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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Gap Analysis of Material Properties Data for Ferritic/Martensitic HT-9 Steel

The US Department of Energy (DOE), Office of Nuclear Energy (NE), is supporting the development of an ASME Code Case for adoption of 12Cr-1Mo-VW ferritic/martensitic (F/M) steel, commonly known as HT-9, primarily for use in elevated temperature design of liquid-metal fast reactors (LMFR) and components. In 2011, Los Alamos National Laboratory (LANL) nuclear engineering staff began assisting in the development of a small modular reactor (SMR) design concept, previously known as the Hyperion Module, now called the Gen4 Module. LANL staff immediately proposed HT-9 for the reactor vessel and components, as well as fuel clad and ducting, due to its superior thermal qualities. Although the ASME material Code Case, for adoption of HT-9 as an approved elevated temperature material for LMFR service, is the ultimate goal of this project, there are several key deliverables that must first be successfully accomplished. The most important key deliverable is the research, accumulation, and documentation of specific material parameters; physical, mechanical, and environmental, which becomes the basis for an ASME Code Case. Time-independent tensile and ductility data and time-dependent creep and creep-rupture behavior are some of the material properties required for a successful ASME Code case. Although this report provides a cursory review of the available data, a much more comprehensive study of open-source data would be necessary. This report serves three purposes: (a) provides a list of already existing material data information that could ultimately be made available to the ASME Code, (b) determines the HT-9 material properties data missing from available sources that would be required and (c) estimates the necessary material testing required to close the gap. Ultimately, the gap analysis demonstrates that certain material properties testing will be required to fulfill the necessary information package for an ASME Code Case.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A multi-modal scanning system to digitize CBRNE emergency response scenes

A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.

Salathe, Marco↗
DOE OSTI2022

A multi-modal scanning system to digitize CBRNE emergency response scenes

A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.

Prins, Nicholas↗
DOE OSTI2015

Modeling CH 4 and CO 2 cycling using porewater stable isotopes in a thermokarst bog in Interior Alaska: results from three conceptual reaction networks

Quantifying rates of microbial carbon transformation in peatlands is essential for gaining mechanistic understanding of the factors that influence methane emissions from these systems, and for predicting how emissions will respond to climate change and other disturbances. In this study, we used porewater stable isotopes collected from both the edge and center of a thermokarst bog in Interior Alaska to estimate in situ microbial reaction rates. We expected that near the edge of the thaw feature, actively thawing permafrost and greater abundance of sedges would increase carbon, oxygen and nutrient availability, enabling faster microbial rates relative to the center of the thaw feature. We developed three different conceptual reaction networks that explained the temporal change in porewater CO2, CH4, δ13C-CO2 and δ13C-CH4. All three reaction-network models included methane production, methane oxidation and CO2 production, and two of the models included homoacetogenesis — a reaction not previously included in isotope-based porewater models. All three models fit the data equally well, but rates resulting from the models differed. Most notably, inclusion of homoacetogenesis altered the modeled pathways of methane production when the reaction was directly coupled to methanogenesis, and it decreased gross methane production rates by up to a factor of five when it remained decoupled from methanogenesis. The ability of all three conceptual reaction networks to successfully match the measured data indicate that this technique for estimating in-situ reaction rates requires other data and information from the site to confirm the considered set of microbial reactions. Despite these differences, all models indicated that, as expected, rates were greater at the edge than in the center of the thaw bog, that rates at the edge increased more during the growing season than did rates in the center, and that the ratio of acetoclastic to hydrogenotrophic methanogenesis was greater at the edge than in the center. In both locations, modeled rates (excluding methane oxidation) increased with depth. A puzzling outcome from the effort was that none of the models could fit the porewater dataset without generating “fugitive” carbon (i.e., methane or acetate generated by the models but not detected at the field site), indicating that either our conceptualization of the reactions occurring at the site remains incomplete or our site measurements are missing important carbon transformations and/or carbon fluxes. This model–data discrepancy will motivate and inform future research efforts focused on improving our understanding of carbon cycling in permafrost wetlands.

