Double shell targets are a promising potential avenue to obtain robust neutron yield at current laser facilities. Similar to single shell designs, double shells require the symmetric implosion of an ablator in order to uniformly compress and heat a fuel volume, with the goal of achieving thermonuclear burn. Significant differences between double and single shells include the usage of an aluminum ablator as well as a reverse ramp laser pulse. In addition, double shells require a different convergence than single shells for fuel ignition. Numerical implosion studies at various energies with comparisons to experimental outcomes are required to gain confidence that simulations can capture the ablator shape from subscale to full scale. The current work builds on previous implosion experiments conducted at 1-MJ laser energy to confirm achieved ablator symmetry at 1.25 and 1.5 MJ. Average ablator P2 and P4 shapes measured in these experiments are within 5% of the simulated shape, which merits the platforms for further experimental studies.

beam with annular radial profile and a second beam with the uniform radial profile. It is found that the first beam causes some additional fuel compression and confinement that decrease the total beam energy required for the ignition to 6 kJ, which is 40% smaller than in the case of a single beam with uniform radial profile.

Building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While simulation codes are used to model ICF implosions, incomplete physics and the need for approximations deteriorate their predictive capability. Identification of relationships between controllable design inputs and measurable outcomes can help guide the future design of experiments and development of simulation codes, which can potentially improve the accuracy of the computational models used to simulate ICF implosions. In this article, we leverage developments in machine learning (ML) and methods for ML feature importance/sensitivity analysis to identify complex relationships in ways that are difficult to process using expert judgment alone. We present work using random forest (RF) regression for prediction of yield, velocity, and other experimental outcomes given a suite of design parameters, along with an assessment of important relationships and uncertainties in the prediction model. We show that RF models are capable of learning and predicting on ICF experimental data with high accuracy, and we extract feature importance metrics that provide insight into the physical significance of different controllable design inputs for various ICF design configurations. These results can be used to augment expert intuition and simulation results for optimal design of future ICF experiments.

Double shell targets1 on the National Ignition Facility (NIF) provide for an alternative path to a high yield experiment compared to the single shells. The concept of the design is that through kinetic energy transfer between an outer ablator and inner pusher, conditions needed for robust burn can be achieved with a lower convergence ratio and internal temperature compared to a single shell. Due to the multilayer construction of the target, features that can perturb any of the multiple layers of the capsule and degrade target performance are a concern. Understanding the mechanics of these degradations and ways to prevent them is extremely important for a successful design.

Discrepancies exist between theoretical and experimental opacity data for iron, at temperatures 180–195 eV and electron densities near 3 × 1022/cm3, relevant to the solar radiative-convective boundary. Another discrepancy, between theory and helioseismic measurements of the boundary’s location, would be ameliorated if the experimental opacity is correct. To address these issues, this paper details the first results from new experiments under development at the National Ignition Facility (NIF), using a different method to replicate the prior experimental conditions. In the NIF experiments, 64 laser beams indirectly heat a plastic-tamped rectangular iron-magnesium sample inside a gold cavity. Another 64 beams implode a spherical plastic shell to produce a continuum X-ray flash which backlights the hot sample. An X-ray spectrometer records the transmitted X-rays, the unattenuated X-rays passing around the sample, and the sample’s self-emission. From these data, X-ray transmission spectra are inferred, showing Mg K-shell and Fe L-shell X-ray transitions from plasma at a temperature of ~150 eV and electron density of ~8 × 1021/cm3. These conditions are similar to prior Z measurements which agree better with theory. The NIF transmission data show statistical uncertainties of 2–10%, but various systematic uncertainties must be addressed before pursuing quantitative comparisons. The paths to reduction of the largest uncertainties are discussed. Once the uncertainty is reduced, future NIF experiments will probe higher temperatures (170–200 eV) to address the ongoing disagreement between theory and Z data.

The Mshock campaign is studying the feed through of the Richtmyer-Meshkov instability (RMI) in a thin layer in the high energy density (HED) regime. Experiments utilize a beryllium shock tube filled with low density foam and a high density plastic to study the instability. Initial experiments were performed at the OMEGA laser facility and recently at the National Ignition facility. While the basic design of the experiment is the same, critical components were changed to optimize the data quantity and clarity for the more energetic NIF.

Experiments at the National Ignition Facility (NIF) using targets containing a deuterium-tritium (D-T) fuel layer have, until recently, required that a high-quality layer of solid D-T (herein referred to as an ice layer) be formed in the capsule. The development of a process to line the inner surface of a target capsule with a foam layer of a thickness that is typical of ice layers has resulted in the ability to field targets with liquid layers wetting the foam. Successful fielding of liquid-layer targets on NIF required not only a foam-lined capsule but also changes to the capsule filling process and the manner with which the inventory is maintained in the capsule. Additionally, changes to target heater power and the temperature drops across target components were required in order to achieve the desired range of shot temperatures. These changes and the target's performance during four target shots on NIF are discussed.

The double-shell platform fielded at the National Ignition Facility requires developments in new machining techniques and robotic assembly stations to meet the experimental specifications. Current double-shell target designs use a dense high-Z inner shell, a foam cushion, and a low-Z outer shell. The design requires that the inner shell be gas filled using a fill tube. This tube impacts the entire machining and assembly design. Other intermediate physics designs have to be fielded to answer physics questions and advance the technology to be able to fabricate the full point design in the near future. One of these intermediate designs is a mid-Z imaging design. The methods of designing, fabricating, and characterizing each of the major components of an imaging double shell are discussed with an emphasis on the fabrication of the machined outer metal shell.

The Big Area BackLigher (BABL) has been developed for large area laser-driven x-ray backlighting on the National Ignition Facility (NIF), which can be used for general High Energy Density (HED) experiments. The BABL has been optimized via hydrodynamic simulations to produce laser-to-x-ray conversion efficiencies of up to nearly 5%. Four BABL foil materials, Zn, Fe, V, and Cu, have been used for He-alpha x ray production.