Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation
We present a new analysis methodology that allows for the self-consistent integration of multiple diagnostics including nuclear measurements, x-ray imaging, and x-ray power detectors to determine the primary stagnation parameters, such as temperature, pressure, stagnation volume, and mix fraction in...
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| Veröffentlicht in: | Physics of plasmas 2022-05, Vol.29 (5) |
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| creator | Knapp, P. F. Glinsky, M. E. Schaeuble, M. A. Jennings, C. A. Evans, M. Gunning, J. Awe, T. J. Chandler, G. A. Geissel, M. Gomez, M. R. Hahn, K. D. Hansen, S. B. Harding, E. C. Harvey-Thompson, A. J. Humane, S. Klein, B. T. Mangan, M. Nagayama, T. Porwitzky, A. J. Ruiz, D. E. Schmit, P. F. Slutz, S. A. Smith, I. C. Weis, M. R. Yager-Elorriaga, D. A. Ampleford, D. J. Beckwith, K. Mattsson, T. R. Peterson, K. J. Sinars, D. B. |
| description | We present a new analysis methodology that allows for the self-consistent integration of multiple diagnostics including nuclear measurements, x-ray imaging, and x-ray power detectors to determine the primary stagnation parameters, such as temperature, pressure, stagnation volume, and mix fraction in magnetized liner inertial fusion (MagLIF) experiments. The analysis uses a simplified model of the stagnation plasma in conjunction with a Bayesian inference framework to determine the most probable configuration that describes the experimental observations while simultaneously revealing the principal uncertainties in the analysis. We validate the approach by using a range of tests including analytic and three-dimensional MHD models. An ensemble of MagLIF experiments is analyzed, and the generalized Lawson criterion χ is estimated for all experiments. |
| doi_str_mv | 10.1063/5.0087115 |
| format | Article |
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F. ; Glinsky, M. E. ; Schaeuble, M. A. ; Jennings, C. A. ; Evans, M. ; Gunning, J. ; Awe, T. J. ; Chandler, G. A. ; Geissel, M. ; Gomez, M. R. ; Hahn, K. D. ; Hansen, S. B. ; Harding, E. C. ; Harvey-Thompson, A. J. ; Humane, S. ; Klein, B. T. ; Mangan, M. ; Nagayama, T. ; Porwitzky, A. J. ; Ruiz, D. E. ; Schmit, P. F. ; Slutz, S. A. ; Smith, I. C. ; Weis, M. R. ; Yager-Elorriaga, D. A. ; Ampleford, D. J. ; Beckwith, K. ; Mattsson, T. R. ; Peterson, K. J. ; Sinars, D. B.</creator><creatorcontrib>Knapp, P. F. ; Glinsky, M. E. ; Schaeuble, M. A. ; Jennings, C. A. ; Evans, M. ; Gunning, J. ; Awe, T. J. ; Chandler, G. A. ; Geissel, M. ; Gomez, M. R. ; Hahn, K. D. ; Hansen, S. B. ; Harding, E. C. ; Harvey-Thompson, A. J. ; Humane, S. ; Klein, B. T. ; Mangan, M. ; Nagayama, T. ; Porwitzky, A. J. ; Ruiz, D. E. ; Schmit, P. F. ; Slutz, S. A. ; Smith, I. C. ; Weis, M. R. ; Yager-Elorriaga, D. A. ; Ampleford, D. J. ; Beckwith, K. ; Mattsson, T. R. ; Peterson, K. J. ; Sinars, D. 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F.</creatorcontrib><creatorcontrib>Glinsky, M. E.</creatorcontrib><creatorcontrib>Schaeuble, M. A.</creatorcontrib><creatorcontrib>Jennings, C. A.</creatorcontrib><creatorcontrib>Evans, M.</creatorcontrib><creatorcontrib>Gunning, J.</creatorcontrib><creatorcontrib>Awe, T. J.</creatorcontrib><creatorcontrib>Chandler, G. A.</creatorcontrib><creatorcontrib>Geissel, M.</creatorcontrib><creatorcontrib>Gomez, M. R.</creatorcontrib><creatorcontrib>Hahn, K. D.</creatorcontrib><creatorcontrib>Hansen, S. B.</creatorcontrib><creatorcontrib>Harding, E. C.</creatorcontrib><creatorcontrib>Harvey-Thompson, A. J.