13CH4↗
NASA NTRS1960

A Homing Missile Control System to Reduce the Effects of Radome Diffraction

The problem of radome diffraction in radar-controlled homing missiles at high speeds and high altitudes is considered from the point of view of developing a control system configuration which will alleviate the deleterious effects of the diffraction. It is shown that radome diffraction is in essence a kinematic feedback of body angular velocities which causes the radar to sense large apparent line-of-sight angular velocities. The normal control system cannot distinguish between the erroneous and actual line-of-sight rates, and entirely wrong maneuvers are produced which result in large miss distances. The problem is resolved by adding to the control system a special-purpose computer which utilizes measured body angular velocity to extract from the radar output true line-of-sight information for use in steering the missile. The computer operates on the principle of sampling and storing the radar output at instants when the body angular velocity is low and using this stored information for maneuvering commands. In addition, when the angular velocity is not low the computer determines a radome diffraction compensation which is subtracted from the radar output to reduce the error in the sampled information. Analog simulation results for the proposed control system operating in a coplanar (vertical plane) attack indicate a potential decrease in miss distance to an order of magnitude below that for a conventional system. Effects of glint noise, random target maneuvers, initial heading errors, and missile maneuverability are considered in the investigation.

Smith, Gerald L.↗
DOE OSTI2013

A new nidovirus (NamDinh virus NDiV): Its ultrastructural characterization in the C6/36 mosquito cell line

We describe the ultrastructure of the NamDinh virus (NDiV), a new member of the order Nidovirales grown in the C6/36 mosquito cell line. Uninfected and NDiV-infected cells were investigated by electron microscopy 24–48 h after infection. The results show that the viral nucleocapsid-like particles form clusters concentrated in the vacuoles, the endoplasmic reticulum, and are scattered in the cytoplasm. Mature virions of NDiV were released as budding particles on the cell surface where viral components appear to lie beneath and along the plasma membrane. Free homogeneous virus particles were obtained by ultracentrifugation on sucrose gradients of culture fluids. The size of the round-shaped particles with a complete internal structure was 80 nm in diameter. This is the first study to provide information on the morphogenesis and ultrastructure of the first insect nidovirus NDiV, a missing evolutionary link in the emergence of the viruses with the largest RNA genomes. - Highlights: • NamDinh virus (NDiV), a new member of the order Nidovirales was tested in cultured cell line. • The morphogenesis and ultrastructure of NDiV were investigated by electron microscopy. • The viral nucleocapsid-like particles clustered and scattered in the cytoplasm. • NDiVs were released as budding particles on the cell surface. • The size of the viral particles with a complete internal structure was 80 nm in diameter.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Electron scattering and neutrino physics

Abstract A thorough understanding of neutrino–nucleus scattering physics is crucial for the successful execution of the entire US neutrino physics program. Neutrino–nucleus interaction constitutes one of the biggest systematic uncertainties in neutrino experiments—both at intermediate energies affecting long-baseline deep underground neutrino experiment, as well as at low energies affecting coherent scattering neutrino program—and could well be the difference between achieving or missing discovery level precision. To this end, electron–nucleus scattering experiments provide vital information to test, assess and validate different nuclear models and event generators intended to test, assess and validate different nuclear models and event generators intended to be used in neutrino experiments. Similarly, for the low-energy neutrino program revolving around the coherent elastic neutrino–nucleus scattering (CEvNS) physics at stopped pion sources, such as at ORNL, the main source of uncertainty in the evaluation of the CEvNS cross section is driven by the underlying nuclear structure, embedded in the weak form factor, of the target nucleus. To this end, parity-violating electron scattering (PVES) experiments, utilizing polarized electron beams, provide vital model-independent information in determining weak form factors. This information is vital in achieving a percent level precision needed to disentangle new physics signals from the standard model expected CEvNS rate. In this white paper, we highlight connections between electron- and neutrino–nucleus scattering physics at energies ranging from 10 s of MeV to a few GeV, review the status of ongoing and planned electron scattering experiments, identify gaps, and lay out a path forward that benefits the neutrino community. We also highlight the systemic challenges with respect to the divide between the nuclear and high-energy physics communities and funding that presents additional hurdles in mobilizing these connections to the benefit of neutrino programs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Exploring the Early Lightning Notification of an Electric Field Mill at the Savannah River Site

At the Savannah River Site (SRS), employees receive automated broadcast notification about lightning only after three strikes have already occurred near the site boundary. To increase employee safety, it is preferential to give employees lead time before lightning strikes occur. We compared measurements from an on-site electric field mill to lightning detection data from the National Lightning Detection Network and the Geostationary Lightning Mapper. Using a difference threshold, we determined that the electric field mill provided a lead time greater than 6 minutes for 95% of lightning events from 2009-2020, with an average lead time of 56 minutes. Detection of events were limited to a 7-mile radius around the field mill. We also identified that the field mill threshold generated many false detections not clearly identified. False detections and detections from only precipitation can be reduced by using a second threshold without creating too many missed detections (Type II errors). The two thresholds used together provide the best information about rapidly changing electric fields and aid in advanced detection necessary to improve the lightning warning system used at SRS.

