Engineering topics

Vazirani, Nomita Nirmal

Publications and source records attributed to Vazirani, Nomita Nirmal.

7 records

DOE OSTI2024

Beryllium–tungsten graded density inner shells in double shell capsules for improved hydrodynamic stability

The outer surface of the high-Z inner shell in the double shell configuration of inertial confinement fusion experiments experiences Rayleigh–Taylor instability growth during the implosion process due to inverted density and pressure gradients between a highly compressed foam interstitial layer and the accelerating dense inner shell. Graded density layers have long been known to reduce instability growth rates. In this study, we employ high-fidelity radiation hydrodynamic simulations to demonstrate this improved stability when grading beryllium into tungsten. We first characterize the response to L-band preheat of these layers using a newly calibrated radiation drive. While graded layer capsules suffer reduced performance (here, measured as DD neutron yield from a CD foam fuel) in 1D simulations due to reduced kinetic energy coupling and reduced fuel compression, they suffer less of a performance drop when 2D instabilities are accounted for. With the improved stability of graded layers, we explore the performance of capsules with larger fuel radii and thinner shells as a preliminary study to find new designs in which graded layers produce the highest yields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

FY2024 Q4 L2 Milestone 8237 for Opacity-on-NIF

This document addresses parts 2 and 3 of the original milestone request. In the following writeup, the development of OpSpecTR at LLNL by LLNL and NNSS personnel will be detailed first, followed by a write-up of the development of Vme-resolved simulaVons of the opacity-on-NIF experiment. Capsule backlight simulaVons, hohlraum simulaVons, and sample simulaVons from CASSIO are combined to produce the line of sight from the capsule to an effecVve OpSpec posiVon. Spectra are generated by post-processing these simulaVons from either Spect3D, a commercial software by Prism ComputaVonal Sciences, or FESTR (Finite Element Spectroscopic Transport of RadiaVon), a LANL code. While the simulaVons do not at this stage proceed late enough to include the worst of the backgrounds generated from the hohlraum experimentally and each post-processing simulaVon includes only one ray for each spectrometer channel, these efforts represent proof of concept for a new capability to complete Vme-resolved and Vmegated simulaVons for the complete line of sight of the complex opacity-on-NIF geometry. Future work will be discussed at the end of the report for both efforts.

42 ENGINEERING↗

DOE OSTI2024

Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design

Access to reliable, clean energy sources is a major concern for national security. Much research is focused on the “grand challenge” of producing energy via controlled fusion reactions in a laboratory setting. For fusion experiments, specifically inertial confinement fusion (ICF), to produce sufficient energy, the fusion reactions in the ICF fuel need to become self-sustaining and burn deuterium-tritium (DT) fuel efficiently. The recent record-breaking NIF ignition shot was able to achieve this goal as well as produce more energy than used to drive the experiment. This achievement brings self-sustaining fusion-based power systems closer than ever before, capable of providing humans with access to secure, renewable energy. In order to further progress toward the actualization of such power systems, more ICF experiments need to be conducted at large laser facilities such as the United States's National Ignition Facility (NIF) or France's Laser Mega-Joule. The high cost per shot and limited number of shots that are possible per year make it prohibitive to perform large numbers of experiments. As such, experimental design relies heavily on complex predictive physics simulations for high-fidelity “preshot” analysis. These multidimensional, multi-physics, high-fidelity simulations have to account for a variety of input parameters as well as modeling the extreme conditions (pressures and densities) present at ignition. Such simulations (especially in 3D) can become computationally prohibitive to turn around for each ICF experiment. In this work, we explore using Bayesian optimization with Gaussian processes (GPs) to find optimal designs for ICF double shell targets, while keeping computational costs to manageable levels. These double shell targets have an inner shell that grades from beryllium on the outer surface to the higher Z material molybdenum, as opposed to the nominally used tungsten, on the inside in order to trade off between the high performance associated with high density inner shells and capsule stability. We describe our results for “capsule-only” xRAGE simulations to study the physics between different capsule designs, inner shell materials, and potential for future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Coupling 1D xRAGE simulations with machine learning for graded inner shell design optimization in double shell capsules

