Engineering topics

Nora, Ryan

Publications and source records attributed to Nora, Ryan.

3 records

DOE OSTI2023

First large capsule implosions in a frustum-shaped hohlraum

Here, we report on the first indirect-drive implosions driven by a dual conical frustum-shaped hohlraum denoted “frustraum” and the experimental tuning campaigns leading up to two layered implosions. The campaign used 1.2 and 1.4 mm inner radius high density carbon (HDC) capsules and represented the largest HDC capsules to be imploded on the National Ignition Facility via indirect drive. Several techniques were successfully implemented to control the Legendre mode 2 capsule symmetry of the implosions, including changing the wall angle of the frustraum, which is not possible with cylindrical hohlraums. A mode 4 feature was observed and its implications for hotspot mix discussed. Two layered implosions were conducted with 1.2 mm inner radius capsules, the latter of which achieved the highest layered capsule absorbed energy on the National Ignition Facility using only 1.74 MJ of laser energy. The layered implosion results, along with generalized Lawson parameters, suggest that increasing the energy absorbed by the capsule at the expense of long coast times makes it more challenging to achieve ignition and that further reducing coast time (time between end of laser pulse and bang time) closer to the 1 ns level is warranted to improve the areal density and make it easier to achieve the hotspot temperature, alpha heating, and yield amplification required for ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Effects of Laser Bandwidth in Direct-Drive High-Performance DT-Layered Implosions on the OMEGA Laser

In direct-drive inertial confinement fusion, the laser bandwidth reduces the laser imprinting seed of hydrodynamic instabilities. The impact of varying bandwidth on the performance of direct-drive DT-layered implosions was studied in targets with different hydrodynamic stability properties. The stability was controlled by changing the shell adiabat from (α F ≃ 5) (more stable) to (α F ≃ 3.5) (less stable). Herein these experiments show that the performance of lower adiabat implosions improves considerably as the bandwidth is raised indicating that further bandwidth increases, beyond the current capabilities of OMEGA, would be greatly beneficial. These results suggest that the future generation of ultra-broadband lasers could enable achieving high convergence and possibly high gains in direct drive ICF.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Iterative sampling of expensive simulations for faster deep surrogate training

Deep neural network (DNN) surrogates of expensive physics simulations are enabling a rapid change in the way that common experimental design and analysis tasks are approached. Surrogate models allow simulations to be performed in parallel and separately from downstream tasks, thereby enabling analyses that would be impossible with the simulation in-the-loop; surrogates based on DNNs can effectively emulate diverse non-scalar data of the types collected in fusion and laboratory-astrophysics experiments. The challenge is in training the surrogate model, for which large ensembles of physics simulations must be run, preferably without wasting computational effort on uninteresting simulations. Here, in this paper, we present an iterative sampling scheme that can preferentially propose simulations in interesting regions of parameter space without neglecting unexplored regions, allowing high-quality and wide-ranging surrogate models to be trained using 2–3 times fewer simulations compare to space-filling designs. Our approach uses an explicit importance function defined on the simulation output space, balanced against a measure of simulation density which serves as a proxy for surrogate accuracy. It is easy to implement and can be tuned to find interesting simulations early in the study, allowing surrogates to be trained quickly and refined as new simulations become available; this represents an important step towards the routine generation of deep surrogate models quickly enough to be truly relevant to experimental work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