42 ENGINEERING↗
DOE OSTI2021

Relationship Extraction: Automatic Information Extraction and Organization for Supporting Analysts in Threat Assessment

In order for analysts to be able to do their work, they sift through hundreds, thousands, or even millions of documents to make connections between entities of interest. This process is time consuming, tedious, and prone to potential error from missed connections or connections made that should not have been. There exist many tools in natural language processing, or NLP, to extract information from documents. However, when it comes to relationship extraction, there has been varied success. This project began with a goal to solve the relationship extraction problem which developed into a deeper understanding of the problem and the associated challenges for solving this problem on a general scale. In this report, we explain our research and approach to relationship extraction, identify other auxiliary problems in NLP that provide additional challenges to solving relationship extraction generally, explain our analysis of the current state of relationship extraction, and postulate future work to address these problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
NASA NTRS2015

Mission Design Analysis for the Martian Moon Phobos: Close Flybys, Missed Thrusts, and Other In-Flight Entertainment

A robotic mission to the Martian moons Phobos and Deimos would offer a wealth of scientific information and serve as a useful precursor to potential human missions. In this paper, we investigate a prospective mission enabled by solar electric propulsion that would explore Phobos via a series of flybys followed by capture into orbit around the moon. Of particular interest are low-cost options for capture and walkdown to the target science orbits aided by multi-body effects due to the mutual gravitational interaction of Phobos and Mars. We also consider contingency operations in the event of missed thrust or maneuver execution errors.

SEP↗
DOE OSTI2022

The US Naval Observatory VLBI Spectroscopic Catalog

Despite their importance for astrometry and navigation, the active galactic nuclei (AGNs) that comprise the International Celestial Reference Frame (ICRF) are relatively poorly understood, with key information such as their spectroscopic redshifts, AGN spectral type, and emission-/absorption-line properties generally missing from the literature. Using an updated, publicly available, state-of-the-art spectroscopic fitting code optimized for the spectra of AGNs from low to high redshift, we present a catalog of emission-line and spectral continuum parameters for 1014 unique ICRF3 objects with single-fiber spectra from the Sloan Digital Sky Survey DR16. We additionally present black hole virial mass scaling relationships that use Hα-, Hβ-, Mg II -, and C IV -based line widths, all consistent with each other, which can be used in studies of radio-loud objects across a wide range of redshifts, and we use these scaling relationships to provide derived properties such as black hole masses and bolometric luminosities for the catalog. We briefly comment on these properties for the ICRF objects, as well as their overall spectroscopic characteristics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

Lessons Learned From Atomic Oxygen Interaction With Spacecraft Materials in Low Earth Orbit

There have been five Materials International Space Station Experiment (MISSE) passive experiment carriers (PECs) (MISSE 1-5) to date that have been launched, exposed in space on the exterior of International Space Station (ISS) and then returned to Earth for analysis. An additional four MISSE PECs (MISSE 6A, 6B, 7A, and 7B) are in various stages of completion. The PECs are two-sided suitcase to size sample carriers that are intended to provide information on the effects of the low Earth orbital environment on a wide variety of materials and components. As a result of post retrieval analyses of the retrieved MISSE 2 experiments and numerous prior space experiments, there have been valuable lessons learned and needs identified that are worthy of being documented so that planning, design, and analysis of future space environment experiments can benefit from the experience in order to maximize the knowledge gained. Some of the lessons learned involve the techniques, concepts, and issues associated with measuring atomic oxygen erosion yields. These are presented along with several issues to be considered when designing experiments, such as the uncertainty in mission duration, scattering and contamination effects on results, and the accuracy of measuring atomic oxygen erosion.

