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

Abstract

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.

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Cited by in corpus (3)

• Synchronization of turbulence in channel flow
• Temporally sparse data assimilation for the small-scale reconstruction of turbulence
• Image and video compression of fluid flow data