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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Collaboration Website for Muon Catalyzed Fusion and Muon Beam Production

This project sets up a website to support the nascent Muon Catalyzed Fusion collaboration including development of particle accelerators and transport beamlines for muon beams. The website is envisioned as having the general public information pages and private pages for collaboration members. Multimedia elements like images, text animations, and video lectures, covering a broad spectrum of topics will populate the educational site, covering muon facilities, to comprehensive explorations and seminal documents that define the science of Muon Catalyzed Fusion, Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes. Ensuring compatibility across devices and operating systems, it also features integration with Google Docs for collaboration, a code repository (GitHub), a blog platform with comments (WordPress), the potential for ChatGPT integration and interactive graph plotting with Python Plotty to enhance data visualization. This project will maintain public and protected private pages, due to the proprietary nature of the work or research in progress. The public sections will be built to foster dissemination of information and highlight recent work within the NK Labs collaboration, including lectures, published papers, and regular blog posts with open commenting. The private section will support unpublished or nonpublic research, by facilitating collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. Ultimately, this project strives to make complex scientific knowledge more accessible to the public, foster enhanced collaboration, and serve as a platform for sharing cutting-edge research in Muon Catalyzed Fusion and Accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Remote operation of the DIII-D National Fusion Facility

Abstract Full remote scientific operation of the DIII-D National Fusion Facility is now possible through significant advances in the computer science hardware and software infrastructure made over the last decade. Capabilities around information visualization, data movement, and communication have all been enhanced. The level of capability deployed to remotely operate DIII-D required an infrastructure advancement over what had previously been achieved in the fusion community. The large quantity of real-time data that is automatically displayed on DIII-D’s control room screens can now be visualized by remote participants via web-based applications. New audio/video solutions using the VoIP and instant messaging application Discord have been implemented to mimic the dynamic and ad-hoc scientific conversations that are critical in successfully operating an experimental campaign. Discord’s ability for a user to rapidly move between audio channels, text with images, and share screens is a significant enhancement over traditional videoconferencing tools. In addition, multiple combinations of broadcast audio are made available via a web-based application to allow remote participants to simultaneously listen to general announcements/sounds while conducting their own specific conversations. Secure methodologies have been put into place to allow remote control of hardware including DIII-D’s plasma control system application. Secure methods also included the ability of the on-site team to closely coordinate their work with remote team members which has been enhanced through extensions to the wireless network and the use of tablet computers for audio/video/screen sharing. However, no amount of software can fully replace the need for ‘hands on hardware.’ This infrastructure was severely stress tested during the COVID-19 pandemic where occupancy of the DIII-D control room was restricted. Operational efficiency during the pandemic, measured in discharges per hour, remained high (3.8 ± 0.8) compared to values obtained pre-pandemic (3.7 ± 0.8).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Center for Integrated Simulation of Fusion Relevant RF Actuators

This project was part of the “Center for Integrated Simulation of Fusion Relevant RF Actuators” SciDAC-4 project, led by Dr. Paul Bonoli (MIT). Rather than use an acronym (CISFRRFA), the project will be referred to in this document as the “RF-SciDAC4”. The larger SciDAC-4 project goals were to: 1. Develop an integrated simulation of the antenna + sheath + scrape-off-layer + core plasma system which fully utilizes leadership class computing resources to move towards a quantitative predictive capability for the response to RF power. 2. Work closely with the SciDAC-4 Whole Device Modeling (WDM) community to make both our new code development efforts, as well as the established hierarchy of RF tools, available within their environment, and to utilize WDM technologies to implement the couplings below. 3. Validate this predictive capability on appropriately diagnosed experiments including dedicated RF test stands, linear devices, and existing tokamaks. 4. Use these tools to inform design of robust, impurity-mitigating RF heating and current drive sources for future fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Global Carbon Monoxide Products from Combined AIRS, TES and MLS Measurements on A-Train Satellites

