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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Low-mode nonuniformity in direct-drive ICF implosions due to laser smoothing techniques employed on OMEGA

For successful laser-direct-drive inertial confinement fusion implosions, the laser irradiation must be highly uniform over the target surface. On OMEGA, multiple laser beams are used to illuminate targets quasi-uniformly. High-mode-number nonuniformities due to laser speckle on each individual beam are reduced by splitting each beam into two orthogonal polarizations (i.e., polarization smoothing, or PS) and a range of wavelengths (i.e., smoothing by spectral dispersion) that are dispersed at the target plane. However, cross-beam energy transfer (CBET) is sensitive to both the polarizations and wavelengths of the interacting beams, so the interplay between CBET and the laser-smoothing schemes results in unique intensity variation across each beam profile, which is a systematic source of low-mode drive nonuniformity on OMEGA. Here, we model these effects and find that the predicted ℓ = 1 mode in the laser-absorption distribution is consistent with the systematic core-flow direction that has been determined from the OMEGA implosion database. We also observe good agreement with the measured core-flow directions for two specific sets of implosions (one with PS, the other without PS) when we also account for the measured beam mispointing and the beam power imbalance.

Crossed beam scattering↗
DOE OSTI2026

Weibel-mediated filamentary structures observed in the ICF context

Here, in light of novel and past experimental results, we demonstrate how Weibel-mediated filamentary structures can develop in the expanding plasma plume of a laser-irradiated foil. The transverse ballistic cooling that occurs during the quasi-spherical plasma expansion naturally drives an electron pressure anisotropy, resulting in the growth of electron current filaments. This effect competes with electron–ion Coulomb collisions, which tend to isotropize the electron distribution function. Based on theoretical and particle-in-cell modeling, we provide estimates of the dominant wavelength and amplitude of the self-generated magnetic fluctuations, which are found to explain experimental data obtained at the OMEGA and Laser Megajoule facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