Design of Radiation Transport through Heterogeneous, Stochastic Media
POSTER
Abstract
Radiation flow through media containing optically thick particulates dispersed in an optically thin background can challenge high energy density physics models. Typically available transport models depend on a single material equation of state and opacity per spatial cell, such that the solutions may have to average over heterogeneous regions using atomic mix schemes. Direct numerical simulation (DNS) at sufficient resolution can model a particular small-scale stochastic-medium configuration, but many DNS calculations are required to obtain an average solution where stochastic media are defined only probabilistically. Levermore-Pomraning models and extensions are somewhat mature for linear, uncoupled transport, but less so for thermal radiation transport with hydrodynamics. The X-ray Flow Over Lumps (XFOL) experiment at the OMEGA facility seeks to use the COAX spectral diagnostic to measure, in more detail than ever before, radiation flow through stochastic media. In this work, we present design considerations for these experiments using Cassio simulations of radiation flow through optically thin Sc-Si-aerogel foams containing optically thick V-oxide particulates. We compare averaged homogeneous calculations with DNS calculations of the heterogeneous stochastic media.
Presenters
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Tom Byvank
Los Alamos National Laboratory
Authors
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Tom Byvank
Los Alamos National Laboratory
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Chris Fryer
Los Alamos Natl Lab
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Chris J Fontes
Los Alamos National Laboratory, Los Alamos Natl Lab
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Shane X Coffing
Los Alamos National Laboratory, University of Michigan, LANL
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Corey Skinner
University of New Mexico
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Andy S Liao
Los Alamos National Laboratory
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Suzannah R Wood
Los Alamos National Laboratory
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Pawel M Kozlowski
Los Alamos National Laboratory
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Heather M Johns
Los Alamos Natl Lab, LANL
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Harry F Robey
Lawrence Livermore Natl Lab
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David D Meyerhofer
Los Alamos National Laboratory
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Todd Urbatsch
Los Alamos National Laboratory, Los Alamos National Lab, Los Alamos Natl Lab