Advances in machine learning provide the ability to leverage data from expensive simulations of high-energy-density experiments to significantly cut down on computational time and costs associated with the search for optimal target designs. This study presents an application of cutting-edge Bayesian optimization methods to the one-dimensional (1D) design optimization of double shell graded layer targets for inertial confinement fusion experiments. This investigation attempts to reduce hydrodynamic instabilities while retaining high yields for future NIF experiments. Machine learning methods can use predictive physics simulations to identify graded layer designs from within the vast design space that demonstrate high predicted performance, including novel designs with high uncertainty in performance that may hold unexpected promise. By applying machine learning tools to the simulation design, we map the trade-off between 1D yield and instability, specifically isolating parameter ranges, which maintain high performance while showing significantly improved Rayleigh–Taylor stability over the point design. Furthermore, the groundwork laid in this study will be a useful design tool for future NIF experiments with graded layer targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Preshot Report for the NIF Discovery Science DDCyl Campaign: D_Hyd_DDCyl_DRT_DDD/EEE/FFF

The first Discovery Science shot day with the NIF DDCyl campaign demonstrated that Rayleigh-Taylor instability growth during the deceleration phase is scale-invariant for targets that varied in radial dimension and implosion time-scale by a factor of three. Smaller cylindrical implosions at the OMEGA laser facility were compared to the larger cylinders fielded in our first NIF outing. Both sets of targets had an initial m = 20 sinusoidal perturbation machined on the inner surface of an embedded aluminum marker layer, with the amplitude larger by the same factor of three for the NIF-scale targets. We observed growth factors of 14 at late time (t=λ = 7:7 ns, where λ = 1 for OMEGA and λ = 3 for NIF). These used a high density (300 mg/cm³) CH foam core, providing a very long period of deceleration before the rebounding shock hit the incoming spike tips, but the final convergence was only CR≈ 2:25. For our second shot day with this campaign, we are attempting to increase the convergence ratio to CR≥ 5 before reshock, while still measuring instability growth during the convergence/deceleration phase. As discussed in previous reports, the best way to increase convergence before reshock is to lower the density of the central foam. The preshot designs called for the use of a 30 mg/cm³ CH foam, though the as-built foams are closer to 40-42 mg/cm³, which is predicted to result in a final CR≈ 5:1 before reshock. Other than the lower foam density, the target design is identical to those used previously.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Design of Cylindrical Implosion Experiments to Demonstrate Scale-Invariant Rayleigh-Taylor Instability Growth

Radiation-hydrodynamics simulations are used to design laser-driven cylindrical implosion experiments to directly measure hydrodynamic instability growth in convergent geometry. Designs for two different size targets, varying in radial dimension by a factor of three, are presented. A set of beam pointings and powers are identified for each scale design that result in a nearly axially uniform implosion of an embedded marker layer. The implosion trajectories are shown to be scale-invariant between designs, with nearly identical scaled acceleration profiles. Finally, linear theory and radiation-hydrodynamics simulations predict that Rayleigh-Taylor instability growth of an azimuthal perturbation, machined on the inner surface of the embedded marker, is also scale-invariant between designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Demonstration of Scale-Invariant Rayleigh-Taylor Instability Growth in Laser-Driven Cylindrical Implosion Experiments

Rayleigh-Taylor instability growth is shown to be hydrodynamically scale-invariant in convergent cylindrical implosions for targets that varied in radial dimension and implosion timescale by a factor of three. The targets were driven directly by laser irradiation providing a short impulse, and instability growth at an embedded aluminum interface occurs as it converges radially inward by a factor of2.25 and decelerates on a central foam core. Late-time growth factors of 14 are observed for a single-modem= 20 azimuthal perturbation at both scales, despite the differences in laser drive conditions between the experimental facilities, consistent with predictions from radiation-hydrodynamics simulations. This platform enables detailed investigations into the limits of hydrodynamic scaling in high-energy-density systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