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.
Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation
Note: This paper is part of the Special Collection: Papers from the 63rd Annual Meeting of the APS Division of Plasma Physics.Note: Paper BI1 4, Bull. Am. Phys. Soc. 66 (2021).
P. F. Knapp, M. E. Glinsky, M. A. Schaeuble, C. A. Jennings, M. Evans, J. Gunning, T. J. Awe, G. A. Chandler, M. Geissel, M. R. Gomez, K. D. Hahn, S. B. Hansen, E. C. Harding, A. J. Harvey-Thompson, S. Humane, B. T. Klein, M. Mangan, T. Nagayama, A. J. Porwitzky, D. E. Ruiz, P. F. Schmit, S. A. Slutz, I. C. Smith, M. R. Weis, D. A. Yager-Elorriaga, D. J. Ampleford, K. Beckwith, T. R. Mattsson, K. J. Peterson, D. B. Sinars; Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation. Phys. Plasmas 1 May 2022; 29 (5): 052711. https://doi.org/10.1063/5.0087115
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