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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 379 records · Page 21

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗

Injection-induced turbulence in stagnation-point boundary layers

A theory is developed for the stagnation point boundary layer with injection under the hypothesis that turbulence is produced at the wall by injection. From the existing experimental heat transfer rate data obtained in wind tunnels, the wall mixing length is deduced to be a product of a time constant and an injection velocity. The theory reproduces the observed increase in heat transfer rates at high injection rates. For graphite and carbon-carbon composite, the time constant is determined to be 0.0002 sec from the existing ablation data taken in an arc-jet tunnel and a balistic range.

Park, C.↗

SPECS: Orbital debris removal

The debris problem has reached a stage at which the risk to satellites and spacecraft has become substantial in low Earth orbit (LEO). This research discovered that small particles posed little threat to spacecraft because shielding can effectively prevent these particles from damaging the spacecraft. The research also showed that, even though collision with a large piece of debris could destroy the spacecraft, the large pieces of debris pose little danger because they can be tracked and the spacecraft can be maneuvered away from these pieces. Additionally, there are many current designs to capture and remove large debris particles from the space environment. From this analysis, it was decided to concentrate on the removal of medium-sized orbital debris, that is, those pieces ranging from 1 cm to 50 cm in size. The current design incorporates a transfer vehicle and a netting vehicle to capture the medium-sized debris. The system is based near an operational space station located at 28.5 deg inclination and 400 km altitude. The system uses ground-based tracking to determine the location of a satellite breakup or debris cloud. These data are uploaded to the transfer vehicle, which proceeds to rendezvous with the debris at a lower altitude parking orbit. Next, the netting vehicle is deployed, tracks the targeted debris, and captures it. After expending the available nets, the netting vehicle returns to the transfer vehicle for a new netting module and continues to capture more debris in the target area. Once all the netting modules are expended, the transfer vehicle returns to the space station's orbit where it is resupplied with new netting modules from a space shuttle load. The new modules are launched by the shuttle from the ground and the expended modules are taken back to Earth for removal of the captured debris, refueling, and repacking of the nets. Once the netting modules are refurbished, they are taken back into orbit for reuse. In a typical mission, the system has the ability to capture 50 pieces of orbital debris. One mission will take approximately six months and the system is designed to allow for a 30 deg inclination change on the outgoing and incoming trips of the transfer vehicle.

Source record↗

Command and Control of Space Assets Through Internet-Based Technologies Demonstrated

The NASA Glenn Research Center successfully demonstrated a transmission-control-protocol/ Internet-protocol- (TCP/IP) based approach to the command and control of onorbit assets over a secure network. This is a significant accomplishment because future NASA missions will benefit by using Internet-standards-based protocols. Benefits of this Internet-based space command and control system architecture include reduced mission costs and increased mission efficiency. The demonstration proved that this communications architecture is viable for future NASA missions. This demonstration was a significant feat involving multiple NASA organizations and industry. Phillip Paulsen, from Glenn's Project Development and Integration Office, served as the overall project lead, and David Foltz, from Glenn's Satellite Networks and Architectures Branch, provided the hybrid networking support for the required Internet connections. The goal was to build a network that would emulate a connection between a space experiment on the International Space Station and a researcher accessing the experiment from anywhere on the Internet, as shown. The experiment was interfaced to a wireless 802.11 network inside the demonstration area. The wireless link provided connectivity to the Tracking and Data Relay Satellite System (TDRSS) Internet Link Terminal (TILT) satellite uplink terminal located 300 ft away in a parking lot on top of a panel van. TILT provided a crucial link in this demonstration. Leslie Ambrose, NASA Goddard Space Flight Center, provided the TILT/TDRSS support. The TILT unit transmitted the signal to TDRS 6 and was received at the White Sands Second TDRSS Ground Station. This station provided the gateway to the Internet. Coordination also took place at the White Sands station to install a Veridian Firewall and automated security incident measurement (ASIM) system to the Second TDRSS Ground Station Internet gateway. The firewall provides a trusted network for the simulated space experiment. A second Internet connection at the demonstration area was implemented to provide Internet connectivity to a group of workstations to serve as platforms for controlling the simulated space experiment. Installation of this Internet connection was coordinated with an Internet service provider (ISP) and local NASA Johnson Space Center personnel. Not only did this TCP/IP-based architecture prove that a principal investigator on the Internet can securely command and control on-orbit assets, it also demonstrated that valuable virtual testing of planned on-orbit activities can be conducted over the Internet prior to actual deployment in space.

