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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

LISA: Opening New Horizons

The Laser Interferometer Space Antenna (LISA) is a space-borne observatory that will open the low frequency (approx.0.1-100 mHz) gravitational wave window on the universe. LISA will observe a rich variety of gravitational wave sources, including mergers of massive black holes, captures of stellar black holes by massive black holes in the centers of galaxies, and compact Galactic binaries. These sources are generally long-lived, providing unprecedented opportunities for multi-messenger astronomy in the transient sky. This talk will present an overview of these scientific arenas, highlighting how LISA will enable stunning discoveries in origins, understanding the cosmic order, and the frontiers of knowledge.

Centrella, Joan M.↗
NASA NTRS2013

Prominence Mass Supply and the Cavity

A prevalent but untested paradigm is often used to describe the prominence-cavity system; the cavity is under-dense because it it evacuated by supplying mass to the condensed prominence. The thermal non-equilibrium (TNE) model of prominence formation offers a theoretical framework to predict the thermodynamic evolutin of the prominence and the surrounding corona. We examine the evidence for a prominence-cavity connection by comparing the TNE model and diagnostics of dynamic extreme ultraviolet (EUV) emission surrounding the prominence, specifically prominence horns. Horns are correlated extensions of prminence plasma and coronal plasma which appear to connect the prominence and cavity. The TNE model predicts that large-scale brightenings will occur in the Solar Dynamics Observatory Atmospheric Imaging Assembly 171 A badpass near he prominence that are associated with the cooling phase of condensation formation. In our simulations, variations in the magnitude of footpoint heating lead to variations in the duration, spatial scale, and temporal offset between emission enhancements in the other EUV bandpasses. While these predictions match well a subset of the horn observations, the range of variations in the observed structures is not captured by the model. We discuss the implications of one-dimensional loop simulations for the three-dimensional time-averaged equilibrium in the prominence and the cavity. Evidence suggests that horns are likely caused by condensing prominence plasma, but the larger question of whether this process produces a density-depleted cavity requires a more tightly constrained model of heating and better knowledge of the associated magnetic structure.

PROMINENCES↗
NASA NTRSDate not supplied

Expanding Biological Repository Data Available for Sharing and Knowledge Discovery

Biology has developed next-generation data science and alternative analytical approaches with methodologies which require principal investigator (PI) experimental assay data be re-used. This new approach involves mining multiple datasets at once from various hierarchical organizations of biological complexity, while concurrently evaluating how experimental factors affect endpoints of standard assays. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make findable, accessible, interoperable, and reusable (FAIR) all non-human space-relevant biological data. These data include mission metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery, and subject-experienced telemetry (radiation, temperature, humidity, acoustics, vibrations). ALSDA has transformed to bring current biological repository data and all future collected data into this new scientific data mining reality. It has integrated into the ‘NASA Open Science’ group of projects to facilitate a suite of new tools and workflows to improve data accessibility and reusability by implementing data management plans, automating data submission agreements, and adopting the single-point-of-entry data submission portal, originally developed by NASA GeneLab. These systems required ALSDA to develop science assay configurations for the submission portal, capturing essential assay parameters according to established norms in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. ALSDA datasets are curated to maintain rich metadata, accuracy of datasets, data transparency, provenance, and additionally ensure data are machine-readable (e.g., R and Python languages). ALSDA integration with GeneLab and its analysis portals enable higher-order physiological-level datasets be mined in conjunction with -omics datasets. As ALSDA physiological-level datasets are published (micro-computed tomography, histology, intraocular pressure, hormonal assays, immunostaining, ultrasonography), the merging of hierarchical organizations of biological complexity from spaceflight will enable new knowledge discovery approaches.

Ryan T Scott↗
DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Investigating the Impacts of Aqueous-Phase Processing on Organic Aerosol Chemical Climatology Using ARM and ASR Observations

