Pre-shot predictions and post-shot analysis of high yield implosions on the National Ignition Facility using LANL's xRAGE code

ORAL

Abstract

High yield layered capsule implosions on the National Ignition Facility now routinely demonstrate gain (yield greater than input laser energy) [1]. Nevertheless, predicting the outcome of experiments remains challenging due to a high sensitivity to capsule quality [2] and drive asymmetry [3], particularly in this regime where strong alpha heating amplifies these and other sensitivities [4]. The xRAGE [5,6] code is now being used to provide pre-shot predictions for many of these implosions, supplementing HYDRA [7] and CogSim [8] predictions. xRAGE provides a unique capability to easily, routinely, and accurately model capsule defects and engineering features like the fill tube. We will discuss modeling strategies, results, and lessons learned from the predictions that have been performed so far.

[1] Abu-Shawareb et al, Phys Rev Lett 132:065102, 2024

[2] Haines et al, Phys Plasmas 29:042704, 2022

[3] Kritcher et al, Phys Plasmas 21:042708, 2014

[4] Haines et al, Phys Plasmas 31:042705, 2024

[5] Gittings et al, Comput Sci Discov 1:015005, 2008

[6] Haines et al, Phys Plasmas 24:052701, 2017

[7] Marinak et al, Phys Plasmas 8:2275, 2001

[8] Humbird et al, Phys Plasmas 28:042709, 2021

Presenters

  • Brian Michael Haines

    Los Alamos National Laboratory

Authors

  • Brian Michael Haines

    Los Alamos National Laboratory

  • Annie L Kritcher

    Lawrence Livermore National Laboratory

  • Abbas Nikroo

    Lawrence Livermore Natl Lab

  • Brian James Albright

    Los Alamos National Laboratory, Los Alamos Natl Lab

  • William S Daughton

    Los Alamos Natl Lab

  • Nelson M Hoffman

    Los Alamos National Laboratory

  • John J Kuczek

    Los Alamos National Lab

  • Ryan S Lester

    Los Alamos National Laboratory

  • Kevin D Meaney

    LANL

  • Joshua Paul Sauppe

    Los Alamos National Laboratory