Sensitivity of the Convergence to Direct-Drive Cylindrical Implosion Parameters

ORAL

Abstract

To achieve efficient thermonuclear burn in Inertial Confinement Fusion (ICF) implosions, high convergence is needed to reduce the required amount of driver energy. Additionally, there is a well-known correlation between the convergence and hydrodynamic instabilities, such as the Rayleigh-Taylor (RT) instability, which have a deleterious effect on ICF. Thus, examining both the consequences of high convergence as well as the target parameters necessary for achieving this condition is essential to the development of robust target designs. 1D simulations of cylindrical targets produced by the Los Alamos Eulerian radiation-hydrodynamics code, \texttt{xRAGE}, have been used to search our target parameter space. Studying the topology of these spaces both informs our understanding of the sensitivity of the convergence to target design parameters, such as fill density, and provides insight into the exact extent to which instability growth can be attributed to convergence. We will present future plans for high convergence direct-drive cylindrical implosion experiments fielded at the National Ignition Facility (NIF). Experiments utilizing the NIF should be able to produce high quality measurements reaching convergences near 15; 4x greater than previous cylindrical implosions.

*Work performed by Los Alamos National Laboratory under Contract 89233218CNA000001 for the National Nuclear Security Administration of the U.S. Department of Energy.

Authors

  • William Gammel

    • Los Alamos National Laboratory
  • J.P. Sauppe

    • Los Alamos National Laboratory
    • Los Alamos National Lab
  • J. Kline

    • Los Alamos National Laboratory
    • Los Alamos National Lab
  • Sasikumar Palaniyappan

    • Los Alamos National Laboratory
    • Los Alamos National Laboratory, Los Alamos, NM 87545
    • Los Alamos National Lab
  • K.A. Flippo

    • Los Alamos National Laboratory
    • LANL
    • Los Alamos National Lab
  • Benjamin Tobias

    • Los Alamos National Laboratory
    • Los Alamos National Lab
    • LLNL
  • Nomita Vazirani

    • Los Alamos National Laboratory