This study tests a novel methodology to add value to satellite data sets. This methodology, data fusion, is similar to data assimilation, except that the background modelbased field is replaced by a satellite data set, in this case AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) measurements. The observational information comes from CO measurements with lower spatial coverage than AIRS, namely, from TES (Tropospheric Emission Spectrometer) and MLS (Microwave Limb Sounder). We show that combining these data sets with data fusion uses the higher spectral resolution of TES to extend AIRS CO observational sensitivity to the lower troposphere, a region especially important for air quality studies. We also show that combined CO measurements from AIRS and MLS provide enhanced information in the UTLS (upper troposphere/lower stratosphere) region compared to each product individually. The combined AIRS-TES and AIRS-MLS CO products are validated against DACOM (differential absorption mid-IR diode laser spectrometer) in situ CO measurements from the INTEX-B (Intercontinental Chemical Transport Experiment: MILAGRO and Pacific phases) field campaign and in situ data from HIPPO (HIAPER Pole-to-Pole Observations) flights. The data fusion results show improved sensitivities in the lower and upper troposphere (20-30% and above 20%, respectively) as compared with AIRS-only version 5 CO retrievals, and improved daily coverage compared with TES and MLS CO data.

combined AIRS↗
DOE OSTI2021

Upgrade of the Materials Analysis Particle Probe (MAPP-U) to decipher the impact of lithium-based surfaces on NSTX-U plasma behavior

Understanding the plasma wall interaction (PWI) remains a critical issue for the feasibility of thermonuclear magnetic fusion energy solutions. Key issues with PWI mechanisms in fusion tokamak reactors include: evolution of surface chemistry and its role on hydrogen retention. In particular how low-Z coatings such as lithium can impact the behavior of plasma at the edge and in the core. PMI (plasma-material interactions) are particularly important for strategies that involve low-recycling regimes and the use of lithium PFS (plasma-facing surfaces) to attain them, as in the case of NSTX-U. Recent reports have indicated the importance of access to the evolving plasma-facing surface during and in-between plasma discharges. Changes in surface chemistry and morphology due to ion bombardment and the difficulty of diagnosing plasma-facing surfaces, especially reactive surfaces, complicate the development of a predictive understanding of the wall and its interaction with the plasma. Consequently, this impairs the ability to design advanced PFC materials for future plasma-burning fusion reactors and appropriate PMI code validation. The Materials Analysis Particle Probe (MAPP) is an established and on-going PMI probe diagnostic system compatible with the highly chemically reactive system of lithium and boron coatings adopted by the NSTX-U research program. MAPP is the first PMI diagnostic to capture the surface physics and chemistry in-vacuo in a fusion tokamak system and correlate this data to controlled plasma shots. Currently MAPP captures this information at a fixed radial location at the NSTX-U outboard divertor region. The MAPP diagnostic has enabled understanding of the near-surface and surface chemistry of complex evolving lithiated and borated carbon-based PFC surfaces retention and transport of hydrogen. Coupled to atomistic simulations in collaboration with P. Krstic of Stony Brook U. MAPP has been very successful in achieving high-impact scientific research in its current grant period evidenced by two invited review articles and over 20 peer-reviewed manuscripts and over 40 contributed and invited presentations at both national and international conferences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

AEPF: Attention-Enabled Point Fusion for 3D Object Detection

Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources. With separate 2D and 3D feature extraction backbones, feature fusion can become more challenging as these modes generate different gradients, leading to gradient conflicts and suboptimal convergence during network optimization. To this end, we propose a 3D object detection method, Attention-Enabled Point Fusion (AEPF). AEPF uses images and voxelized point cloud data as inputs and estimates the 3D bounding boxes of object locations as outputs. An attention mechanism is introduced to an existing feature fusion strategy to improve 3D detection accuracy and two variants are proposed. These two variants, AEPF-Small and AEPF-Large, address different needs. AEPF-Small, with a lightweight attention module and fewer parameters, offers fast inference. AEPF-Large, with a more complex attention module and increased parameters, provides higher accuracy than baseline models. Experimental results on the KITTI validation set show that AEPF-Small maintains SOTA 3D detection accuracy while inferencing at higher speeds. AEPF-Large achieves mean average precision scores of 91.13, 79.06, and 76.15 for the car class’s easy, medium, and hard targets, respectively, in the KITTI validation set. Results from ablation experiments are also presented to support the choice of model architecture.

