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Wavelet‐based data compression for flow simulation on block‐structured Cartesian mesh
Author(s) -
Sakai Ryotaro,
Sasaki Daisuke,
Obayashi Shigeru,
Nakahashi Kazuhiro
Publication year - 2013
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.3808
Subject(s) - octree , data compression , wavelet , image compression , computer science , arithmetic coding , algorithm , compression ratio , compression (physics) , computer vision , mathematics , artificial intelligence , image processing , context adaptive binary arithmetic coding , image (mathematics) , engineering , materials science , composite material , internal combustion engine , automotive engineering
SUMMARY 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. Copyright © 2013 John Wiley & Sons, Ltd.