Compression of Magnetohydrodynamic Simulation Data Using Singular Value Decomposition

Journal Article · Sun Oct 01 04:00:00 EDT 2006 · Journal of Computational Physics

OSTI ID:931693

Del-Castillo-Negrete, Diego B ^[1]; Hirshman, Steven Paul ^[1]; Spong, Donald A ^[1]; D'Azevedo, Ed F ^[1]

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1. ORNL

Numerical calculations of magnetic and flow fields in magnetohydrodynamic (MHD) simulations can result in extensive data sets. Particle-based calculations in these MHD fields, needed to provide closure relations for the MHD equations, will require communication of this data to multiple processors and rapid interpolation at numerous particle orbit positions. To facilitate this analysis it is advantageous to compress the data using singular value decomposition (SVD, or principal orthogonal decomposition, POD) methods. As an example of the compression technique, SVD is applied to magnetic field data arising from a dynamic nonlinear MHD code. The performance of the SVD compression algorithm is analyzed by calculating Poincare plots for electron orbits in a three-dimensional magnetic field and comparing the results with uncompressed data.

• Research Organization: Oak Ridge National Laboratory (ORNL)
• Sponsoring Organization: ORNL LDRD Director's R&D
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 931693
• Journal Information: Journal of Computational Physics, Journal Name: Journal of Computational Physics Journal Issue: 1 Vol. 222; ISSN JCTPAH; ISSN 0021-9991
• Country of Publication: United States
• Language: English

Related Subjects

75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY
ALGORITHMS
CLOSURES
COMMUNICATIONS
COMPRESSION
ELECTRONS
INTERPOLATION
MAGNETIC FIELDS
MAGNETOHYDRODYNAMICS
PERFORMANCE
SIMULATION