Adjoint-based Broadband Noise Minimization using Stochastic Noise Generation
Paper in proceedings, 2019

In this paper, we present an adjoint-based broadband noise minimization framework using stochastic noise generation (SNG). The SNG module is implemented in the open-source multi-physics solver suite SU2 and coupled with the existing Reynolds-averaged Navier-Stokes (RANS) to allow fast assessment of broadband noise sources. In addition, a discrete adjoint solver on the basis of algorithmic differentiation (AD) is developed for the coupled RANS-SNG system to enable efficient evaluation of broadband noise design sensitivities. The adjoint-based RANS-SNG framework developed in this work not only avoids the regularization problem that plagues the adjoint solutions for scale-resolving simulations, but also significantly lowers the computational cost and leads to a faster turn-around time for the initial design evaluation phase. Current results show that the RANS-SNG method can efficiently provide broadband noise level assessment for various configurations without resorting to computationally prohibitive scale-resolving simulations. Furthermore, current results also show that the design sensitivities computed by the AD-based coupled adjoint-RANS-SNG solver is highly accurate. Finally, shape optimizations performed on the basis of such coupled-sensitivity are shown to be effective in removing the broadband noise source near the trailing edge of a NACA0012 airfoil profile as well as around the side-edge of an isolated flap.

optimization

airframe noise

noise reduction

turbulence

aeroacoustics

transport

adjoint method

Author

Beckett Yx Zhou

Technische Universität Kaiserslautern

Nicolas R. Gauger

Technische Universität Kaiserslautern

Huadong Yao

Chalmers, Mechanics and Maritime Sciences, Fluid Dynamics

Peng Shia-Hui

Chalmers, Mechanics and Maritime Sciences, Fluid Dynamics

Lars Davidson

Chalmers, Mechanics and Maritime Sciences, Fluid Dynamics

AIAA 2019-2697

25th AIAA/CEAS Aeroacoustics Conference
, ,

Psychoacoustics of Flow-Induced Cabin Noise

Chalmers, 2019-01-01 -- 2019-12-31.

Areas of Advance

Transport

Subject Categories

Aerospace Engineering

Computational Mathematics

Fluid Mechanics and Acoustics

DOI

10.2514/6.2019-2697

More information

Created

5/31/2019