Mallat Scattering Transformation based surrogate for Magnetohydrodynamics
Mallat Scattering Transformation based surrogate for Magnetohydrodynamics
About this item
Full title
Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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More information
Scope and Contents
Contents
A Machine and Deep Learning (MLDL) methodology is developed and applied to give a high fidelity, fast surrogate for 2D resistive MagnetoHydroDynamic (MHD) simulations of Magnetic Liner Inertial Fusion (MagLIF) implosions. The resistive MHD code GORGON is used to generate an ensemble of implosions with different liner aspect ratios, initial gas preh...
Alternative Titles
Full title
Mallat Scattering Transformation based surrogate for Magnetohydrodynamics
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_osti_scitechconnect_1970385
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_osti_scitechconnect_1970385
Other Identifiers
ISSN
0178-7675
E-ISSN
1432-0924
DOI
10.1007/s00466-023-02302-1
