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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Building Inclusive Educational and Career Pathways in Fusion Energy

This paper was written in preparation for the Workforce Accelerator for Fusion Energy Development conference, which was funded by the National Science Foundation. Prior to the conference, participants from academia, government, industry, national laboratories, and nonprofit organizations worked together to write White papers. Held in Hampton, Virginia, in May 2024, the conference convened participants to discuss various topics in support of workforce development in fusion energy. As the fusion industry expands, efforts to recruit and retain a diverse workforce, ensure equitable access to fusion education, and gain public support will be critical to meeting workforce needs in this field. We outline strategic recommendations across three vital areas: improving diversity data collection; supporting career advancement and retention with a diversity, equity, inclusion, accessibility, and belonging focus; and strengthening community engagement and education in fusion energy.

Cote, Laleh [Lawrence Berkeley National Laboratory↗
DOE OSTI2020

Analytic fits to atom-in-jellium shear modulus predictions

Fits to AJ shear modulus calculations from ρ0 to the limit of the corresponding AJ EOS table (usually 1000 ρ0), adjusted to reproduce STP shear modulus where possible. Fitting minimized the fractional difference, so low-pressure points would be reproduced accurately despite the wide-ranging tabulation. AJ calculations were at T=0. Isochoric variation G(T) has been small for all cases spot-tested so far, and may have either sign. The fitted equation usually matches the AJ data to within a few percent. Between numerical noise in the AJ calculation and probably-physical structure not captured by the equation, the deviation could be up to 20% in some places in most models, and 30% in a few. AJ does not capture structural phase transitions or phases stabilized by directional bonds, where the shear modulus may vary by a greater amount. Where possible, STP ρ,G were used as parameters, and low pressure AJ points were de-weighted or removed if necessary. Otherwise, such as where AJ fails to capture solid phases with a significantly different shear modulus, the AJ data were fitted as far down in pressure as possible, G0 was also fitted if necessary, and ρ0 was also adjusted if needed to keep G0>0. The resulting models are not intended for use at low pressure, though some are probably adequate for practical purposes

36 MATERIALS SCIENCE↗
DOE OSTI2022

Physics-based model of irradiation creep for ferritic materials under fusion energy operation conditions

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this paper, we develop a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. Here, we carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum with average recoil energies of 20 keV and a damage dose rate of ≈3×10 –7 dpa/s at temperatures between 300 and 800 K.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Renewable low-Z wall for fusion reactors with built-in tritium recovery (Final Technical Report)

This project pursued development of a novel renewable plasma-facing wall technology for fusion reactors. The technology is based on a slurry which can be easily delivered by delivery tubes to the reactor wall. The slurry dries at the hot reactor wall into pebble rods which are extruded out into the hot plasma, where the pebbles break off and fall along the reactor wall and can be recovered by gravity and re-used. The falling pebbles carry away heat and tritium and also protect the wall against large scale erosion or redeposition of material. The research focused on carbon-based pebble rods and demonstrated that pebble rods could be produced from slurry with tolerable levels of outgassing on a reactor-relevant timescale (< 5 minutes). Steady-state handling of reactor relevant (up to 50 MW/m 2 ) normal-incidence heat loads was demonstrated. Pebble release velocities were found to be sufficiently small (< 1 m/s) to allow recovery below the vacuum chamber. Tunability of the pebble rod breaking rate was demonstrated by changing the fill fraction of the interpebble matrix which binds the pebbles together. This work could benefit the public by helping move forward the design of commercially viable fusion energy reactors. Designing a first wall for magnetic fusion reactors which can handle the huge heat loads present and also avoid buildup of tritium-containing deposits is extremely challenging and requires novel approaches like the one being investigated here.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Thermochemical Data Fusion Using Graph Representation Learning

Large databases are required for “Big Data” applications in catalysis and materials science. Thermochemical databases can be created by combining data from various sources and by correcting low-fidelity datasets to higher accuracy with minimal computation. To achieve this “data fusion”, thermochemical quantities of interest, calculated at various levels of density functional theory (DFT), need to be mapped to the same, high levels of theory. In this work, a graph theoretical, statistical framework is proposed for such tasks. Subgraph frequencies are shown to provide a natural representation for learning these fusion maps. The maps are linear and are learnt with automated descriptor selection. Using a dataset of as few as ~1% from the QM9 database of 133,885 molecules, these models can predict multiple thermochemical quantities at a higher level of theory with an accuracy of 1 kcal/mol. Here, the method is explainable, generalizable, and provides a diagnostic tool for outlier identification