This project improved understanding of how atmospheric aerosol particles form and evolve, with a focus on the role of water-driven (aqueous-phase) chemical reactions in the atmosphere. These processes occur in clouds, fog, and humid air and can significantly change the composition and properties of airborne particles, known as aerosols, which influence air quality and climate. By combining field measurements, laboratory experiments, and advanced analytical techniques, the project identified key chemical signatures that allow scientists to distinguish particles formed through aqueous processes from those formed in the gas phase. Observations from multiple environments, including wildfire smoke, urban regions, and cloud-influenced areas, show that aqueous chemistry is an important pathway for particle formation and aging. The project also developed new measurement approaches using uncrewed aerial systems (UAS) to capture how aerosol composition varies with altitude, providing critical insights into how particles interact with clouds. In addition, new data analysis frameworks were created to better interpret long-term aerosol measurements and improve characterization of particle sources and transformations. These results have been integrated into a global database of aerosol measurements and used to support atmospheric modeling efforts. Overall, the project provides important tools and knowledge to improve predictions of how aerosols affect climate and air quality, particularly through their interactions with radiation and clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2002

An Assessment of the Ability of Potential Satellite Instruments to Resolve Spatial and Temporal Variability of Atmospheric CO2

Sufficiently precise satellite observations with adequate spatial and temporal resolution would substantially increase our knowledge of the atmospheric CO2 distribution and would undoubtedly lead to reduced uncertainty in estimates of the global carbon budget. An overview of possible strategies for measuring CO2 from space will be presented, including IR and nearby measurements, active sensors and broad band and narrow band passive sensors. The ability of potential satellite instruments with a variety of orbits, horizontal resolution and vertical weighting functions to capture the variation in atmospheric CO2 mixing ratios will be illustrated using a combination of surface data, aircraft data and model results.

Andrews, A.↗
DOE OSTI2025

Geothermal Collegiate Competition: Evolution and Impact

In 2010, the U.S. Department of Energy (DOE) announced the launch of its inaugural National Geothermal Student Competition. The competition was open to all colleges, universities, and other post-secondary institutions in the United States, and was labeled as the first-ever to address geothermal education. The GeoVision, published in 2019 by the Geothermal Technologies Office (GTO), stated that improving geothermal energy education and outreach is critical in reducing risks and costs of geothermal technology deployment. The key actions included improving public education and outreach about geothermal energy and providing resources intended to attract and inform a skilled geothermal workforce. Student competitions in particular have the ability to increase awareness of renewable energy fields by engaging multi-disciplinary students in compelling design challenges to prepare them for careers in renewable energy. GTO, in partnership with an administration team at the National Renewable Energy Laboratory (NREL), currently supports the Geothermal Collegiate Competition (GCC), with the main objective of advancing and cultivating collegiate student knowledge and career interest in geothermal energy. The administrating team works toward growing the number of students and collegiate institutions engaged, as well as diversifying the scope of the student design challenges. The main intentions of this publication are documenting the competition’s evolution, setting a baseline for future GCC impact analysis and serving as a guide to other students’ competition design committees looking for ideas to capture and increase the interest of students in collegiate competitions.

Geothermal Collegiate Competition↗
NASA NTRS1999

Principal Investigator-in-a-Box

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].

Young, Laurence R.↗
NASA NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗
NASA NTRSDate not supplied

Using Open Innovation in Reducing Risk to Crews

In the exploration of destinations outside of Earth's neighborhood, specifically Mars, scientific and engineering inquiries have occurred by two means; observations from satellites and observations by landed spacecraft. Satellite observations (Mariner, MRO, Mars Odyssey, provide global-scale spatial and temporal data while landed spacecraft (Viking, Mars Pathfinder, Spirit, Opportunity, Phoenix Mars Lander) investigate highly localized areas of the surface of the planet. In preparation for human exploration, extensive knowledge of the surface and atmospheric environments should be known before the first human leaves Earth. The primary goal of performing reconnaissance on Mars on a sub-global scale is to know as much as possible about the environment to which crews will be subjected. At the current rate of launching and landing probes to Mars, it will take a very long time to understand the surface and atmospheric conditions associated with the regions where prospective crews may land. Meanwhile electronics and electrical systems are rapidly getting smaller. One can argue that to acquire the knowledge of the region, one must take hundreds, maybe thousands of measurements simultaneously. One means to perform such a task is to deploy a swarm of sensors. Such a swarm would perform an in-situ assessment of the region. Imagine a close flyby mission to Mars for example, where mini- to micro-sensors are deposited into the atmosphere over half an orbit or more. The sensors, captured by the atmospheric drag and Martian gravity slowly descend buffeted about by Martian winds and weather until they settle on the surface a great time later (think of how long dust takes to settle). As they descend they communicate a vast array of data; temperature, chemistry, pressure, radiation dose, electric or magnetic properties from a region of the planet and an individual sensor need not measure the same quantity as its neighbors. Initially, they could move at the whim of the environment but later versions could have locomotion or propulsion mechanisms. Humans wouldn't need to decide where the sensors go, the sensors do that for themselves. This is a key strength of a sensor swarm. The intelligence relies on the group not on a decision maker on earth. Real time sensor inputs direct what the swarm considers most interesting to investigate resulting in emergent behavior. We issued a $20,000 challenge to the global innovators to provide solutions as to how such a swarm could be initialized and by what protocols and methodologies by which they operate. Over 400 innovators from 49 countries took a look at the problem, with three receiving partial awards for solutions.

