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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Daily, 30 m Resolution NDSI Data for the East River Watershed, CO for 2000-2020

This dataset contains daily Normalized Difference Snow Index (NDSI) values at 30 m spatial resolution for the East River watershed in Colorado, USA. The temporal range of these data includes water years 2001-2020. These data were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). This model fuses low spatial and high temporal resolution data from MODIS (500 m, daily) with high spatial and low temporal resolution data from Landsat (30 m, 16 days) to create a 30m synthetic daily snow product. This product allows for the analysis of historical snow covered area trends in the East River Watershed at fine spatiotemporal resolutions where it was not available previously. This research was performed as a part of the Department of Energy’s Subsurface Biogeochemical Research Program with the primary intent of better understanding the timing and spatial patterns of water delivery to the Critical Zone in mountain watersheds. Each .zip file contains one "water year" of data (October 1 - September 30; i.e., water year 2010 starts October 1, 2010 and ends September 30, 2011). Each zip file contains the following: STARFM daily Normalized Difference Snow Index (NDSI) fusion data files in GeoTiff format with one layer for each day between Landsat data acquisition dates (i.e., for dates of Landsat acquisition, the Landsat image is included for that date). The study area is located in an area of Landsat path overlap, so Landsat dates acquisitions are every 7-9 days. Landsat NDSI files containing the high spatial (30m), low temporal (7-9 days due to Landsat path overlap) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Dates for which no Landsat data were obtained are included as NoData layers. MODIS NDSI files containing the high temporal (daily), low spatial (500m) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Please note the MODIS data were resampled to 30m pixels for input into the STARFM model. The data have a scale factor of 10,000 and a no data value of -32767. The projection of all datasets is WGS 84 (EPSG: 4326), which has a latitude/longitude based degree resolution of 0.0002694946 X 0.0002694946, and approximates to the 30 m spatial resolution mentioned above. The Layer Index files in .csv format. They contain information for each layer in the above GeoTiff files regarding the corresponding date for each layer, the fraction of pixels in the image that contain valid data (missing data is due to either cloud cover or poor data quality; these values are not percent snow cover). Dates of Landsat overpass are indicated in these files. If no Landsat data were able to be obtained due to cloud cover or lack of Landsat Tier 1 data available on Google Earth Engine, this is also noted.

EARTH SCIENCE > CRYOSPHERE > SNOW/ICE↗
DOE OSTI2022

Proton stopping measurements at low velocity in warm dense carbon

Abstract Ion stopping in warm dense matter is a process of fundamental importance for the understanding of the properties of dense plasmas, the realization and the interpretation of experiments involving ion-beam-heated warm dense matter samples, and for inertial confinement fusion research. The theoretical description of the ion stopping power in warm dense matter is difficult notably due to electron coupling and degeneracy, and measurements are still largely missing. In particular, the low-velocity stopping range, that features the largest modelling uncertainties, remains virtually unexplored. Here, we report proton energy-loss measurements in warm dense plasma at unprecedented low projectile velocities. Our energy-loss data, combined with a precise target characterization based on plasma-emission measurements using two independent spectroscopy diagnostics, demonstrate a significant deviation of the stopping power from classical models in this regime. In particular, we show that our results are in closest agreement with recent first-principles simulations based on time-dependent density functional theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Status of the High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory (FNAL) and Lawrence Berkeley National Laboratory (LBNL) are building a new High Field Vertical Magnet Test Facility (HFVMTF) for testing superconducting cables in high magnetic field. The background magnetic field of 15 T in the HFVMTF will be produced by a magnet provided by LBNL. The HFVMTF is jointly funded by the US DOE Offices of Science, High Energy Physics (HEP), and Fusion Energy Sciences (FES), and will serve as a superconducting cable test facility in high magnetic fields and a wide range of temperatures for HEP and FES communities. This facility will also be used to test high-field superconducting magnet models and demonstrators, including hybrid magnets, produced by the US Magnet Development Program (MDP). The paper describes the status of the facility, including construction, cryostat designs, top and lambda plates, and systems for powering, and quench protection and monitoring.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A simple model to scope out parameter space for indirect drive designs on NIF