Chemistry↗
DOE OSTI2026

In-situ synchrotron X-ray investigation of phase evolution in gas atomized powder enabling manufacturing of nanoscale oxide-dispersion strengthened ferritic steels

Here, we present an investigation of Fe-14Cr-3W-0.4Y-0.4Zr-0.18Ti (wt.%) as a reduced-activation oxide-dispersion strengthened (ODS) ferritic steel, an alternative to the “14YWT” structural alloys designed for nuclear energy applications. Gas atomization reaction synthesis (GARS) was used to produce these Zr-modified powders with a non-equilibrium (metastable) phase that enable a heat treatment (delayed) route for producing nanoscale oxide-dispersion strengthening. In situ synchrotron X-ray diffraction and transmission electron microscopy were used to analyze phase evolution as a function of temperature and time, revealing formation of highly dispersed oxide nanoprecipitate phases at temperatures above those needed for powder consolidation and shaping of components. This would allow fabrication of net-shape parts using conventional powder-processing methods prior to thermal activation of a reaction producing nanocrystalline Y-(Ti, Zr)-O particles, with a size of 20 ± 7 nm. These results can inform processing of tubes, cladding, sheets, and plates for use in advanced fission and fusion reactors.

In-situ synchrotron X-ray diffraction↗
DOE OSTI2024

Imaging 3D chemistry at 1 nm resolution with fused multi-modal electron tomography

Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment is completed. Even larger doses are required to achieve high resolution. Thus, chemical mapping in 3D has been unachievable except at lower resolution with the most radiation-hard materials. Here, high-resolution 3D chemical imaging is achieved near or below one-nanometer resolution in an Au-Fe 3 O 4 metamaterial within an organic ligand matrix, Co 3 O 4 -Mn 3 O 4 core-shell nanocrystals, and ZnS-Cu 0.64 S 0.36 nanomaterial using fused multi-modal electron tomography. Multi-modal data fusion enables high-resolution chemical tomography often with 99% less dose by linking information encoded within both elastic (HAADF) and inelastic (EDX/EELS) signals. We thus demonstrate that sub-nanometer 3D resolution of chemistry is measurable for a broad class of geometrically and compositionally complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cherenkov Gamma Ray Detectors on High-Energy-Density Systems

Cherenkov gamma ray detectors are a valuable diagnostic technique for HED systems. Inertial confinement fusion is working towards high gain ignition. Gamma rays from ICF systems can help inform the degradation mechanisms preventing ignition: Carbon ablator is not being degraded, unlike the DT fuel; carbon γ timing can estimate shell energy during bangtime and may suggest hot spot cooling rate; and Cherenkov detectors are also used for high spatial and temporal resolution ICF mix studies on OMEGA. Cherenkov systems also inform energy spectrum of radiographic sources: ARC laser and Mercury pulsed power machine.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Informing ARC divertor design and plasma facing material selection through integrated modeling

This INFUSE 2023 project between UCLA and Commonwealth Fusion Systems used computer modeling to test whether tungsten materials can survive in CFS's ARC fusion reactor divertor. The team simulated plasma conditions and material responses, finding that tungsten-rhenium alloys resist grain growth better than pure tungsten, and that hydrogen buildup depends more on particle flux than temperature. The work helps CFS design durable plasma-facing components for their fusion power plant.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Thermal and Nonthermal Electron-ion Bremsstrahlung Spectrum from High-Temperature Plasmas

Electron-ion bremsstrahlung radiation from high-temperature plasmas is investigated. The first- and second-order Coulomb corrections in the nonrelativistic bremsstrahlung radiation power are obtained by the Elwert-Sommerfeld factor. In this paper, two cases of the electron distributions, the thermal and nonthermal power-law distributions, are considered. The inclusion of Coulomb corrections is necessary in deducing correctly the electron distribution function from radiation data. These results provide the correct information of electron distributions in high-temperature plasmas, such as in inertial confinement fusion plasmas and in the astrophysical hot thermal and nonthermal x-ray sources.

Jung, Young-Dae↗
NASA NTRS2019

Covariance Realism Is Not Enough

A great deal of effort has been put into improving the practice of space situational awareness such that covariance data associated with predicted close approaches is more “realistic.” However, “realistic” usually has meant “larger” and this presents a problem. In many cases, there exist multiple sources for predictive ephemerides, which may be fused to produce predictive states with smaller associated covariances. Ancillary to the fusion computation is the capability to assess consistency of the estimates. If actionable covariance information becomes available, interval estimates for the miss distance provide a more informative alternative to collision probability for risk assessment.

