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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Co-op at Sandia National Laboratories (July - December 2019, Final Report)

This co-op was performed at Sandia National Laboratories (SNL) within the Weapon Surety Engineering 11 Department (9435), which is a customer-focused organization that provides engineering and system analysis expertise to ensure a safe deterrent throughout the entire weapon lifecycle. Engineers in 9435 develop a deep knowledge in both component and system function to support rigorous evaluation and mitigation of potential failure modes. They operate across multiple engineering disciplines (mechanical, electrical, computer, materials and systems engineering) with opportunities to develop crossdisciplinary capability. The team supports a variety of stockpile systems and is part of the product teams during development, design and production, as well as advanced concept and exploratory efforts. 9435 engineers use their extensive component and system knowledge, as well as experimental data and modeling, to ensure products function as intended with assured safety. Members of the department learn the function of multiple components, how those components integrate within the system and apply surety principles and processes to ensure a safe, secure, reliable, and effective U.S. nuclear deterrent.

42 ENGINEERING↗
DOE OSTI2023

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies

This report represents the milestone deliverable M2SF-23SN010301072 “Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies” The report provides a status update of FY23 activities for the work package Argillite Disposal work packages for the DOE-NE Spent Fuel Waste Form Science and Technology (SFWST) Program. Clay-rich geological media (often referred as shale or argillite) are among the most abundant type of sedimentary rock near the Earth’s surface. Argillaceous rock formations have the following advantageous attributes for deep geological nuclear waste disposal: widespread geologic occurrence, found in stable geologic settings, low permeability, self-sealing properties, low effective diffusion coefficient, high sorption capacity, and have the appropriate depth and thickness to host nuclear waste repository concepts. The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress (through experiment, modeling, and testing) in the study of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in clay/shale/argillaceous rock. International collaboration activities comprising field-scale heater tests, field data monitoring, and laboratory-scale experiments provide key information on changes to the engineered barrier system (EBS) material exposed high thermal loads. Moreover, consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the engineered barrier system (EBS) design concepts. Chemical and structural analyses of sampled bentonite material from laboratory tests at elevated temperatures are key to the characterization of thermal effects affecting bentonite clay barrier performance. The knowledge provided by these experiments is crucial to constrain the extent of sacrificial zones in the EBS design during the thermal period. Thermal, hydrologic, mechanical, and chemical (THMC) data collected from heater tests and laboratory experiments have been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches to assess issues on coupled processes involving porous media flow, transport, geomechanical phenomena, chemical interactions with barrier/geologic materials, and the development of EBS concepts. These lines of knowledge are central to the design of deep geological backfilled repository concepts where temperature plays a key role in the EBS behavior, potential interactions with host rock, and long-term performance in the safety assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

RANGERS: Methodology Report on Design and Performance Assessment of Engineered Barrier Systems in a Salt Repository for HLW/SNF

Salt formations are one of the potential host rocks for the final disposal of high-level radioactive waste (HLW) in deep geological repositories, both in Germany and the United States. The safe isolation of radioactive waste in these repositories relies on a multi-barrier system, combining engineered and natural barriers. The natural barrier is provided by the salt rock itself, known for its self-sealing properties and long-term stability. The engineered barrier, on the other hand, comprises sealing components strategically placed within the repository to enhance its containment capabilities. In both Germany and the United States, long-term safety assessments require demonstrating the integrity of the natural barrier for a period of up to 1 million years. Concurrently, the engineered barrier system (EBS) must maintain its structural and functional integrity until the long-term sealing, such as the granular salt backfill material, has re-consolidated to its final low porosity and permeability. Based on extensive expertise and experience with engineered barriers in salt formations, BGE TECHNOLOGY GmbH and Sandia National Laboratories have partnered to develop a robust methodology for the integrity and performance assessment of EBS in HLW repositories through the RANGERS project. This collaborative effort aims to establish a unified approach to geotechnical engineering, repository design, integrity and performance evaluation of EBS in salt repositories.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Automated, high-accuracy classification of textured microstructures using a convolutional neural network

