Assessing the Origins o f the Helical Instability in Axially Magnetized Liner Implosions
Abstract not provided.
Publications
Narrowband Self-Emission X-ray Imaging of MagLIF Targets on Z
Abstract not provided.
Understanding the relationship between current loss and load hardware geometry in Z machine experiments
Abstract not provided.
First demonstration of an inductively driven X-pinch for diagnosing high energy density experiments on the Z Pulsed Power Facility
Abstract not provided.
A Time-Resolved In-Chamber X-Ray Pin Hole Imager for Z
Abstract not provided.
Performance Scaling in Magnetized Liner Inertial Fusion Experiments
Physical Review Letters
We present experimental results from the first systematic study of performance scaling with drive parameters for a magnetoinertial fusion concept. In magnetized liner inertial fusion experiments, the burn-averaged ion temperature doubles to 3.1 keV and the primary deuterium-deuterium neutron yield increases by more than an order of magnitude to 1.1×1013 (2 kJ deuterium-tritium equivalent) through a simultaneous increase in the applied magnetic field (from 10.4 to 15.9 T), laser preheat energy (from 0.46 to 1.2 kJ), and current coupling (from 16 to 20 MA). Individual parametric scans of the initial magnetic field and laser preheat energy show the expected trends, demonstrating the importance of magnetic insulation and the impact of the Nernst effect for this concept. A drive-current scan shows that present experiments operate close to the point where implosion stability is a limiting factor in performance, demonstrating the need to raise fuel pressure as drive current is increased. Simulations that capture these experimental trends indicate that another order of magnitude increase in yield on the Z facility is possible with additional increases of input parameters.
Deep Learning Enabled Bayesian Inference of Fuel Magnetization in Magnetized Liner Inertial Fusion Experiments on Z
Abstract not provided.
Bayesian Analysis Techniques Part 2: Deep Learning in the Inference Loop
Abstract not provided.
Update on MagLIF preheat experiments
Abstract not provided.
Deep Learning Enabled Bayesian Inference of Fuel Magnetization in Magnetized Liner Inertial Fusion Experiments on Z
Abstract not provided.
Performance scaling with drive parameters in Magnetized Liner Inertial Fusion experiments
Abstract not provided.
Quantification of MagLIF Morphology using the Mallat Scattering Transformation
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.
Signatures of preheat performance in Magnetized Liner Inertial Fusion experiments from time-resolved stimulated Raman and Brillouin backscatter spectra
Abstract not provided.
Laser Gate Experiment for Increasing Energy Coupling Efficiencies in Magnetized Liner Inertial Fusion (MagLIF)
Abstract not provided.
Magneto Rayleigh-Taylor instability growth in magnetically driven cylindrical liners
Abstract not provided.
Inductively driven transmission lines (IDTLs): fringe-field-driven devices for powering diagnostic X-ray sources on the Z Pulsed Power Facility
Abstract not provided.
The Impact on Mix of Different Preheat Protocols
Abstract not provided.
Scaling of Stagnation Conditions n Magnetized Liner Inertial Fusion Experiments
Abstract not provided.
Progress in Implementing High-Energy Low-Mix Laser Preheat for MagLIF
Abstract not provided.
Towards Learning MagLIF Performance from Stagnation Morphology
Abstract not provided.
LASER GATE EXPERIMENT FOR REDUCING ENERGY COUPLING LOSSES IN MAGNETIZED LINER INERTIAL FUSION (MAGLIF)
Abstract not provided.
Towards Learning MagLIF Performance from Stagnation Morphology
Abstract not provided.
Stagnation performance scaling of Magnetized Liner Inertial Fusion
Abstract not provided.
The Mallat Scattering Transform (MST) in high energy density plasmas: a new look at nonlinear multiscale physics in HED
Abstract not provided.
Stagnation Performance Scaling of Magnetized Liner Inertial Fusion
Abstract not provided.
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