Mel Ferebee↗
NASA NTRS1998

The Importance of Semi-Major Axis Knowledge in the Determination of Near-Circular Orbits

Modem orbit determination has mostly been accomplished using Cartesian coordinates. This usage has carried over in recent years to the use of GPS for satellite orbit determination. The unprecedented positioning accuracy of GPS has tended to focus attention more on the system's capability to locate the spacecraft's location at a particular epoch than on its accuracy in determination of the orbit, per se. As is well-known, the latter depends on a coordinated knowledge of position, velocity, and the correlation between their errors. Failure to determine a properly coordinated position/velocity state vector at a given epoch can lead to an epoch state that does not propagate well, and/or may not be usable for the execution of orbit adjustment maneuvers. For the quite common case of near-circular orbits, the degree to which position and velocity estimates are properly coordinated is largely captured by the error in semi-major axis (SMA) they jointly produce. Figure 1 depicts the relationships among radius error, speed error, and their correlation which exist for a typical low altitude Earth orbit. Two familiar consequences are the relationship Figure 1 shows are the following: (1) downrange position error grows at the per orbit rate of 3(pi) times the SMA error; (2) a velocity change imparted to the orbit will have an error of (pi) divided by the orbit period times the SMA error. A less familiar consequence occurs in the problem of initializing the covariance matrix for a sequential orbit determination filter. An initial covariance consistent with orbital dynamics should be used if the covariance is to propagate well. Properly accounting for the SMA error of the initial state in the construction of the initial covariance accomplishes half of this objective, by specifying the partition of the covariance corresponding to down-track position and radial velocity errors. The remainder of the in-plane covariance partition may be specified in terms of the flight path angle error of the initial state. Figure 2 illustrates the effect of properly and not properly initializing a covariance. This figure was produced by propagating the covariance shown on the plot, without process noise, in a circular low Earth orbit whose period is 5828.5 seconds. The upper subplot, in which the proper relationships among position, velocity, and their correlation has been used, shows overall error growth, in terms of the standard deviations of the inertial position coordinates, of about half of the lower subplot, whose initial covariance was based on other considerations.

Carpenter, J. Russell↗
DOE OSTI2026

Experimental uncertainty quantification using templates of expected measurement uncertainties for fast neutron-induced total, capture, and scattering cross sections

Careful experimental uncertainty quantification (UQ) is key for developing trustworthy evaluated nuclear data. Templates to account for missing or under-reported experimental uncertainties were recently developed by the covariance committee of Cross Section Evaluation Working Group (CSEWG). In this work, we illustrate the practical application and limitations of these templates for selected neutron-induced reactions, including (n, tot), (n, γ), and (n, xn) in the fast energy range, to illustrate their use in data analyses for nuclear data evaluations. We show that while the templates provide consistent framework, proper implementation still requires detailed knowledge of experimental conditions and careful treatment of nonlinear effects in cross section derivation. Case studies highlight how template-assisted UQ improves consistency with previous evaluations such as ENDF/B and reveals open challenges in propagating uncertainties across different energy regimes. The main contribution of this paper is to connect formal template recommendations with their use in practical evaluation workflows, clarifying both their benefits and current limitations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

CRADA Number NFE-22-09333 with Holocene Climate Corporation (CRADA Final Report:)

Holocene Climate Corporation has developed and scaled up a novel technology for Direct Air Capture (DAC) that is based on cutting-edge research initiated at Oak Ridge National Laboratory (ORNL). According to the IPCC, carbon dioxide capture from the air and its sequestration are necessary to keep global temperature rise below 1.5°C by 2050. DAC is a viable and practical way to reach this goal. DAC can happen anywhere in the world, takes up a fraction of the land of forests, and along with the sequestration of CO 2 , provides permanent and verifiable removal of carbon from the atmosphere. The proposed project aimed to facilitate knowledge transfer from ORNL to Holocene focusing on (i) the synthesis of the ORNL patented material which builds the cornerstone of the DAC technology, and (ii) required analytical methods needed to conduct crystallization bench-scale experimentation and technology development. Furthermore, ORNL conducted research centered around CO 2 absorption using an air-liquid contacting structure with an aqueous amino acid solution. The achievements under this project comprise successful knowledge transfer from ORNL to the entire Holocene team to jump-start their internal R&D and technological development activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Understanding and mitigating degradation in amine-based sorbents for CO 2 direct air capture

