Beckett Yx Zhou

A Discrete Adjoint Framework for Unsteady Aerodynamic and Aeroacoustic Optimization

In this paper, we present an unsteady aerodynamic and aeroacoustic optimization framework in which algorithmic differentiation (AD) is applied to the open-source multi-physics solver SU2 to obtain design sensitivities. An AD-based consistent discrete adjoint solver is developed which directly inherits the convergence properties of the primal flow solver due to the differentiation of the entire nonlinear fixed-point iterator. In addition, a coupled CFD-CAA far-field noise prediction framework using a permeable surface Ffowcs WilliamsHawkings approach is also developed. The resultant AD-based discrete adjoint solver is applied to both drag and noise minimization problems. The results suggest that the unsteady adjoint information provided by this AD-based discrete adjoint framework is accurate and robust, due to the algorithmic differentiation of the entire design chain including the dynamic mesh movement routine and various turbulence model, as well as the hybrid CFD-CAA model.

Noise Sources of Trailing-Edge Turbulence Controlled by Porous Media

To reduce trailing-edge noise an investigation of a noise reduction technique based on porous media is presented. Large-eddy simulations (LES) and solutions of the acoustic perturbation equations (APE) are used to investigate the trailing-edge noise of a flat plate at a freestream Mach number 0.06 and a Reynolds number of 135000 based on the chord length and the freestream velocity. The acoustic fields are determined in a three dimensional domain to include the impact of the spanwise coherence length on the noise generation. The porous surface at the trailing edge covers an area in the spanwise times streamwise direction of 512 times 800 in inner wall units. The two-point correlation of the velocity components shows that the modified velocity field by the porous surface has a smaller correlation length and a smooth variation of the turbulence length at the trailing edge. The porous surface reduces the overall sound pressure level from 3dB to 8dB. The sound spectra possess a strong tone at the Strouhal number of fh/U∞ = 0.2 and the broadband spectrum follows the −2 power slope of the frequency. Due to the uniform porous surface the peak of the tone was decreased by 10dB.

On the Adjoint-based Control of Trailing-Edge Turbulence and Noise Minimization via Porous Material

In this paper, we present a discrete adjoint-based optimization framework to obtain the optimal distribution of the porous material over the trailing edge of a 3-D flat plate. The near-body strength of the noise source generated by the unsteady turbulent flow field is computed using a high-fidelity large-eddy simulation (LES). The acoustic signal thus generated is then propagated to the far-field using the acoustic perturbation equations (APE). The design gradients are computed using the forward and reverse modes of algorithmic differentiation (AD). The increase of memory requirement in the reverse mode AD is alleviated by checkpointing. By optimally controlling the material porosity and permeability, it is possible to minimize the turbulence intensity responsible for noise generation at the trailing edge and thus significantly reduce the radiated noise. The optimal porous trailing-edge design achieves a noise reduction of up to 18dB.

A Discrete Adjoint Approach for Trailing-Edge Noise Minimization Using Porous Material

In this paper, we present a discrete adjoint-based optimization framework to obtain the optimal distribution of the porous material over the trailing edge of a 3-D flat plate. The near-body strength of the noise source generated by the unsteady turbulent flow field is computed using a high-fidelity large-eddy simulation (LES). By optimally controlling the material porosity and permeability, it is possible to minimize the turbulence intensity responsible for noise generation at the trailing edge and thus significantly reduce the radiated noise. We demonstrate, using a simple geometry as a first step, the efficacy of the discrete adjoint method in achieving minimum-noise design via optimal distribution of porous media, with future applications to aircraft high-lift devices.

Adjoint-based Trailing-Edge Noise Minimization using Porous Material

In this paper, we present a discrete adjoint-based optimization framework to obtain the optimal distribution of the porous material over the trailing edge of a 3-D flat plate. The near-body strength of the noise source generated by the unsteady turbulent flow field is computed using a high-fidelity large-eddy simulation (LES). The acoustic signal thus generated is then propagated to the far-field using the acoustic perturbation equations (APE). The design gradients are computed using the forward and reverse modes of automatic differentiation (AD). The increase of memory requirement in the reverse mode AD is alleviated by checkpointing. By optimally controlling the material porosity and permeability, it is possible to minimize the turbulence intensity responsible for noise generation at the trailing edge and thus significantly reduce the radiated noise. We demonstrate, using a simple geometry as a first step, the efficacy of the discrete adjoint method in achieving minimum-noise design via optimal distribution of porous media, with future applications to aircraft high-lift devices.

Towards Adjoint-Based Trailing-Edge Noise Minimization Using Porous Material

In this paper, we present a discrete adjoint-based optimization framework to obtain the optimal distribution of the porous material over the trailing edge of a 3-D flat plate. The near-body strength of the noise source generated by the unsteady turbulent flow field is computed using a high-fidelity large-eddy simulation (LES). The design gradients are computed using the forward and reverse modes of automatic differentiation (AD). The increase of memory requirement in the reverse mode AD is alleviated by checkpointing. We show, by optimally controlling the material porosity and permeability, it is possible to minimize the turbulence intensity responsible for noise generation at the trailing edge and thus significantly reduce the radiated noise.