Noise Reduction through Chevron Nozzles via Multi-Point Optimization
Final Report Abstract
Hybrid LES/CAA simulations of a cold turbulent jet were performed for several nozzles with chevrons at a Reynolds number Re = 400,000 and a Mach number Ma = 0.9. The expected effect that chevrons increase the power spectral density for higher frequencies and decrease it for lower frequencies was confirmed. Furthermore, a novel direct-hybrid method has been developed and was used to predict jet noise from chevron nozzles. Results for two benchmark nozzles demonstrate its applicability and accuracy for jet noise problems. Moreover, the direct-hybrid method overcomes the deficiencies of standard hybrid CFD-CAA noise prediction methodologies. Thus, it constitutes an accurate and efficient candidate to perform large-scale simulations of three-dimensional turbulent aeroacoustic problems. The direct-hybrid method was used for the prediction of the thrust and the overall sound pressure level in multiple chevron shape optimization steps. The parametrization of the chevron nozzle geometry is restricted to two parameters describing the chevron tip angle and the chevron shape. A cost function based on the integrated acoustic pressure and a penalty term taking into account the thrust loss was formulated. Improved nozzle designs for the two independent parameters in terms of thrust-constrained noise reduction are identified. The overall acoustic benefit in the sideline direction is about 0.55dB in both cases. This investigation demonstrates the ability to perform thrust-constrained shape optimizations of individual chevron nozzles to reduce jet noise from aircraft engines. In accordance with the project objectives, the developed methodology forms the basis of a framework for optimal chevron designs. The results show the pronounced sensitivity of the flow field and the sound field. Their direct dependence requires a deeper analysis of the noise source regions and the effect of the chevron geometry variations. An improved understanding of the noise generating mechanisms and their locations will ease the development of noise reducing chevron nozzles with minimal performance penalties. The current analysis indicates that a more general approach should be pursued, i.e., not only the shape of the chevron should be allowed to be changed but also their solid surface. In other words, the solution space should be increased by also considering porous chevrons. It was shown that the computation of sensitivities lead to problems when applied to chaotic dynamical problems. Direct and adjoint sensitivity methods provide the correct results, however, their magnitude is too large to be useful. It should be emphasized, that this is not a problem of the sensitivity method used, but rather a problem of the definition of the objective function and the regularity of the derivatives. Methods for computing correct sensitivity derivatives of statistical quantities usually involve averaging over a large number of ensemble calculations. Another approach is the so-called Least-Squares-Shadowing (LSS) method. LSS has been shown to compute accurate sensitivities for a number of chaotic dynamical systems, including chaotic vortex shedding from a two-dimensional airfoil. In an related DFG Project it was shown that LSS can compute accurate gradients, albeit at the cost of requiring large amounts of memory and wall-clock time. A different approach can be the use of URANS as a surrogate model. Here, the sensitivities are computed on this lower fidelity model which are then used to optimize a objective function evaluated using scale-resolving methods. Steps in that direction were already taken by the development of an AD-based consistent discrete adjoint solver. In addition, a coupled 3-dimensional CFD-CAA far-field noise prediction framework using a permeable surface Ffowcs Williams-Hawkings approach in time domain was developed. In this study the optimization results obtained on the basis of 3D unsteady Reynolds-averaged Navier-Stokes equations (URANS simulations) were analyzed afterwards using scale-resolving simulations of higher fidelity.
Publications
- (2019) High-Performance Derivative Computations using CoDiPack. ACM Trans. Math. Softw. (ACM Transactions on Mathematical Software) 45 (4) 1–26
Sagebaum, Max; Albring, Tim; Gauger, Nicolas R.
