Compression of magnetohydrodynamic simulation data using singular value decomposition

Journal Article · Thu Mar 01 04:00:00 EST 2007 · Journal of Computational Physics

DOI:https://doi.org/10.1016/j.jcp.2006.07.022· OSTI ID:20991563

Castillo Negrete, D del ^[1]; Hirshman, S P ^[1]; Spong, D A ^[1]; D'Azevedo, E F ^[1]

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1. Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

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.

• OSTI ID: 20991563
• 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

71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
ALGORITHMS
APPROXIMATIONS
COMPUTERIZED SIMULATION
DATA TRANSMISSION
EQUATIONS
INTERPOLATION
MAGNETIC FIELDS
MAGNETOHYDRODYNAMICS
NONLINEAR PROBLEMS
ORBITS
PERFORMANCE
THREE-DIMENSIONAL CALCULATIONS