Data compression for turbulence databases using spatiotemporal subsampling and local resimulation

Zhao Wu, Tamer A. Zaki, and Charles Meneveau
Phys. Rev. Fluids 5, 064607 – Published 15 June 2020

Abstract

Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatiotemporal subsampling and local resimulation is proposed. Numerical resimulation experiments for decaying isotropic turbulence based on subsampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate subsampling and subdomain resimulation.

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  • Received 26 October 2019
  • Accepted 19 May 2020

DOI:https://doi.org/10.1103/PhysRevFluids.5.064607

©2020 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
Fluid Dynamics

Authors & Affiliations

Zhao Wu, Tamer A. Zaki, and Charles Meneveau

  • Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA

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Issue

Vol. 5, Iss. 6 — June 2020

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