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).
Highlights
The field of computational fluid dynamics (CFD) is data intensive, for highfidelity simulations
In the present work we propose a lossy data compression algorithm, with which we have obtained high levels of acceptable compression ratios for the turbulent flow through a straight pipe and the turbulent boundary layers developing around a wing section
The discrete Legendre transform (DLT) based truncation method outperforms discrete Chebyshev transform (DCT), which could compress up to a maximum of 70%. These results were consistent with the spectral analysis, which in addition reflected that downsampling significantly affects the smallest scales in the power-spectral density distributions
Summary
The field of computational fluid dynamics (CFD) is data intensive, for highfidelity simulations. The purpose is to identify bounds within which computational data can be reduced without affecting the ulterior postprocessing, i.e., determination of relevant flow quantities such as turbulence statistics, power-spectral densities or coherent structures.
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