Crystallographic texture is an important descriptor of material properties but requires time-intensive electron backscatter diffraction (EBSD) for identifying grain orientations. While some metrics such as grain size or grain aspect ratio can distinguish textured microstructures from untextured microstructures after significant grain growth, such morphological differences are not always visually observable. This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional neural network results are compared with a statistical Kolmogorov–Smirnov tests with traditional morphological metrics for describing microstructures. Results show that the convolutional neural network achieves a significantly improved classification accuracy, particularly at early stages of grain growth, highlighting the capability of deep learning to identify the subtle morphological patterns resulting from texture. The results demonstrate the potential of a convolutional neural network as a tool for reliable and automated microstructure classification with minimal preprocessing.

36 MATERIALS SCIENCE↗
DOE OSTI2017

ASPHERICITY, INTERACTION, AND DUST IN THE TYPE II-P/II-L SUPERNOVA 2013EJ IN MESSIER 74

SN 2013ej is a well-studied core-collapse supernova (SN) that stemmed from a directly identified red supergiant (RSG) progenitor in galaxy M74. The source exhibits signs of substantial geometric asphericity, X-rays from persistent interaction with circumstellar material (CSM), thermal emission from warm dust, and a light curve that appears intermediate between supernovae of Types II-P and II-L. The proximity of this source motivates a close inspection of these physical characteristics and their potential interconnection. We present multiepoch spectropolarimetry of SN 2013ej during the first 107 days and deep optical spectroscopy and ultraviolet through infrared photometry past ∼800 days. SN 2013ej exhibits the strongest and most persistent continuum and line polarization ever observed for a SN of its class during the recombination phase. Modeling indicates that the data are consistent with an oblate ellipsoidal photosphere, viewed nearly edge-on and probably augmented by optical scattering from circumstellar dust. We suggest that interaction with an equatorial distribution of CSM, perhaps the result of binary evolution, is responsible for generating the photospheric asphericity. Relatedly, our late-time optical imaging and spectroscopy show that asymmetric CSM interaction is ongoing, and the morphology of broad H α emission from shock-excited ejecta provides additional evidence that the geometry of the interaction region is ellipsoidal. Alternatively, a prolate ellipsoidal geometry from an intrinsically bipolar explosion is also a plausible interpretation of the data but would probably require a ballistic jet of radioactive material capable of penetrating the hydrogen envelope early in the recombination phase. Finally, our latest space-based optical imaging confirms that the late interaction-powered light curve dropped below the stellar progenitor level, confirming the RSG star’s association with the explosion.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

A 3-D Magnetic Analysis of a Stirling Convertor Linear Alternator Under Load

The NASA Glenn Research Center (GRC), the Department of Energy (DOE), and the Stirling Technology Company (STC) are developing Stirling convertors for Stirling Radioisotope Power Systems (SRPS) to provide electrical power for future NASA deep space missions. STC is developing the 55-We Technology Demonstration Convertor (TDC) under contract to DOE. Of critical importance to the successful development of the Stirling convertor for space power applications is the development of a lightweight and highly efficient linear alternator. This paper presents a 3-dimensional finite element method (FEM) approach for evaluating Stirling convertor linear alternators. The model extends a magnetostatic analysis previously reported at the 35th Intersociety Energy Conversion Engineering Conference (IECEC) to include the effects of the load current. STC's 55-We linear alternator design was selected to validate the model. Spatial plots of magnetic field strength (H) are presented in the region of the exciting permanent magnets. The margin for permanent magnet demagnetization is calculated at the expected magnet operating temperature for the near earth environment and for various average magnet temperatures. These thermal conditions were selected to represent a worst-case condition for the planned deep space missions. This paper presents plots that identify regions of high H where the potential to alter the magnetic moment of the magnets exists.