Carpenter, J. Russell↗
NASA NTRSDate not supplied

Traffic Prediction for Uncommunicative Aircraft in Terminal Airspace: Development Framework and Performance Evaluations

This paper presents an air traffic prediction algorithm that takes observations of an aircraft and classifies aircraft type, estimates the aircraft's intent to and method of joining an airport traffic pattern, and predicts the aircaft's future trajectory. To develop algorithms that enable autonomous aircraft to safely insert into un-towered traffic patterns, several challenges need to be addressed. These challenges range from traffic detection to sensor fusion to own-ship trajectory replanning. Critical to a trajectory replanning algorithm is information regarding the future behavior of all traffic aircraft in the operational environment. The presented traffic prediction algorithm generates this information using regular measurements of traffic aircraft position and velocity to classify the aircraft by speed-class, estimate how the aircraft will approach the runway, and construct a predicted trajectory to the runway including future positions and velocities at specific times. The predictions of the presented algorithm are the necessary inputs for any downstream traffic pattern sequencing and own-ship trajectory planning routines. The presented algorithm is benchmarked using approximately 300 randomized traffic trajectories, spanning four vehicle weight classes and eight traffic entry types. While the algorithm can process multiple traffic vehicles in the terminal area, there is no prediction of traffic-on-traffic interaction. Each traffic vehicle is processed separately.

John D McMinn↗
DOE OSTI2024

Measuring 3D Chemistry at 1 nm Resolution with Fused Multi-Modal Electron Tomography

Measuring the three-dimensional (3D) distribution of chemistry in nanoscale matter is a longstanding challenge for metrological science. The inelastic scattering events required for 3D chemical imaging are too rare, requiring high beam exposure that destroys the specimen before an experiment is completed. Even larger doses are required to achieve high resolution. Thus, chemical mapping in 3D has been unachievable except at lower resolution with the most radiation-hard materials. Here, high-resolution 3D chemical imaging is achieved near or below one-nanometer resolution in an Au-Fe3O4 metamaterial within an organic ligand matrix, Co3O4-Mn3O4 core-shell nanocrystals, and ZnS-Cu0.64S0.36 nanomaterial using fused multi-modal electron tomography. Multi-modal data fusion enables high-resolution chemical tomography often with 99% less dose by linking information encoded within both elastic (HAADF) and inelastic (EDX/EELS) signals. We thus demonstrate that sub-nanometer 3D resolution of chemistry is measurable for a broad class of geometrically and compositionally complex materials.

Schwartz, Jonathan↗
NASA NTRS1992

Proliferation and performance of hybridoma cells in microgravity (7-IML-1)

The purpose of this experiment is to study how cell performance (biosynthesis and secretion) is altered by altered gravity conditions. Hybridoma cells are obtained by fusion of an activated B-lymphocyte with a myeloma cell. Activated B-lymphocytes, derived from a human or an animal, carry the information required to produce antibodies of a certain specificity and can survive only a few days in culture. Myeloma cells are tumor cells which can grow indefinitely in culture. Therefore, the product of the fusion is an immortal cell line capable of producing homogeneous antibodies (monoclonal antibodies). Experimental procedures are explained in some detail.

Cogoli, Augusto↗
NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST toreduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗
NASA NTRSDate not supplied

Multiclass Flight Anomaly Detection Using Sensor Fusion Based on Dempster-Shafer Theory

As aviation systems in commercial operations continue to grow in complexity, the anomalies exhibited by these systems become more elaborate and difficult to detect. To address the challenge of detecting these complex anomalies, deep learning models have been used extensively in aviation anomaly detection studies, at the expense of end-user interpretability. Aiming to maintain the same level of interpretability as traditional threshold-exceedance methods, we continue our development of prediction models using ordinal patterns and their distributions throughout the flight. Specifically, this study extends our work into multiclass anomaly detection using sensor fusion based on Dempster-Shafer theory (DST), a second-order probability theory used to combine information from different sources of evidence. Our approach uses DST to reduce the uncertainty in the class predictions of an ensemble of classifiers. These classifiers rely on the similarity between flight data and class templates to make a prediction of the state of the aircraft. Our approach aims to take advantage of simple models trained on interpretable features (ordinal patterns) to correctly predict an anomaly and identify the flight dynamics linked to the anomaly. Our results show an improvement when using DST-based sensor fusion over simple majority voting. Additionally, our results provide insight into aircraft states linked to rare high-risk anomalies.

Risk detection↗