Simulating Radiation Flow through Lattices
ORAL
Abstract
Recent experimental breakthroughs, such as LANL’s COAX platform, have advanced our ability to explore radiation flow dynamics through unconventional targets. Of particular interest is radiation through heterogeneous media such as lattices, consisting of optically thick struts in an optically thin background. Such heterogeneous targets introduce intricate interactions between radiation and hydrodynamics. Simulations using LANL’s xRage/Cassio code are constrained using diagnostic images from these indirectly driven lattice experiments.
Simulating lattices with precision remains computationally daunting. Significant scale differences between regions necessitate an impractically large number of computational cells to properly resolve features. To address this, we focus on developing simplified models, ranging from a laterally infinite 3D domain to a fully homogenized 2D representation. Each model undergoes detailed analysis of radiation front position, energy and opacity spectra, angular radiation profile, and mean and directional chord length. This approach aims to evaluate how different geometries influence radiation flow propagation within simulations.
Simulating lattices with precision remains computationally daunting. Significant scale differences between regions necessitate an impractically large number of computational cells to properly resolve features. To address this, we focus on developing simplified models, ranging from a laterally infinite 3D domain to a fully homogenized 2D representation. Each model undergoes detailed analysis of radiation front position, energy and opacity spectra, angular radiation profile, and mean and directional chord length. This approach aims to evaluate how different geometries influence radiation flow propagation within simulations.
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Presenters
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claire recamier
Los Alamos National Laboratory
Authors
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claire recamier
Los Alamos National Laboratory
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Jacob Feltman
Los Alamos National Laboratory
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Tom Byvank
Los Alamos National Laboratory
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Ryan S Lester
Los Alamos National Laboratory
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Todd J Urbatsch
Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)