Area-Based Image Metrics Elucidate Differences Between Radiation-Hydrodynamics Simulations and NIF Experimental X-ray Images

ORAL

Abstract

X-ray images at the National Ignition Facility (NIF) provide important metrics regarding the shape of the hotspot along a given line-of-sight. The 17% contour from peak brightness is usually used to infer the size of the hotspot as well as determine shape perturbations quantified through the Legendre coefficients P2 and P4. Unfortunately features that lie inside the contour such as those that could arise from tent or fill-tube perturbations are not easily captured. Here we present the use of a two-dimensional orthonormal basis of Laguerre-Gaussian modes (LGM) to accurately represent an image with about 100 coefficients. The LGM basis is able to describe both low- and high-frequency components of the entire image unlike the Legendre decomposition which is limited to the 17% contour. The decomposition of the image into LGM modes reduces the image storage requirements by about 100x; an important consideration for doing an ensemble of 50K rad-hydro simulations. LGM image coefficients from NIF hGXD images can be directly compared to post-shot rad-hydro simulations. We demonstrate how the LGM coefficients from simulations centered around the BigFoot N180128 shot can be used to better constrain the evolution of ICF implosions. LLNL-ABS-780323

*This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Authors

  • Michael Kruse

    • Lawrence Livermore Natl Lab
  • John Field

    • Lawrence Livermore Natl Lab
  • James Gaffney

    • Lawrence Livermore Natl Lab
  • Ryan Nora

    • Lawrence Livermore Natl Lab
  • Kelli Humbird

    • Lawrence Livermore Natl Lab
  • Robin Benedetti

    • Lawrence Livermore Natl Lab
  • Nobuhiko Izumi

    • Lawrence Livermore Natl Lab
  • Shahab Khan

    • Lawrence Livermore Natl Lab
  • Tammy Ma

    • Lawrence Livermore Natl Lab
  • Luc Peterson

    • Lawrence Livermore Natl Lab
  • Brian Spears

    • Lawrence Livermore Natl Lab