Noise Reduction through Chevron Nozzles via Multi-Point Optimization

• Applicants: Professor Dr. Nicolas R. Gauger; Professor Dr.-Ing. Wolfgang Schröder
• Subject Area: Fluid Mechanics
• Term: from 2014 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 247310774

Despite the progressive introduction of high-bypass-ratio engines and Chevrons, which have a characteristic sawtooth-like shape at the trailing edge of the engine nozzle, jet noise still is a significant source of aircraft engine noise. Within the proposed project the use of chevron nozzles for such noise reduction is investigated. Chevrons can reduce the noise level during aircraft takeoff, but also can lead to thrust loss during both takeoff and cruise flight. Therefore, chevrons have to be optimized to maximize noise reduction at takeoff and avoid thrust reduction under cruise flight and takeoff conditions. To address this issue, it is proposed to develop a novel multi-point thrust-constrained noise minimization framework for optimal chevron designs, coupling a high-fidelity aeroacoustic solver withstate-of-the-art gradient-based optimization algorithms. An adjoint will be implemented for the aeroacoustic solver by using automatic differentiation in reverse mode such that gradient information of thenoise level with respect to the chevron shape will be available. Most importantly, the chevron shapes are optimized such that their far-field noise is minimized and a penalty term incorporated into the cost function avoids thrust loss. Furthermore, the adjoint will be used for an analysis to identify those sound sources, which are responsible for the major noise production in the coaxial jet from the aircraft engine and which are modified by the chevrons. The results will yield a better understanding of the impact that the various chevron nozzles have on both the noise and thrust productions at different aircraft operations and provide a first methodological basis for performing optimal chevron designs beyond the experimental cut-and-try approach.

• DFG Programme: Research Grants
• Participating Person: Dr.-Ing. Matthias Meinke