Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session F01: Nonlinear Dynamics: Bifurcations & Chaos
8:00 AM–9:57 AM,
Monday, November 19, 2018
Georgia World Congress Center
Room: B201
Chair: Spencer Smith, Mt. Holyoke College
Abstract ID: BAPS.2018.DFD.F01.3
Abstract: F01.00003 : Chaotic sensitivity analysis of noise at chevron nozzle exits
8:26 AM–8:39 AM
Presenter:
Nisha Chandramoorthy
(Massachusetts Inst of Tech-MIT)
Authors:
Nisha Chandramoorthy
(Massachusetts Inst of Tech-MIT)
Qiqi Wang
(Massachusetts Inst of Tech-MIT)
Zhong-Nan Wang
(University of Cambridge)
The computation of sensitivities of turbulent fluid flows to input parameter perturbations is important for gradient-based multi-disciplinary design optimization, uncertainty quantification, mesh adaptation and so on. Since linearized perturbation equations are unstable in chaotic systems, conventional adjoint sensitivity analysis methods that are successful with steady RANS solutions, fail in the case of high-fidelity chaotic numerical simulations such as LES. At present, some potential candidates for sensitivity computation in chaotic systems are shadowing-based and ensemble-based methods. Ensemble-based methods exhibit poor rate of convergence and are hence impractical for eddy-resolving simulations; Shadowing-based methods are not guaranteed to converge since the computed shadowing trajectories may be rare trajectories that do not correspond to the average dynamics of the fluid system. We propose an alternative called Space-Split-Sensitivity (S3) computation that provably converges to the mean response of a chaotic system to parameter perturbations. We demonstrate that the new algorithm enables optimization of chevron nozzle geometry to reduce the noise produced by jet engines.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.F01.3
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