Measuring Initial X-Ray Flux from a Halfraum for Radiation Flow Studies Using Dante and FIDUCIA

ORAL

Abstract

Radiation flows in stochastic media are not well understood from a radiation-hydrodynamics–simulation perspective. A study known as the X-Ray Flow Over Lumps Campaign seeks to validate radiation-hydrodynamics models by studying the radiation flow from a halfraum through doped foams with various sizes of inclusions.1 The inclusions change the absorption spectra of the foam as the radiation propagates from the halfraum; as a result, the changes to the absorption depend heavily on the physics assumptions used in the model. The first critical step to the measurements and validation of these models is to characterize the initial flux from the halfraum with a high degree of certainty. FIDUCIA, a method for inferring x-ray flux from the halfraum drive using cubic splines, generates a broadband picture of the initial flux with high precision.2 The x-ray flux is determined using monotonicity-conserving interpolation and a χ2 global minimization solver to produce only physically valid solutions. This new interpolation method reduces uncertainty in the x-ray flux measurement as validated by a Monte Carlo simulation.

*This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award Number DE-NA0003856. Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by Triad National Security, LLC for the National Nuclear Security Administration of U.S. Department of Energy under contract 89233218CNA000001.

Presenters

  • Daniel H Barnak

    • Laboratory for Laser Energetics
    • University of Rochester

Authors

  • Daniel H Barnak

    • Laboratory for Laser Energetics
    • University of Rochester
  • Tom Byvank

    • Los Alamos National Laboratory
  • Dzafer Camdzic

    • Los Alamos National Laboratory
  • Ahmed T Elshafiey

    • LANL
  • Heather M Johns

    • Los Alamos Natl Lab
  • Pawel M Kozlowski

    • LANL
  • Todd J Urbatsch

    • Los Alamos National Laboratory