Banks, Bruce A.↗
NASA NTRS2008

Johnson Space Center Astronaut and Flight Surgeon Survey Report (January 2008)

In early 2007, an incident involving former astronaut, Lisa Nowak, led NASA to conduct several reviews including internal and external evaluations of astronaut behavioral health and medical care. The internal NASA review, led by Johnson Space Center (JSC), focused on two elements: 1) current astronaut behavioral medicine practices and 2) a review of relevant records and information to determine whether any leading indicators that could have averted the incident were missed. The external review, conducted by the NASA Astronaut Health Care System Review Committee (comprised of external experts from the behavioral health and aerospace medical communities), focused on space medicine operations at JSC.

Johnson Space Center(JSC)↗
DOE OSTI2025

Enhancing fire emissions inventories for acute health effects studies: integrating high spatial and temporal resolution data

Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies. This paper provides a method for improving an FEI dataset with readily available information to create a more robust dataset with daily fire progression. High temporal and spatial resolution burned area information from two FEI products are combined into a single dataset, and a linear regression model fills gaps in daily fire progression. The combined dataset provides up to 71% more PM 2.5 emissions, 69% more burned area, and 367% more fire days per year than using a single source of burned area information. The FEI combination method results in improved FEI information with no gaps in daily fire emissions estimates. The combined dataset provides a functional improvement to FEI data that can be achieved with currently available data.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Explaining Missing Data in Graphs: A Constraint-based Approach

Abstract: This paper introduces a constraint-based approach to clarify missing values in graphs. Our method capitalizes on a set S of graph data constraints. An explanation is a sequence of operational enforcement of S towards the recovery of interested yet missing data (e.g., attribute values, edges). We show that constraint-based approach helps us to understand not only why a value is missing, but also how to recover the missing value. We study S-explanation problem, which is to compute the optimal explanations with guarantees on the informativeness and conciseness. We show the problem is in ?P^2 for established graph data constraints such as graph keys and graph association rules. We develop an efficient bidirectional algorithm to compute optimal explanations, without enforcing S on the entire graph. We also show our algorithm can be easily extended to support graph refinement within limited time, and to explain missing answers. Using real-world graphs, we experimentally verify the effectiveness and efficiency of our algorithms.

Data Analytics↗
DOE OSTI2023

Important Factors for the Reliable and Reproducible Preparation of Non-aqueous Electrolyte Solutions for Lithium Batteries

Electrolyte solutions play a crucial role in rechargeable lithium batteries. Driven by an ever-increasing demand for better batteries, more and more stringent performance requirements are being asked of electrolytes. This demand to achieve electrolytes beyond the state-of-the-art has driven an increasing number of publications over the past decade. Nevertheless, a detailed description of electrolyte preparation is frequently missing when reporting new electrolytes for batteries, creating a barrier for others to reproduce important findings. In addition, false or misleading information in a paper may result from unintentional inaccuracies during the electrolyte preparation process. This article highlights important factors for the reliable and reproducible preparation of non-aqueous electrolyte solutions for lithium batteries, with the aim of encouraging researchers to follow more rigorous reporting standards.

Cao, Xia↗
DOE OSTI2022

A deep learning approach to identify missing is-a relations in SNOMED CT

Abstract Objective SNOMED CT is the largest clinical terminology worldwide. Quality assurance of SNOMED CT is of utmost importance to ensure that it provides accurate domain knowledge to various SNOMED CT-based applications. In this work, we introduce a deep learning-based approach to uncover missing is-a relations in SNOMED CT. Materials and Methods Our focus is to identify missing is-a relations between concept-pairs exhibiting a containment pattern (ie, the set of words of one concept being a proper subset of that of the other concept). We use hierarchically related containment concept-pairs as positive instances and hierarchically unrelated containment concept-pairs as negative instances to train a model predicting whether an is-a relation exists between 2 concepts with containment pattern. The model is a binary classifier leveraging concept name features, hierarchical features, enriched lexical attribute features, and logical definition features. We introduce a cross-validation inspired approach to identify missing is-a relations among all hierarchically unrelated containment concept-pairs. Results We trained and applied our model on the Clinical finding subhierarchy of SNOMED CT (September 2019 US edition). Our model (based on the validation sets) achieved a precision of 0.8164, recall of 0.8397, and F1 score of 0.8279. Applying the model to predict actual missing is-a relations, we obtained a total of 1661 potential candidates. Domain experts performed evaluation on randomly selected 230 samples and verified that 192 (83.48%) are valid. Conclusions The results showed that our deep learning approach is effective in uncovering missing is-a relations between containment concept-pairs in SNOMED CT.

97 MATHEMATICS AND COMPUTING↗