In this work, we present a simple model to scope out parameter space for indirect-drive, inertial confinement fusion designs for the National Ignition Facility laser. Because the parameter space is large, simple models can be used to identify regions of parameter space for further study with more sophisticated models and experiments. We include a model for Hohlraum radiation drive and symmetry—both based on empirical scalings from the data. The model for radiation drive is based on assuming that the high atomic number (Z) Hohlraum wall dominates the energy balance during the high power, peak of the pulse (≳ 300 TW). We find that the time-dependent radiation drive flux can be described by the running integral of the laser energy divided by the Hohlraum area multiplied by constant slopes in two distinct time periods. The first period is when the laser power rises rapidly, so the radiation temperature increases due to changes in laser power and wall albedo. The second period is during peak power—here, the laser power is typically held constant—so, the radiation temperature increases only due to changes in the wall albedo. This model is applied to several NIF designs with different Hohlraum sizes, laser pulse length durations, and peak powers and energies. Drive and symmetry models can be combined to find regions of parameter space that have high capsule absorbed energy while maintaining a symmetric implosion. We propose a new metric for evaluating designs based on minimizing the radius at which the maximum implosion kinetic energy is achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

National Ignition Campaign Data Analysis by an ICF Outsider

A simple DT burn model, with no alpha-particle warming feedback, using a combination of ICF inputs and the measured ion temperature, T, volume compression, C, ablator velocity, v, and burn width time, Δt, can reproduce the national-ignition campaign (NIC) fusion yields with a rms percent difference of ~40%. Analysis suggestion the fusion-yield reproducibility of NIC events with nominally identically measured T, C, v, and Δt is <30%. The highest fusion yields, at a fixed laser energy are obtained with depleted-uranium (DU) hohlraums and high-density carbon (HDC) ablators. Small diameter fit tubes (≤5 μm) enhance fusion yields by an average of 26±15% relative to 10-μm diameter fit tubes. A dependence of fusion yield on the diameter of the capsule relative to the diameter of the hohlraum is inferred for fixed T, C, v, and Δt. No evidence of conditions close to ignition, or alpha-particle warming is found in the existing NIC data with LEH< 2MJ. To obtain a predictive model for extrapolation proposes we map the T, C, and v into power laws as a function of LEH. The above mentioned extrapolatable model has a rms percent difference from the yields of the second half of the NIC of (56 ± 4)%. Higher (and significantly lower) DT temperatures are obtained with HDC ablators (and low-foot drives). The highest compressions are obtained via low-foot drives, but this does not compensate for the corresponding lower temperatures. An extrapolation of the presented model suggests significant alpha-particle heating at an LEH of ~5 MJ. It is hoped that others more familiar it the conditions needed for ignition will use to presented model to estimate the LEH required for ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Study of ablation and shock generation across three orders of magnitude of laser intensity with 100 ps laser pulses

The laser ablation and subsequent shock generation in solid targets plays an important role in a variety of research topics from equation of state models for materials to inertial confinement fusion. One of the long-standing issues is the knowledge of ablation depth in the picosecond time regime. Here, we report on a direct technique for determining the ablation depth in aluminum using x-ray diffraction data from Linac Coherent Light Source at the Stanford Linear Accelerator Center. This technique gives a direct measurement of the shock wave propagation in the bulk target, enabling an ability to discern early timescale physics from late timescale effects not available in postmortem analysis. We find that the ablation depths only vary by 0.2 μm across three orders of magnitude of laser intensity, while the pressure increased by a factor of 10 following a square root dependence on laser pulse energy. We further observe that the ablation depth in this intensity range (10 11 –10 13 W/cm 2 in intensity, corresponding to 0.8–80 J/cm 2 in fluence) cannot be modeled by a universal scaling law, given the complexity of the mechanisms governing laser ablation in this intensity regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Data-driven prediction of scaling and ignition of inertial confinement fusion experiments

Recent advances in inertial confinement fusion (ICF) at the National Ignition Facility (NIF), including ignition and energy gain, are enabled by a close coupling between experiments and high-fidelity simulations. Neither simulations nor experiments can fully constrain the behavior of ICF implosions on their own, meaning pre- and postshot simulation studies must incorporate experimental data to be reliable. Linking past data with simulations to make predictions for upcoming designs and quantifying the uncertainty in those predictions has been an ongoing challenge in ICF research. We have developed a data-driven approach to prediction and uncertainty quantification that combines large ensembles of simulations with Bayesian inference and deep learning. The approach builds a predictive model for the statistical distribution of key performance parameters, which is jointly informed by past experiments and physics simulations. The prediction distribution captures the impact of experimental uncertainty, expert priors, design changes, and shot-to-shot variations. We have used this new capability to predict a 10× increase in ignition probability between Hybrid-E shots driven with 2.05 MJ compared to 1.9 MJ, and validated our predictions against subsequent experiments. We describe our new Bayesian postshot and prediction capabilities, discuss their application to NIF ignition and validate the results, and finally investigate the impact of data sparsity on our prediction results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

How Bayesian methods can improve R -matrix analyses of data: The example of the d t reaction

