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Title: Characterizing magnetized plasmas with dynamic mode decomposition

Abstract

Accurate and efficient plasma models are essential to understand and control experimental devices. Existing magnetohydrodynamic or kinetic models are nonlinear and computationally intensive and can be difficult to interpret, while often only approximating the true dynamics. In this work, data-driven techniques recently developed in the field of fluid dynamics are leveraged to develop interpretable reduced-order models of plasmas that strike a balance between accuracy and efficiency. In particular, dynamic mode decomposition (DMD) is used to extract spatio-temporal magnetic coherent structures from the experimental and simulation datasets of the helicity injected torus with steady inductive (HIT-SI) experiment. Three-dimensional magnetic surface probes from the HIT-SI experiment are analyzed, along with companion simulations with synthetic internal magnetic probes. A number of leading variants of the DMD algorithm are compared, including the sparsity-promoting and optimized DMD. Optimized DMD results in the highest overall prediction accuracy, while sparsity-promoting DMD yields physically interpretable models that avoid overfitting. These DMD algorithms uncover several coherent magnetic modes that provide new physical insights into the inner plasma structure. These modes were subsequently used to discover a previously unobserved three-dimensional structure in the simulation, rotating at the second injector harmonic. Finally, using data from probes at experimentally accessible locations, DMDmore » identifies a resistive kink mode, a ubiquitous instability seen in magnetized plasmas.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [1]
  1. Univ. of Washington, Seattle, WA (United States)
  2. CTFusion Inc., Seattle, WA (United States)
  3. Univ. of Washington, Seattle, WA (United States); Columbia Univ., New York, NY (United States)
Publication Date:
Research Org.:
Univ. of Washington, Seattle, WA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Fusion Energy Sciences (FES)
OSTI Identifier:
1608227
Alternate Identifier(s):
OSTI ID: 1602583
Grant/Contract Number:  
SC0016256; FG02-96ER54361
Resource Type:
Accepted Manuscript
Journal Name:
Physics of Plasmas
Additional Journal Information:
Journal Volume: 27; Journal Issue: 3; Journal ID: ISSN 1070-664X
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; 97 MATHEMATICS AND COMPUTING

Citation Formats

Kaptanoglu, A. A., Morgan, K. D., Hansen, C. J., and Brunton, S. L. Characterizing magnetized plasmas with dynamic mode decomposition. United States: N. p., 2020. Web. doi:10.1063/1.5138932.
Kaptanoglu, A. A., Morgan, K. D., Hansen, C. J., & Brunton, S. L. Characterizing magnetized plasmas with dynamic mode decomposition. United States. doi:https://doi.org/10.1063/1.5138932
Kaptanoglu, A. A., Morgan, K. D., Hansen, C. J., and Brunton, S. L. Tue . "Characterizing magnetized plasmas with dynamic mode decomposition". United States. doi:https://doi.org/10.1063/1.5138932. https://www.osti.gov/servlets/purl/1608227.
@article{osti_1608227,
title = {Characterizing magnetized plasmas with dynamic mode decomposition},
author = {Kaptanoglu, A. A. and Morgan, K. D. and Hansen, C. J. and Brunton, S. L.},
abstractNote = {Accurate and efficient plasma models are essential to understand and control experimental devices. Existing magnetohydrodynamic or kinetic models are nonlinear and computationally intensive and can be difficult to interpret, while often only approximating the true dynamics. In this work, data-driven techniques recently developed in the field of fluid dynamics are leveraged to develop interpretable reduced-order models of plasmas that strike a balance between accuracy and efficiency. In particular, dynamic mode decomposition (DMD) is used to extract spatio-temporal magnetic coherent structures from the experimental and simulation datasets of the helicity injected torus with steady inductive (HIT-SI) experiment. Three-dimensional magnetic surface probes from the HIT-SI experiment are analyzed, along with companion simulations with synthetic internal magnetic probes. A number of leading variants of the DMD algorithm are compared, including the sparsity-promoting and optimized DMD. Optimized DMD results in the highest overall prediction accuracy, while sparsity-promoting DMD yields physically interpretable models that avoid overfitting. These DMD algorithms uncover several coherent magnetic modes that provide new physical insights into the inner plasma structure. These modes were subsequently used to discover a previously unobserved three-dimensional structure in the simulation, rotating at the second injector harmonic. Finally, using data from probes at experimentally accessible locations, DMD identifies a resistive kink mode, a ubiquitous instability seen in magnetized plasmas.},
doi = {10.1063/1.5138932},
journal = {Physics of Plasmas},
number = 3,
volume = 27,
place = {United States},
year = {2020},
month = {3}
}

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