Generating synthetic turbulence with vector autoregression of proper orthogonal decomposition time coefficients
Stanly R, Du S, Xavier D, Perez A, Mukha T, Markidis S, Rezaeiravesh S, Schlatter P (2024)
Publication Type: Journal article
Publication year: 2024
Journal
Book Volume: 1000
Article Number: A83
Abstract
This study introduces vector autoregression (VAR) as a linear procedure that can be used for synthesizing turbulence time series over an entire plane, allowing them to be imposed as an efficient turbulent inflow condition in simulations requiring stationary and cross-correlated turbulence time series. VAR is a statistical tool for modelling and prediction of multivariate time series through capturing linear correlations between multiple time series. A Fourier-based proper orthogonal decomposition (POD) is performed on the two-dimensional (2-D) velocity slices from a precursor simulation of a turbulent boundary layer at a momentum thickness-based Reynolds number,. A subset of the most energetic structures in space are then extracted, followed by applying a VAR model to their complex time coefficients. It is observed that VAR models constructed using time coefficients of 5 and 30 most energetic POD modes per wavenumber (corresponding to and of turbulent kinetic energy, respectively) are able to make accurate predictions of the evolution of the velocity field at for infinite time. Moreover, the 2-D velocity fields from the POD-VAR when used as a turbulent inflow condition, gave a short development distance when compared with other common inflow methods. Since the VAR model can produce an infinite number of velocity planes in time, this enables reaching statistical stationarity without having to run an extremely long precursor simulation or applying ad hoc methods such as periodic time series.
Authors with CRIS profile
Involved external institutions
Royal Institute of Technology / Kungliga Tekniska Högskolan (KTH)
Sweden (SE)
King Abdullah University of Science and Technology (KAUST) / جامعة الملك عبد الله للعلوم و التقنية
Saudi Arabia (SA)
University of Manchester
United Kingdom (GB)
Sweden (SE)
King Abdullah University of Science and Technology (KAUST) / جامعة الملك عبد الله للعلوم و التقنية
Saudi Arabia (SA)
University of Manchester
United Kingdom (GB)
How to cite
APA:
Stanly, R., Du, S., Xavier, D., Perez, A., Mukha, T., Markidis, S.,... Schlatter, P. (2024). Generating synthetic turbulence with vector autoregression of proper orthogonal decomposition time coefficients. Journal of Fluid Mechanics, 1000. https://doi.org/10.1017/jfm.2024.1034
MLA:
Stanly, Ronith, et al. "Generating synthetic turbulence with vector autoregression of proper orthogonal decomposition time coefficients." Journal of Fluid Mechanics 1000 (2024).
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