Geng, Steven M.↗
NASA NTRS2013

Advances in the Development of a WCl6 CVD System for Coating UO2 Powders with Tungsten

W-UO2 CERMET fuels are under development to enable Nuclear Thermal Propulsion (NTP) for deep space exploration. Research efforts with an emphasis on fuel fabrication, testing, and identification of potential risks is underway. One primary risk is fuel loss due to CTE mismatch between W and UO2 and the grain boundary structure of W particles resulting in higher thermal stresses. Mechanical failure can result in significant reduction of the UO2 by hot hydrogen. Fuel loss can be mitigated if the UO2 particles are coated with a layer of high density tungsten before the consolidation process. This paper discusses the work to date, results, and advances of a fluidized bed chemical vapor deposition (CVD) system that utilizes the H2-WCl6 reduction process. Keywords: Space, Nuclear, Thermal, Propulsion, Fuel, CERMET, CVD, Tungsten, Uranium

Mireles, Omar R.↗
NASA NTRS2013

Performance Characterization of the Air Force Transformational Satellite 12 kW Hall Thruster

The STMD GCD ISP project is tasked with developing, maturing, and testing enabling human exploration propulsion requirements and potential designs for advanced high-energy, in-space propulsion systems to support deep-space human exploration and reduce travel time between Earth's orbit and future destinations for human activity. High-power Hall propulsion systems have been identified as enabling technologies and have been the focus of the activities at NASA Glenn-In-house effort to evaluate performance and interrogate operation of NASA designed and manufactured Hall thrusters. Evaluate existing high TRL EP devices that may be suitable for implementation in SEP TDM.

Propulsion↗
NASA NTRSDate not supplied

Comparative Analysis of Thermal Conversion Technologies for Deep Space Missions

Radioisotope power systems (RPS) utilizing Plutonium-238 as a heat source for thermal-to-electric energy conversion have been used as a reliable power source for NASA’s deep space missions for sixty years. Recent innovations and improvements to thermal energy technologies show potential increases to radioisotope system efficiencies from current measurements of ~5-7% to efficiencies upwards of 20%. This report surveys and ranks recent, innovative thermal-to-electric energy conversion research technologies. Technologies being developed at universities and industry are compared with respect to thermal conversion method and relevant key performance parameters. Key performance parameters are identified as system specific power per kg, efficiency, power output, technology readiness level, and system mass. Analytical Hierarchy Process (AHP) was utilized to create weighted values for each evaluation criterion. The AHP tables combined with decision matrices create table scores for past, present, and potential future systems. The table score was combined with a conversion method score in an adjustable system to add value to flight-proven or well-tested thermal conversion technologies such as thermoelectrics. While the three highest-ranking systems reviewed are currently being developed by NASA’s RPS Program, the additional highest-ranking systems not under-development by RPS could warrant further research.

Radioisotope Power System↗
DOE OSTI2017

AN INDUCTIVE MAPPING WITH CONVOLUTIONAL REPRESENTATIONS FOR HUMAN SETTLEMENT DETECTION: PRELIMINARY RESULTS

Undoubtedly, deep convolutional learning methods continue to improve performance in image-level classification for computer vision and remote sensing applications. However, the spatio-temporal nature of remote sensing imagery offers other interesting challenges in multiscale image understanding. Emerging opportunities include seeking fine-grained and neighborhood mapping with overhead imagery. Limitations due to lack of relevant scale ground-truth often mandates that these challenges are pursued as disjoint. We test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate surprising potential on multiscale experiments that incorporate edge-level details up to semantic-level informationWe test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a novel unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate a preliminary inductive transfer learning potential on multiscale experiments that incorporate edge-level details up to semantic-level informationWe test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a novel unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate a preliminary inductive transfer learning potential on multiscale experiments that incorporate edge-level details up to semantic-level information.

