Wavelet-based data compression for flow simulation on block-structured Cartesian mesh

Ryotaro Sakai, Daisuke Sasaki, Shigeru Obayashi, Kazuhiro Nakahashi

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


A data compression method based on image encoding techniques is presented for a flow simulation data set. An input flow field data set is converted into the octree structure by discrete wavelet transform, and then quantized finely or coarsely depending on its importance in the flow field. Embedded zerotree wavelet encoding as the image encoding technique and entropy encoding reduce the data size by making use of the octree structure created previously. The present compression method is incorporated in a block-structured Cartesian mesh method called Building-Cube method. The Building-Cube method gives not only good performance in the flow simulation but also consistency with the embedded zerotree wavelet encoding in the data compression. Three compression cases for incompressible and compressible flow simulations, including a large-scale simulation with O(10 8) mesh points, demonstrate that the present compression method gives both high compression ratios and good qualities of compressed data.

Original languageEnglish
Pages (from-to)462-476
Number of pages15
JournalInternational Journal for Numerical Methods in Fluids
Issue number5
Publication statusPublished - 2013 Oct 20


  • Cartesian mesh
  • Compressible flow
  • Data compression
  • Embedded zerotree wavelet
  • Incompressible flow
  • Wavelet transform


Dive into the research topics of 'Wavelet-based data compression for flow simulation on block-structured Cartesian mesh'. Together they form a unique fingerprint.

Cite this