The 3 H(d, n) 4 He reaction is of significant interest in nuclear astrophysics and nuclear applications. It is an important, early step in big-bang nucleosynthesis and a key process in nuclear fusion reactors. We use one- and two-level R-matrix approximations to analyze data on the cross section for this reaction at center-of-mass energies below 215 keV. We critically examine the data sets using a Bayesian statistical model that allows for both common-mode and additional point-to-point un- certainties. We use Markov Chain Monte Carlo sampling to evaluate this R-matrix-plus-statistical model and find two-level R-matrix results that are stable with respect to variations in the channel radii. The S factor at 40 keV evaluates to 25.36(19) MeV b (68% credibility interval). We discuss our Bayesian analysis in detail and provide guidance for future applications of Bayesian methods to R-matrix analyses. We also discuss possible paths to further reduction of the S-factor uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Low Energy Analysis of NuclEar Reactions v0.0.1

This is a lightweight, easy to use Python analysis package for analyzing public low-energy nuclear reaction data relevant to understanding basic nuclear processes, often of relevance to Solar Fusion, to improve our theoretical understanding of them, and enable connections with input from lattice QCD. It performs the analysis in a Bayesian Framework and supports Bayesian Model Averaging to provide a robust uncertainty quantification.

Walker-Loud, André↗
DOE OSTI2025

Optimizing Simulation Fidelity in Direct-Drive Inertial Confinement Fusion with Cassio

Recently, the National Ignition Facility (NIF) demonstrated that inertial confinement fusion (ICF) is capable to achieve thermonuclear (TN) ignition in the laboratory, making it a crucial method on the path to replicate the Sun’s power production mechanism on Earth. However, the physics governing the high-energy density environments is very complex and remains a challenge to fully understand and model. For example, dopants in the TN fuel are important diagnostic tools to extract the thermodynamic conditions of the plasma. However, if their concentration is chosen too high, they can significantly degrade the performance of an ICF capsule. In this study, we use the Los Alamos National Laboratory radiation-hydrodynamics code Cassio to model ICF implosions of capsules which contain deuterium fuel with high-Z dopants like Krypton and Argon from the high-Z campaign conducted 15 years ago. We focus on how chosen computational and physics parameters influence the implosion outcomes. By systematically changing the resolution of the computational mesh and the photon energies as well as modifying settings for the laser drive and TN fuel pre-heat effects, we assess the impact on experimentally measured performance metrics like neutron production from TN burn and x-ray emission during the implosion. Our results will help to improve the fidelity of simulations and guide future numerical studies and experimental designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Electron heating in 2D: Combining Fermi–Ulam acceleration and magnetic-moment non-adiabaticity in a mirror-configuration plasma

We analyze a new mechanism for the creation and confinement of energetic electrons in a mirror-configuration plasma. A Fermi–Ulam-type process, driven by end-localized coherent electrostatic oscillations, provides axial acceleration, while a natural non-adiabaticity of μ provides phase decorrelation and energy isotropization. This novel 2D combination causes the electron energy distribution function, calculated with a diffusive-loss model, to assume a Maxwellian shape with the μ non-adiabaticity, reducing loss-cone escape and annulling the absolute-barrier energy-limiting Chirikov criterion of lower dimensional models. Here, the theoretical predictions are compared with data from an experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Impact of Plate Thickness and Joint Geometry on Residual Stresses in 347H Stainless Steel Welds

Weldments of 347H stainless steel are potentially susceptible to stress relaxation cracking at elevated service temperatures. Mitigation of stress relaxation cracking susceptibility within a multipass weld requires a good understanding of welding practices and manufacturing techniques to control high tensile residual stresses. Here in this work, the dependence of residual stress distribution in 347H stainless steel on base plate thickness, joint geometry design, and preheating condition was systematically investigated by using three-dimensional finite element models. The finite element models were validated through good agreement between neutron diffraction measurements and calculated elastic strains. The single-V-groove welds with and without a preheating step all produced similar peak von Mises residual stresses, above 450 MPa, within both the fusion zone and heat-affected zone (HAZ). In plates thicker than 0.5 in. (12.7 mm), high tensile residual stress could be observed in a relatively large area, from the middle of the plate thickness to underneath the top surface. A double-V groove shifted the high tensile stress area to the middle thickness of the weld. A single-J-groove weld was able to confine the residual stress to a very small region near the middle thickness within the fusion zone and suppressed the von Mises residual stress within the HAZ to below 400 MPa.

