Lossy Data Compression Effects on Wall-bounded Turbulence: Bounds on Data Reduction

Otero E, Vinuesa R, Marin O, Laure E, Schlatter P (2018)

Publication Type: Journal article

Publication year: 2018

Journal

Flow Turbulence and Combustion Springer Verlag (Germany)

Book Volume: 101

Pages Range: 365-387

Journal Issue: 2

DOI: 10.1007/s10494-018-9923-5

Abstract

Postprocessing and storage of large data sets represent one of the main computational bottlenecks in computational fluid dynamics. We assume that the accuracy necessary for computation is higher than needed for postprocessing. Therefore, in the current work we assess thresholds for data reduction as required by the most common data analysis tools used in the study of fluid flow phenomena, specifically wall-bounded turbulence. These thresholds are imposed a priori by the user in L2-norm, and we assess a set of parameters to identify the minimum accuracy requirements. The method considered in the present work is the discrete Legendre transform (DLT), which we evaluate in the computation of turbulence statistics, spectral analysis and resilience for cases highly-sensitive to the initial conditions. Maximum acceptable compression ratios of the original data have been found to be around 97%, depending on the application purpose. The new method outperforms downsampling, as well as the previously explored data truncation method based on discrete Chebyshev transform (DCT).

Authors with CRIS profile

Philipp Schlatter

Involved external institutions

Argonne National Laboratory US United States (USA) (US) Royal Institute of Technology / Kungliga Tekniska Högskolan (KTH) SE Sweden (SE)

How to cite

APA:

Otero, E., Vinuesa, R., Marin, O., Laure, E., & Schlatter, P. (2018). Lossy Data Compression Effects on Wall-bounded Turbulence: Bounds on Data Reduction. Flow Turbulence and Combustion, 101(2), 365-387. https://doi.org/10.1007/s10494-018-9923-5

MLA:

Otero, Evelyn, et al. "Lossy Data Compression Effects on Wall-bounded Turbulence: Bounds on Data Reduction." Flow Turbulence and Combustion 101.2 (2018): 365-387.

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