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Elucidating hydrogen isotope transport mechanisms in proton-conducting ceramics with trapping effects using TMAP8

Hydrogen isotopes play an central role in many science and engineering applications such as fuel cells, hydrogen production, and fusion energy. For these applications, hydrogen separation and extraction applications are pivotal aspects of hydrogen transports, where proton-conducting ceramics (PCCs) have shown great potential. In this study, we propose a new model for hydrogen isotope transport in PCC materials, BaZr 0.9 Y 0.1 O 2.95 (BZY) in particular, which captures behavior in both dry and wet environments. The model expands previous efforts and considers diffusion, trapping, and surface reactions (i.e., dissociation and recombination). We then validate and calibrate the model using deuterium transport measurements from experiments in both dry and wet environments. This study highlights the key role of trapping, often neglected, on hydrogen isotope transport in BZY and other PCC materials. It also explains how the commonly observed discrepancy between dry and wet behavior can be attributed to more active surface reactions and saturated traps due to the increased hydrogen presence under the wet environment. These results provide insights to optimize PCC manufacturing and usage as a hydrogen separation and extraction technology in various fields, emphasizing that lowering the trapping can reduce hydrogen isotope retention. These modeling and calibration efforts are performed using the tritium migration analysis program, version 8 (TMAP8), an open-source application designed for hydrogen isotope transport.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Real-time observation of toroidal current redistributions induced by three-dimensional MHD phenomena triggering vertical displacement events in tokamak plasmas

Three-dimensional MHD instabilities, including edge-localized modes (ELMs) and internal reconnection events (IREs), have been observed to precipitate loss of vertical stability in tokamak plasmas, resulting in vertical displacement events (VDEs). This vertical destabilization can occur due to toroidal current redistributions and/or shape changes resulting from these phenomena. Using a recently introduced method for rapidly reconstructing the two-dimensional toroidal plasma current density profile in real-time, results are presented that demonstrate the specific current distribution changes that occur during ELMs (on KSTAR) and IREs (on MAST-U) that lead to loss of vertical control. The method most efficiently reconstructs the toroidal current density profile by doing so on a basis of principal components of historical profiles. These principal components isolate dominant current profile dynamics, improving interpretability, increasing speed, and reducing dimensionality of the profile computation. On KSTAR, this computation is executed in the real-time plasma control system at a rate of 10 kHz (limited by available CPU cycle times), allowing the current profile evolution to be assessed at several times over the course of each ELM event. Further, by incorporating the reconstructions into a novel vertical stability metric, the contribution of specific current profile dynamics to the loss of vertical stability can be assessed in real-time for VDE avoidance and improved understanding of the causal relationship between three-dimensional MHD phenomena and VDEs. The success of this method in approximating toroidal current density profiles from kinetic equilibrium reconstructions is also presented ($R^2=0.990$), along with its capability to produce other equilibrium quantities of interest in real-time at high time resolution.

edge-localized modes↗
DOE OSTI2021

The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems

We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sensor fusion of pyrometry and acoustic measurements for localized keyhole pore identification in laser powder bed fusion

We report in-situ process monitoring as an aid to part qualification for laser powder-bed fusion (L-PBF) technology is a topic of increasing interest to the additive manufacturing community. In this work, airborne acoustic and inline pyrometry measurements were recorded simultaneously with the laser position. X-ray radiography imaging was used to spatio-temporally register keyhole pore locations to the pyrometry and acoustic signals, enabling binary labeling of data partitions based on pore formation. These labeled partitions were subsequently featurized using a highly comparative time-series analysis toolbox. Acoustic data was found to be much more effective than the pyrometry data for keyhole pore identification. However, when the information contained in both sensing modalities was combined in a sensor fusion strategy, the error rates of the top performing models were significantly reduced.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A new discovery of edge localized modes suppression using ICRH

