Data compression for turbulence databases using spatio-temporal sub-sampling and local re-simulation

Zhao Wu, Tamer A. Zaki, Charles Meneveau

Published 2019-10-26Version 1

Motivated by specific data and accuracy requirements for building numerical databases of turbulent flows, data compression using spatio-temporal sub-sampling and local re-simulation is proposed. Numerical re-simulation experiments for decaying isotropic turbulence based on sub-sampled data are undertaken. The results and error analyses are used to establish parameter choices for sufficiently accurate sub-sampling and sub-domain re-simulation.