Algoritmo genético aplicado à otimização de aerofólio para diminuição de ruído aerodinâmico

Abstract

The noise produced by wind turbines which damages the health, has been a kind of barrier for the accommodation of those to society. This work uses the Brooks, Pope and Marcolini (BPM) model to noise prediction improved for the spatial description of the aerodynamic noise of the main lines of wind turbines produced, used in wind farms, or in urban areas (small-scale), and it was made the optimization of the profiles s809, s822, s834, FX 63-137, SD 2030 e SG 6043 blades in terms of noise levels and the blade performance. The main purpose of this optimization process is to reduce noise emission levels while it avoids large reductions in aerodynamic performance of the turbine by adjusting the geometry of the airfoil. The aerodynamic noise has two sources: inflow self-noise and self-noise. This, in turn, has four different mechanisms to manifest: turbulent boundary layer trailing edge noise, separation-stall noise, laminar boundary layer vortex shedding noise, trailing edge bluntness – vortex shedding noise. For this, it was used the NAFNoise program containing the BPM model and XFOIL code to provide the BPM data input and Genetic Algorithm to perform the optimization process. The optimized profiles fell around 1 dB in noise emission, reduction in aerodynamic performance and a corrugated conformation.