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arXiv · 1909.08310

Actuation response model from sparse data for wall turbulence drag reduction

Daniel Fernex·Richard Semaan·Marian Albers·Pascal S. Meysonnat·Wolfgang Schröder·Bernd R. Noack
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Abstract

We compute, model, and predict drag reduction of an actuated turbulent boundary layer at a momentum thickness based Reynolds number of Reθ = 1000. The actuation is performed using spanwise traveling transversal surface waves parameterized by wavelength, amplitude, and period. The drag reduction for the set of actuation parameters is modeled using 71 large-eddy simulations (LES). This drag model allows to extrapolate outside the actuation domain for larger wavelengths and amplitudes. The modeling novelty is based on combining support vector regression for interpolation, a parameterized ridgeline leading out of the data domain, scaling from Tomiyama and Fukagata (2013), and a discovered self-similar structure of the actuation effect. The model yields high prediction accuracy outside the training data range.

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Daniel Fernex, Richard Semaan, Marian Albers, Pascal S. Meysonnat, Wolfgang Schröder, Bernd R. Noack. 2019-09-18. Actuation response model from sparse data for wall turbulence drag reduction. https://arxiv.org/abs/1909.08310

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