</creatorcontrib><creatorcontrib>Humane, S.</creatorcontrib><creatorcontrib>Klein, B. T.</creatorcontrib><creatorcontrib>Mangan, M.</creatorcontrib><creatorcontrib>Nagayama, T.</creatorcontrib><creatorcontrib>Porwitzky, A. J.</creatorcontrib><creatorcontrib>Ruiz, D. E.</creatorcontrib><creatorcontrib>Schmit, P. F.</creatorcontrib><creatorcontrib>Slutz, S. A.</creatorcontrib><creatorcontrib>Smith, I. C.</creatorcontrib><creatorcontrib>Weis, M. R.</creatorcontrib><creatorcontrib>Yager-Elorriaga, D. A.</creatorcontrib><creatorcontrib>Ampleford, D. J.</creatorcontrib><creatorcontrib>Beckwith, K.</creatorcontrib><creatorcontrib>Mattsson, T. R.</creatorcontrib><creatorcontrib>Peterson, K. J.</creatorcontrib><creatorcontrib>Sinars, D. B.</creatorcontrib><title>Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation</title><title>Physics of plasmas</title><description>We present a new analysis methodology that allows for the self-consistent integration of multiple diagnostics including nuclear measurements, x-ray imaging, and x-ray power detectors to determine the primary stagnation parameters, such as temperature, pressure, stagnation volume, and mix fraction in magnetized liner inertial fusion (MagLIF) experiments. The analysis uses a simplified model of the stagnation plasma in conjunction with a Bayesian inference framework to determine the most probable configuration that describes the experimental observations while simultaneously revealing the principal uncertainties in the analysis. We validate the approach by using a range of tests including analytic and three-dimensional MHD models. 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F. ; Glinsky, M. E. ; Schaeuble, M. A. ; Jennings, C. A. ; Evans, M. ; Gunning, J. ; Awe, T. J. ; Chandler, G. A. ; Geissel, M. ; Gomez, M. R. ; Hahn, K. D. ; Hansen, S. B. ; Harding, E. C. ; Harvey-Thompson, A. J. ; Humane, S. ; Klein, B. T. ; Mangan, M. ; Nagayama, T. ; Porwitzky, A. J. ; Ruiz, D. E. ; Schmit, P. F. ; Slutz, S. A. ; Smith, I. C. ; Weis, M. R. ; Yager-Elorriaga, D. A. ; Ampleford, D. J. ; Beckwith, K. ; Mattsson, T. R. ; Peterson, K. J. ; Sinars, D. 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C.</au><au>Weis, M. R.</au><au>Yager-Elorriaga, D. A.</au><au>Ampleford, D. J.</au><au>Beckwith, K.</au><au>Mattsson, T. R.</au><au>Peterson, K. J.</au><au>Sinars, D. B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation</atitle><jtitle>Physics of plasmas</jtitle><date>2022-05</date><risdate>2022</risdate><volume>29</volume><issue>5</issue><issn>1070-664X</issn><eissn>1089-7674</eissn><coden>PHPAEN</coden><abstract>We present a new analysis methodology that allows for the self-consistent integration of multiple diagnostics including nuclear measurements, x-ray imaging, and x-ray power detectors to determine the primary stagnation parameters, such as temperature, pressure, stagnation volume, and mix fraction in magnetized liner inertial fusion (MagLIF) experiments. 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| fulltext | fulltext |
| identifier | ISSN: 1070-664X |
| ispartof | Physics of plasmas, 2022-05, Vol.29 (5) |
| issn | 1070-664X 1089-7674 |
| language | eng |
| recordid | cdi_osti_scitechconnect_1868390 |
| source | AIP Journals Complete; Alma/SFX Local Collection |
| subjects | Bayesian analysis Experiments Inertial fusion (reactor) Performance measurement Plasma physics Stagnation Statistical inference Three dimensional analysis Three dimensional models X ray imagery |
| title | Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation |
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