Lunga, Dalton↗
DOE OSTI2017

Simulation of Deepwater Horizon oil plume reveals substrate specialization within a complex community of hydrocarbon degraders

The Deepwater Horizon (DWH) accident released an estimated 4.1 million barrels of oil and 10 1 0 mol of natural gas into the Gulf of Mexico, forming deep-sea plumes of dispersed oil droplets and dissolved gases that were largely degraded by bacteria. During the course of this 3-mo disaster a series of different bacterial taxa were enriched in succession within deep plumes, but the metabolic capabilities of the different populations that controlled degradation rates of crude oil components are poorly understood. We experimentally reproduced dispersed plumes of fine oil droplets in Gulf of Mexico seawater and successfully replicated the enrichment and succession of the principal oil-degrading bacteria observed during the DWH event. We recovered near-complete genomes, whose phylogeny matched those of the principal biodegrading taxa observed in the field, including the DWH Oceanospirillales (now identified as a Bermanella species), multiple species of Colwellia, Cycloclasticus, and other members of Gammaproteobacteria, Flavobacteria, and Rhodobacteria. Metabolic pathway analysis, combined with hydrocarbon compositional analysis and species abundance data, revealed substrate specialization that explained the successional pattern of oil-degrading bacteria. The fastest-growing bacteria used short-chain alkanes. The analyses also uncovered potential cooperative and competitive relationships, even among close relatives. We conclude that patterns of microbial succession following deep ocean hydrocarbon blowouts are predictable and primarily driven by the availability of liquid petroleum hydrocarbons rather than natural gases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2001

Approach and Issues Relating to Shield Material Design to Protect Astronauts from Space Radiation

One major obstacle to human space exploration is the possible limitations imposed by the adverse effects of long-term exposure to the space environment. Even before human spaceflight began, the potentially brief exposure of astronauts to the very intense random solar energetic particle (SEP) events was of great concern. A new challenge appears in deep space exploration from exposure to the low-intensity heavy-ion flux of the galactic cosmic rays (GCR) since the missions are of long duration and the accumulated exposures can be high. Since aluminum (traditionally used in spacecraft to avoid potential radiation risks) leads to prohibitively expensive mission launch costs, alternative materials need to be explored. An overview of the materials related issues and their impact on human space exploration will be given.

Wilson, J. W.↗
DOE OSTI2023

Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge

Elucidating protein–ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein–ligand interaction is traditionally tackled by molecular docking and simulation, which is based on physical forces and statistical potentials and cannot effectively leverage cryo-EM data and existing protein structural information in the protein–ligand modeling process. In this work, we developed a deep learning bioinformatics pipeline (DeepProLigand) to predict protein–ligand interactions from cryo-EM density maps of proteins and ligands. DeepProLigand first uses a deep learning method to predict the structure of proteins from cryo-EM maps, which is averaged with a reference (template) structure of the proteins to produce a combined structure to add ligands. The ligands are then identified and added into the structure to generate a protein–ligand complex structure, which is further refined. The method based on the deep learning prediction and template-based modeling was blindly tested in the 2021 EMDataResource Ligand Challenge and was ranked first in fitting ligands to cryo-EM density maps. These results demonstrate that the deep learning bioinformatics approach is a promising direction for modeling protein–ligand interactions on cryo-EM data using prior structural information.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Human Exploration of the Solar System by 2100

It has been suggested that the U.S., in concert with private entities and international partners, set itself on a course to accomplish human exploration of the solar system by the end of this century. This is a strikingly bold vision intended to revitalize the aspirations of HSF in service to the security, economic, and scientific interests of the nation. Solar system distance and time scales impose severe requirements on crewed space transportation systems, however, and fully realizing all objectives in support of this goal will require a multi-decade commitment employing radically advanced technologies - most prominently, space habitats capable of sustaining and protecting life in harsh radiation environments under zero gravity conditions and in-space propulsion technologies capable of rapid deep space transits with earth return, the subject of this paper. While near term mission destinations such as the moon and Mars can be accomplished with chemical propulsion and/or high power SEP, fundamental capability constraints render these traditional systems ineffective for solar system wide exploration. Nuclear based propulsion and alternative energetic methods, on the other hand, represent potential avenues, perhaps the only viable avenues, to high specific power space transport evincing reduced trip time, reduced IMLEO, and expanded deep space reach. Here, very long term HSF objectives for solar system wide exploration are examined in relation to the advanced propulsion technology solution landscape including foundational science, technical/engineering challenges, and developmental prospects.