14 SOLAR ENERGY↗
DOE OSTI2020

Modeling hydrodynamics, magnetic fields, and synthetic radiographs for high-energy-density plasma flows in shock-shear targets

Three-dimensional FLASH radiation-magnetohydrodynamics (radiation-MHD) modeling is carried out to study the hydrodynamics and magnetic fields in the shock-shear derived platform. Here, simulations indicate that fields of tens of Tesla can be generated via the Biermann battery effect due to vortices and mix in the counterpropagating shock-induced shear layer. Synthetic proton radiography simulations using MPRAD and synthetic X-ray image simulations using SPECT3D are carried out to predict the observable features in the diagnostics. Quantifying the effects of magnetic fields in inertial confinement fusion and high-energy-density plasmas represents frontier research that has far-reaching implications in basic and applied sciences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Hydrogen trapping energetics at BCC iron-helium interfaces

Density functional theory (DFT) calculations have been performed to assess the trapping and segregation strength of hydrogen (H) to helium (He) interfaces in BCC (Fe) as a function of He density and surface orientation. The He density ranges from 0 to 2 He/V which corresponds to equilibrium bubbles that are expected to form in the structural components in a fusion reactor environment. The DFT calculations consist of a slab of BCC metal and an initial lattice of FCC He. Here, the report on the binding energy of H to these interfaces as well as the migration barriers into and away from the surface, which together provide information on the de-trapping energy for H at He bubbles. It was found that the binding energy of H to He-Fe interfaces decreases with increasing He density. Migration barriers are also modified due to the He density, which are sensitive to the surface orientation as well as the diffusion pathway. These results provide valuable first-principles energetics that are necessary for higher-order, mesoscale models, and provide insight into the extent to which He bubbles may trap tritium in fusion structural materials.

42 ENGINEERING↗
DOE OSTI2023

Thermal transport in warm dense matter revealed by refraction-enhanced x-ray radiography with a deep-neural-network analysis

Abstract Transport properties of high energy density matter affect the evolution of many systems, ranging from the geodynamo in the Earth’s core, to hydrodynamic instability growth in inertial confinement fusion capsules. Large uncertainties of these properties are present in the warm dense matter regime where both plasma models and condensed matter models become invalid. To overcome this limit, we devise an experimental platform based on x-ray differential heating and time-resolved refraction-enhanced radiography coupled to a deep neural network. We retrieve the first measurement of thermal conductivity of CH and Be in the warm dense matter regime and compare our measurement with the most commonly adopted models. The discrepancies observed are related to the estimation of a correction term from electron-electron collisions. The results necessitate improvement of transport models in the warm dense matter regime and could impact the understanding of the implosion performance for inertial confinement fusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

ATHENA: A unique radiation environment platform at the National Ignition Facility

This paper describes the ATHENA platform, an energy tuning assembly, which was developed to spectrally shape the National Ignition Facility (NIF) deuterium–tritium fusion neutron source to a thermonuclear (fusion) plus prompt fission neutron spectrum with a capability to act as a short-pulse neutron source. This unique, otherwise inaccessible radiation environment complements existing experimental facilities and capabilities. Here, the flexible ATHENA irradiation positions were modeled using an ensemble of Monte Carlo simulations with stochastic sampling of the nuclear cross-sections to characterize the radiation environments and uncertainty for the platform. Validation of the internal neutron spectrum produced from fielding ATHENA at NIF occurred through neutron flux unfolding with 20 measured activation products.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Use of tritium-rich fuel to improve the yield of layered deuterium/tritium inertial fusion capsules

In deuterium–tritium (DT) ice layered implosions, nearly all hot spot mass at peak burn comes from the dense fuel. Accurate prediction of the fuel mass ablation, including the enthalpy associated with mass inflow into the hot spot from the dense fuel, is essential to understanding the energetics and ignition of the hot spot in layered implosions. A recently published boundary layer analysis (Daughton et al., 2023) indicates a faster mass ablation rate than in previous analyses of layered implosions. Inclusion of this effect provides a better match to simulations and leads to a new ignition threshold where the temperature of the dense fuel plays a critical role. This analysis motivates possible new directions for improved capsule performance. Here, the authors present evidence in support of one such approach: the use of tritium-rich ice to decrease 14 MeV neutron scattering and heating of the dense fuel, resulting in less mass ablation and more robust burn of the hot spot. It is found from numerical simulations that despite a less favorable D:T ratio in the ice, the use of a 40:60 D:T ratio leads to an increase in capsule yield of 17% percent compared with that of a 50:50 D:T ratio fuel for capsules resembling those of the recent N210808 ignition experiment on the NIF (Abu-Shawareb et al., 2022) and an increase of 74% compared with that of a 60:40 D:T ratio fuel capsule. Finally, these results are potentially important for modeling all layered implosions, since some degree of DT fractionization may arise naturally during the beta layering process. In addition, this physics is important for the feasibility of high-gain capsule designs that seek to minimize tritium usage, as in some inertial fusion energy concepts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