Here, the high-confinement mode (H-mode) is very important for the fusion performance of ITER and future fusion reactors. The H-mode pedestal is a region featuring strongly reduced turbulence and transport just inside the limiting flux surface with strong plasma gradients, which drive edge localized modes (ELMs) in tokamaks. The ELMs, however, are quasiperiodic relaxations of the pedestal, resulting in a series of hot plasma eruptions similar to magnetospheric substorms, solar and stellar flares, which could potentially damage the ITER divertor plates and first walls. To mitigate and suppress the ELMs in H-mode plasmas, the fusion community has tried to develop effective actuators over the past two decades. Two separate excellent inventions have been awarded to recognize their achievements. The 2018 APS excellence award in Plasma Physics Research was given to Drs. Todd E. Evans, Max E. Fenstermacher, and Richard Alan Moyer for their first experimental demonstration of the stabilization of ELMs in high-confinement diverted discharges by application of very small edge-resonant magnetic perturbations, which led to the adoption of suppression coils in the ITER design. The 2018 Fusion Technology Award from the IEEE’s Nuclear and Plasma Science Society (NPSS) was given to Dr. Larry Baylor for his work designing the fueling, pumping and disruption mitigation system for the US ITER Project and for the implementation of pellet ELM mitigation for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Lithium–Divertor Interactions and Helium/Hydrogen Trapping in Lithiated Metals (Final Technical Report)

The goal of this project was to develop a fundamental understanding of helium and hydrogen behavior in lithium, both in bulk and at interfaces with tungsten, in order to inform the design of lithium based plasma facing components for fusion devices. Over the course of the award, the project produced the first comprehensive, peer reviewed dataset describing helium energetics, migration behaviors, and defect interactions in lithium. The research demonstrated that helium behaves in ways not previously observed in any other body centered cubic (BCC) metal: its interstitial configurations are more stable than substitutional ones, and its migration barriers are extraordinarily low, in some cases more than an order of magnitude below those in tungsten or iron. These discoveries reveal that helium in lithium diffuses so rapidly that its transport may be dominated by translational motion rather than the vibrationally activated mechanisms that underpin conventional solid state diffusion. This work lays a scientific foundation for understanding gas retention, bubble formation, and wall evolution in lithium based fusion environments and provides new computational tools, most notably a newly developed Li–He interatomic potential, for advancing future modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluating the Impact of Tritium Permeation Membrane Performance and Direct Internal Recycling on Fusion Fuel Cycle Efficiency Using TMAP8

An efficient fuel cycle is vital to sustainable and cost-effective energy generation in fusion systems. Since tritium is not widely available, fusion systems must breed their own tritium for sustainable fusion deuterium-tritium reactions. An inefficient fuel cycle increases the tritium inventory needed for operations, which increases costs, constraints on tritium management systems, and safety concerns. A fuel cycle model is a powerful tool for understanding tritium inventories and flow rates across all systems in the fuel cycle. By simplifying the technical details into time-dependent tritium flow rates and inventories, the model can simulate the entire fuel cycle with high computational efficiency, even for technologies that are still under development. It can therefore quantify the impact of new tritium management technologies on fuel cycle efficiency. To evaluate the impact of key components on reducing tritium inventory, we are using and expanding an existing fuel cycle models based on latest advancements in fuel cycle research. The new model integrates Tritium Permeation Membrane (TPM) and Direct Internal Recycling (DIR) to enhance tritium transport from blanket breeders and plasma exhaust. These fuel cycle models are implemented in TMAP8 (Tritium Migration Analysis Program, version 8), a MOOSE-based open-source application designed to provide cutting-edge capabilities for tritium transport and fuel cycle modeling. The study aims to demonstrate the extensibility of existing fuel cycle modeling capability in TMAP8 and to offer a proof-of-principle design for future fusion plant systems. The presentation will cover the performance of fuel cycle modeling capabilities available in TMAP8, highlight advancements in fuel cycle research, and present a sensitivity analysis of these models. The results underline potential approaches and technology solutions to lower tritium inventory requirements, highlighting their role in shaping the future of fusion energy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Deep-Learning-Based Segmentation of Keyhole in In-Situ X-ray Imaging of Laser Powder Bed Fusion

In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality. The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images. The presented tool shows promising average accuracy of 91.24% for keyhole area, and 92.81% for boundary shape, for a range of test dataset conditions in Al6061 (and one AliSi10Mg) alloys, with 300 training images/labels and 100 testing images for each trial. Prospective users may apply the presently trained tool or a retrained version following the approach used here to automatically label keyhole shapes in large image sets.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fusion Materials Research at Oak Ridge National Laboratory in FY2019

This is the eighth Annual report of the Oak Ridge National Laboratory (ORNL) program aimed at developing and qualifying materials that can meet the application requirements of fusion power systems, especially the near-plasma regions of those systems. Earlier issues of these annual reports can be found at the Fusion Materials Program website; more detailed reporting for those and many earlier years are contained in the series of Semiannual Progress reports at the same website, and the detailed results of the program are contained in the published scientific literature.

36 MATERIALS SCIENCE↗