Abstract

Computational Fluid Dynamics (CFD) has been an important tool in aircraft design since the 1970s. Through CFD simulations, the aircraft industry has significantly reduced the need for wind tunnel and flight testing, but current design technologies use low-fidelity models of the turbulent airflow around aircrafts and under limited flight conditions. Removing these limitations requires high-fidelity modeling of turbulence, such as Large Eddy Simulations (LES) or hybrid RANS-LES.

Many of these high fidelity simulations exhibit chaotic dynamics. Sensitivity analysis of these simulations is required for efficiently using them for aircraft design with many design parameters. Algorithms for sensitivity analysis of these chaotic simulations, however, face many challenges. A new algorithm has been developed to overcome this issue. The algorithm, based on the Least Squares Shadowing formulation, finds a non-diverging solution of the linearized governing equation. We will share the recent experience of applying this algorithm to several flow simulations. The algorithm can benefit design optimization, error estimation, adaptive meshing, and uncertainty quantification of chaotic, high fidelity turbulent flow simulations.

Bio

Qiqi Wang got his BS in mathematics from University of Science and Technology at Hefei, China. He then got his PhD in Computational and Mathematical Engineering at Stanford, under the supervision of Parviz Moin and Gianluca Iaccarino. From 2009 to 2015, he was an assistant professor of Aeronautics and Astronautics at MIT. Since 2015, he has been an associate professor in the same department.

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