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Mixing of cold, higher-Z elements into the fuel region of an inertial confinement fusion target spoils the fusion burn efficiency. This mixing process is driven by both "turbulent" and "atomic" mixing processes, the latter being modeled through transport corrections to the basic hydrodynamic models. Recently, there has been a surge in the development of dense plasma transport modeling and the associated transport coefficients; however, experimental validation remains in its infancy. To address this gap in our knowledge of interfacial mixing, Sandia National Laboratories is developing a new experimental platform at the Z-facility to investigate plasma transport in dense plasmas that span the entire warm dense matter regime. Specifically, this platform is being developed to measure species transport across a V/CH interface, using an x-ray driven hohlraum to drive the sample to [?] 190eV over 5ns. The heated sample is diagnosed using radiography optimized to measure the distribution of Vanadium perpendicular the interface. In order to interpret measurements made using this experimental platform, modeling tools that incorporate transport effects in strongly coupled plasmas are required. To this end, we utilize new advances in multi-species kinetic theory, collision models applicable to strongly coupled plasmas and modeling of degenerate electron plasmas to develop such a capability. The resulting kinetic transport code has been applied, along with state-of-the-art radiation hydrodynamic codes, to model the experiments. Results from this modeling effort highlight the importance of strong electric fields, which are present in the kinetic transport code, but absent in the radiation hydrodynamics code, in driving interfacial mixing. Synthetic radiography generated from all of these models reveals the ability of experimental diagnostics to distinguish interfacial mixing driven by a range of transport effects. We demonstrate that the spatial and temporal resolution of radiography diagnostics currently available at the Z-facility can distinguish between these different transport effects when multiple (3 [?] 4) radiographs, separated in time ( [?] 2 ns ) with accurate timing are captured per experiment.

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TYPE SAND Report YEAR 2019

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Quantification of MagLIF Morphology using the Mallat Scattering Transformation

Glinsky, Michael E.; Moore, Thomas M.; Lewis, William L.; Weis, Matthew R.; Jennings, Christopher A.; Ampleford, David A.; Harding, Eric H.; Knapp, Patrick K.; Gomez, Matthew R.; Lussiez, Sophia L.

The morphology of the stagnated plasma resulting from Magnetized Liner Inertial Fusion (MagLIF) is measured by imaging the self-emission x-rays coming from the multi-keV plasma, and the evolution of the imploding liner is measured by radiographs. Equivalent diagnostic response can be derived from integrated rad-MHD simulations from programs such as Hydra and Gorgon. There have been only limited quantitative ways to compare the image mor- phology, that is the texture, of simulations and experiments. We have developed a metric of image morphology based on the Mallat Scattering Transformation (MST), a transformation that has proved to be effective at distinguishing textures, sounds, and written characters. This metric has demonstrated excellent performance in classifying ensembles of synthetic stagnation images. We use this metric to quantitatively compare simulations to experimen- tal images, cross experimental images, and to estimate the parameters of the images with uncertainty via a linear regression of the synthetic images to the parameter used to generate them. This coordinate space has proved very adept at doing a sophisticated relative back- ground subtraction in the MST space. This was needed to compare the experimental self emission images to the rad-MHD simulation images. We have also developed theory that connects the transformation to the causal dynamics of physical systems. This has been done from the classical kinetic perspective and from the field theory perspective, where the MST is the generalized Green's function, or S-matrix of the field theory in the scale basis. From both perspectives the first order MST is the current state of the system, and the second order MST are the transition rates from one state to another. . An efficient, GPU accelerated, Python implementation of the MST was developed. Future applications are discussed.

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TYPE SAND Report YEAR 2019

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