The success of direct air capture (DAC) of CO 2 depends on sorbents that combine high capacity, low energy requirements, and long-term durability. Amine-based sorbents-including solid-supported aminopolymers, grafted amines, and amine-functionalized resins-remain the leading candidates, but their limited lifetimes drive up costs and constrain deployment. In this review, we outline the current understanding of amine-based sorbent degradation with an emphasis on clearly identifying what is known about structure-property-performance relationships, as well as important knowledge gaps. More specifically, we discuss how polymer chemistry, sorbent design variables, and environmental and process conditions contribute to performance loss. In parallel, we outline how advances in spectroscopy, modeling, and accelerated testing are beginning to illuminate chemical and physical degradation mechanisms. Looking forward, we identify future research directions that will be critical for gaining a deeper understanding of degradation, as well as opportunities for developing innovative mitigation strategies for improving the lifetime of amine-based sorbents.

organic↗
NASA NTRS2001

ScienceOrganizer System and Interface Summary

ScienceOrganizer is a specialized knowledge management tool designed to enhance the information storage, organization, and access capabilities of distributed NASA science teams. Users access ScienceOrganizer through an intuitive Web-based interface that enables them to upload, download, and organize project information - including data, documents, images, and scientific records associated with laboratory and field experiments. Information in ScienceOrganizer is "threaded", or interlinked, to enable users to locate, track, and organize interrelated pieces of scientific data. Linkages capture important semantic relationships among information resources in the repository, and these assist users in navigating through the information related to their projects.

Keller, Richard M.↗
NASA NTRS1992

Reasoning about energy in qualitative simulation

While possible behaviors of a mechanism that are consistent with an incomplete state of knowledge can be predicted through qualitative modeling and simulation, spurious behaviors corresponding to no solution of any ordinary differential equation consistent with the model may be generated. The present method for energy-related reasoning eliminates an important source of spurious behaviors, as demonstrated by its application to a nonlinear, proportional-integral controlled. It is shown that such qualitative properties of such a system as stability and zero-offset control are captured by the simulation.

Fouche, Pierre↗
NASA NTRS1991

IDEF3 formalization report

The Process Description Capture Method (IDEF3) is one of several Integrated Computer-Aided Manufacturing (ICAM) DEFinition methods developed by the Air Force to support systems engineering activities, and in particular, to support information systems development. These methods have evolved as a distillation of 'good practice' experience by information system developers and are designed to raise the performance level of the novice practitioner to one comparable with that of an expert. IDEF3 is meant to serve as a knowledge acquisition and requirements definition tool that structures the user's understanding of how a given process, event, or system works around process descriptions. A special purpose graphical language accompanying the method serves to highlight temporal precedence and causality relationships relative to the process or event being described.

Menzel, Christopher↗
NASA NTRS2011

Component-Level Electronic-Assembly Repair (CLEAR) System Architecture

This document captures the system architecture for a Component-Level Electronic-Assembly Repair (CLEAR) capability needed for electronics maintenance and repair of the Constellation Program (CxP). CLEAR is intended to improve flight system supportability and reduce the mass of spares required to maintain the electronics of human rated spacecraft on long duration missions. By necessity it allows the crew to make repairs that would otherwise be performed by Earth based repair depots. Because of practical knowledge and skill limitations of small spaceflight crews they must be augmented by Earth based support crews and automated repair equipment. This system architecture covers the complete system from ground-user to flight hardware and flight crew and defines an Earth segment and a Space segment. The Earth Segment involves database management, operational planning, and remote equipment programming and validation processes. The Space Segment involves the automated diagnostic, test and repair equipment required for a complete repair process. This document defines three major subsystems including, tele-operations that links the flight hardware to ground support, highly reconfigurable diagnostics and test instruments, and a CLEAR Repair Apparatus that automates the physical repair process.

Oeftering, Richard C.↗