Publications Details

Estimation of stagnation performance metrics in magnetized liner inertial fusion experiments using Bayesian data assimilation

Knapp, Patrick K.; Glinsky, Michael E.; Schaeuble, Marc-Andre S.; Jennings, Christopher A.; Evans, Matthew; Gunning, James; Awe, Thomas J.; Chandler, Gordon A.; Geissel, Matthias G.; Gomez, Matthew R.; Hahn, Kelly D.; Hansen, Stephanie B.; Harding, Eric H.; Harvey-Thompson, Adam J.; Humane, Shailja; Klein, Brandon T.; Mangan, Michael M.; Nagayama, Taisuke N.; Porwitzky, Andrew J.; Ruiz, Daniel E.; Schmit, Paul F.; Slutz, Stephen A.; Smith, Ian C.; Weis, Matthew R.; Yager-Elorriaga, David A.; Ampleford, David A.; Beckwith, Kristian B.; Mattsson, Thomas M.; Peterson, Kyle J.; Sinars, Daniel S.

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.