Transportation↗
DOE OSTI2025

Deep learning-based spatio-temporal fusion for high-fidelity ultra-high-speed X-ray radiography

Full-field ultra-high-speed (UHS) X-ray imaging experiments have been well established to characterize various processes and phenomena. However, the potential of UHS experiments through the joint acquisition of X-ray videos with distinct configurations has not been fully exploited. In this paper, we investigate the use of a deep learning-based spatio-temporal fusion (STF) framework to fuse two complementary sequences of X-ray images and reconstruct the target image sequence with high spatial resolution, high frame rate and high fidelity. We applied a transfer learning strategy to train the model and compared the peak signal-to-noise ratio (PSNR), average absolute difference (AAD) and structural similarity (SSIM) of the proposed framework on two independent X-ray data sets with those obtained from a baseline deep learning model, a Bayesian fusion framework and the bicubic interpolation method. The proposed framework outperformed the other methods with various configurations of the input frame separations and image noise levels. With three subsequent images from the low-resolution (LR) sequence of a four times lower spatial resolution and another two images from the high-resolution (HR) sequence of a 20 times lower frame rate, the proposed approach achieved average PSNRs of 37.57 dB and 35.15 dB, respectively. When coupled with the appropriate combination of high-speed cameras, the proposed approach will enhance the performance and therefore the scientific value of UHS X-ray imaging experiments.

deep learning↗
DOE OSTI2017

Seasonal variation of shallow-to-deep convection transition and its link to the environmental conditions over the Central Amazon: Shallow-to-Deep Convection Transition

This study aims to characterize the seasonal variation of the shallow-to-deep convection transition and understand how environmental conditions impact the behavior of this transition using data collected from the Observations and Modeling of the Green Ocean Amazon (GOAmazon) field campaign in the Central Amazon (Manaus). The diurnal cycle of the rain/cloud fraction shows that the wet season has more extensive shallow convection before the transition to deep convection with larger fractional coverage and rainfall; deep convection in the transition season is more intense and has higher vertical extension and a stronger updraft. Surface meteorology, atmospheric moisture, instability, and wind shear are contrasted for the shallow/congestus convection (SC) cases and the locally formed shallow-to-deep convection transition (LD) cases. The comparisons suggest that occurrence of the LD is generally promoted under the conditions of high atmospheric moisture and instability but has a weaker dependence on wind shear. The relative importance of these environmental controls also varies in different seasons: The dry and transition seasons require a deeper moist layer from the boundary layer to midtroposphere than the wet season; convective available potential energy (CAPE) is higher during the transition season, but it is a less important factor for shallow-to-deep convection transition than in other seasons; LD only has significantly larger wind shears than SC during the dry season.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Radio frequency interference protection of communications between the Deep Space Network and deep space flight projects

The increasing density of electrical and electronic circuits in Deep Space Station systems for computation, control, and numerous related functions has combined with the extension of system performance requirements calling for higher speed circuitry along with broader bandwidths. This has progressively increased the number of potential sources of radio frequency interference inside the stations. Also, the extension of spectrum usage both in power and frequency as well as the greater density of usage at all frequencies for national and international satellite communications, space research, Earth resource operations and defense, and particularly the huge expansion of airborne electronic warfare and electronic countermeasures operations in the Mojave area have greatly increased the potential number and severity of radio frequency interference incidents. The various facets of this problem and the efforts to eliminate or minimize the impact of interference on Deep Space Network support of deep space flight projects are described.

Johnston, D. W. H.↗