuration and a perturbation scheme characterized by an intermediate wavelength $\lambda \sim 4.64$, necessary to trigger medium wavelength instabilities between tail and flap vortices and subsequently amplify long wavelength modes.
Large Scale Simulations in CS&E, Parallel and Distributed Computing, Numerical Algorithms for CS&E, Optimization, Evolutionary optimization