Equation of state (EOS) data provide necessary information for accurate multiphysics modeling, which is necessary for fields such as inertial confinement fusion. Here, we suggest a neural network surrogate model of energy and entropy and use thermodynamic relationships to derive other necessary thermodynamic EOS quantities. We incorporate phase information into the model by training a phase classifier and using phase-specific regression models, which improves the modal prediction accuracy. Our model predicts energy values to 1% relative error and entropy to 3.5% relative error in a log-transformed space. Although sound speed predictions require further improvement, the derived pressure values are accurate within 10% relative error. Our results suggest that neural network models can effectively model EOS for inertial confinement fusion simulation applications.
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March 2023
Research Article|
March 14 2023
Neural network surrogate models for equations of state
Katherine L. Mentzer
;
Katherine L. Mentzer
a)
(Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing)
1
Lawrence Livermore National Laboratory
, P. O. Box 808, Livermore, California 94551-0808, USA
2
Institute for Computational and Mathematical Engineering, Stanford University
, 475 Via Ortega Suite B060, Stanford, California 94305, USA
a)Author to whom correspondence should be addressed: kmentzer@stanford.edu
Search for other works by this author on:
J. Luc Peterson
J. Luc Peterson
(Conceptualization, Funding acquisition, Investigation, Project administration, Resources, Supervision, Validation, Writing – review & editing)
1
Lawrence Livermore National Laboratory
, P. O. Box 808, Livermore, California 94551-0808, USA
Search for other works by this author on:
a)Author to whom correspondence should be addressed: kmentzer@stanford.edu
Phys. Plasmas 30, 032704 (2023)
Article history
Received:
September 16 2022
Accepted:
February 26 2023
Citation
Katherine L. Mentzer, J. Luc Peterson; Neural network surrogate models for equations of state. Phys. Plasmas 1 March 2023; 30 (3): 032704. https://doi.org/10.1063/5.0126708
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