(See online at https://doi.org/10.1145/3356900) - (2020) Dynamic load balancing for direct-coupled multiphysics simulations. Computers & Fluids 199 104437
Niemöller, Ansgar; Schlottke-Lakemper, Michael; Meinke, Matthias; Schröder, Wolfgang
(See online at https://doi.org/10.1016/j.compfluid.2020.104437) - „A consistent and robust discrete adjoint solver for the SU2 framework – validation and application“, Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol. 132, pp. 77–86, 2016
T. Albring, M. Sagebaum, N. R. Gauger
(See online at https://doi.org/10.1007/978-3-319-27279-5_7) - „Automated Generation of Performance Values for Algorithmic Differentiation“, Proc. Appl. Math. Mech., vol. 16 (1), pp. 863–864, 2016
M. Sagebaum, T. Albring and N.R. Gauger
(See online at https://doi.org/10.1002/pamm.201610420) - „Computational analysis of nozzle geometry variations for subsonic turbulent jets“, Comput. Fluids, vol. 136, pp. 467–484, 2016
M. O. Cetin, V. Pauz, M. Meinke, and W. Schröder
(See online at https://doi.org/10.1016/j.compfluid.2016.05.033) - „A fully coupled hybrid computational aeroacoustics method on hierarchical Cartesian meshes“, Comput. Fluids, vol. 144, pp. 137–153, 2017
M. Schlottke-Lakemper, H. Yu, S. Berger, M. Meinke, and W. Schröder
(See online at https://doi.org/10.1016/j.compfluid.2016.12.001) - „Assessment of the Recursive Projection Method for the Stabilization of Discrete Adjoint Solvers“, AIAA 2017-3664, 2017
T. Albring, T. Dick and N. R. Gauger
(See online at https://doi.org/10.2514/6.2017-3664) - „Fully turbulent discrete adjoint solver for non-ideal compressible flow applications“, Journal of the Global Power and Propulsion Society, vol. 1, pp. 252–270, 2017
S. Vitale, T. Albring, M. Pini, N. R. Gauger, P. Colonna
(See online at https://doi.org/10.22261/JGPPS.Z1FVOI) - „Numerical analysis of chevron nozzle noise“, 23rd AIAA/CEAS Aeroacoustics Conference, Denver, Colorado, June 5-9, 2017, AIAA 2017–3853, 2017
V. Pauz, A. Niemöller, M. Meinke, and W. Schröder
(See online at https://doi.org/10.2514/6.2017-3853) - „Reduction of Airframe Noise Components Using a Discrete Adjoint Approach“, AIAA 2017-3658, 2017
B. Y. Zhou, T. Albring, N. R. Gauger, C. Ilario, T. Economon and J. J. Alonso
(See online at https://doi.org/10.2514/6.2017-3658) - „A one-shot optimization framework with additional equality constraints applied to multi-objective aerodynamic shape optimization“, Optimization Methods and Software, vol. 33, no. 4–6, pp. 694–707, 2018
L. Kusch, T. Albring, A. Walther, N.R. Gauger
(See online at https://doi.org/10.1080/10556788.2018.1437158) - „Jet Noise Prediction for Chevron Nozzles using a Direct-Hybrid CFD/CAA Method“, in Tenth International Conference on Computational Fluid Dynamics (ICCFD10), Barcelona, Spain, July 9-13, 2018, ICCFD10–237, 2018
A. Niemöller, M. Schlottke-Lakemper, M. Meinke, and W. Schröder
- „Efficient parallelization for volume-coupled multiphysics simulations“, Comput. Methods. Appl. Mech. Eng., vol. 352, pp. 461–487, 2019
M. Schlottke-Lakemper, A. Niemöller, M. Meinke, and W. Schröder
(See online at https://doi.org/10.1016/j.cma.2019.04.032) - „Noise Reduction using a Direct-Hybrid CFD/CAA Method“, 25th AIAA/CEAS Aeroacoustics Conference, Delft, The Netherlands, May 20-24, 2019, no. 2019–2579, 2019
A. Niemöller, M. Meinke, W. Schröder, T. Albring, and N. Gauger
(See online at https://doi.org/10.2514/6.2019-2579)