Foltz, David A.↗

Representation of the Physiological Factors Contributing to Postflight Changes in Functional Performance Using Motion Analysis Software

Astronauts experience changes in multiple physiological systems due to exposure to the microgravity conditions of space flight. To understand how changes in physiological function influence functional performance, a testing procedure has been developed that evaluates both astronaut postflight functional performance and related physiological changes. Astronauts complete seven functional and physiological tests. The objective of this project is to use motion tracking and digitizing software to visually display the postflight decrement in the functional performance of the astronauts. The motion analysis software will be used to digitize astronaut data videos into stick figure videos to represent the astronauts as they perform the Functional Tasks Tests. This project will benefit NASA by allowing NASA scientists to present data of their neurological studies without revealing the identities of the astronauts.

Parks, Kelsey↗

The Western Aeronautical Test Range. Chapter 10 Tools

The Western Aeronautical Test Range (WATR) staff at the NASA Dryden Flight Research Center is developing a translation software called Chapter 10 Tools in response to challenges posed by post-flight processing data files originating from various on-board digital recorders that follow the Range Commanders Council Inter-Range Instrumentation Group (IRIG) 106 Chapter 10 Digital Recording Standard but use differing interpretations of the Standard. The software will read the date files regardless of the vendor implementation of the source recorder, displaying data, identifying and correcting errors, and producing a data file that can be successfully processed post-flight

Knudtson, Kevin↗

Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet(UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of>~0.4 and GEMS SSA values of<~0.95.Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

aerosol↗

Reassessing long-standing meteorological records: an example using the national hottest day in Ireland

This analysis highlights the potential value in reanalysing early national meteorological records from around the world. These were oftentimes measured via techniques that preceded standardisation of instrumentation and methods of observation and thus could be subject to considerable biases and uncertainties. This analysis uses the techniques pioneered by WMO record assessment teams. The highest currently recognised air temperature (33.3 °C) ever recorded in the Republic of Ireland was logged at Kilkenny Castle in 1887. The original observational record however no longer exists. Given that Ireland is now the only country in Europe to have a national heat record that was set in the 19th century, a reassessment of the verity of this record is both timely and valuable. The present analysis undertakes a fundamental reassessment of the plausibility of the 1887 temperature record using methods similar to those used to assess various weather extremes under WMO auspices over recent years. Specifically, we undertake an inter-station reassessment using sparse available records and make recourse to the new and improved 20CRv3 sparse-input reanalysis product. Neither surrounding available stations nor the reanalysis offer substantive support for the Kilkenny record of 33.3 °C being correct. Moreover, recent data rescue efforts have uncovered several earlier extreme values, one of which exceeds the Kilkenny value (33.5 °C on 16 July 1876 recorded at the Phoenix Park). However, the sparsity of early observational networks, a distinct lack of synoptic support from 20CRv3 for many of the extreme heat values, and the fact that these measurements were obtained using non-standard exposures lead us to conclude that there is grossly insufficient evidence to support any of these 19th century extremes as robust national heat record candidates. Data from the early 20th century onwards benefit from a denser network of stations undertaking measurements in a more standardised manner, many under the direct auspices of Met Éireann and its predecessors, adhering to WMO guidance and protocols. This enables more robust cross-checking of records. We argue that the Met Éireann-recognised 20th century heat record from Boora in 1976 is verified as the most plausible robust national temperature record based upon the synoptic situation and comparisons with nearby neighbouring stations. This measurement of 32.5°C thus likely constitutes the highest reliably recorded temperature measurement in the Republic of Ireland. Ultimately, the formal decision on any reassessment and reassignment of the national record rests with the national meteorological service, Met Éireann.

15 GEOTHERMAL ENERGY↗

Advanced Systems Map, Monitor, and Manage Earth's Resources

SpecTIR LLC, headquartered in Reno, Nevada, is recognized for innovative sensor design, on-demand hyperspectral data collection, and image-generating products for business, academia, and national and international governments. SpecTIR's current vice president of business development has brought a wealth of NASA-related research experience to the company, as the former principal investigator on a NASA-sponsored hyperspectral crop-imaging project. This project, made possible through a Small Business Technology Transfer (STTR) contract with Goddard Space Flight Center, aimed to enhance airborne hyperspectral sensing and ground-truthing means for crop inspection in the Mid-Atlantic region of the United States. Areas of application for such technology include precision farming and irrigation; oil, gas, and mineral exploration; pollution and contamination monitoring; wetland and forestry characterization; water quality assessment; and submerged aquatic vegetation mapping. Today, SpecTIR maintains its relationship with Goddard through programs at the University of Maryland in College Park, Maryland, and at the U.S. Department of Agriculture campus in Beltsville, Maryland. Additionally, work continues on the integration of hyperspectral data with LIDAR systems and other commercial-off-the-shelf technologies.

Source record↗

Estimation of tropical forest canopy temperatures, thermal response numbers, and evapotranspiration using an aircraft-based thermal sensor

Thermal infrared Multispectral Scanner (TIMS) data were collected at a resolution of 5 to 10 m from a tropical rain forest over an elevation gradient from 35 to 2700 m in the Braulio Carrillo National Park in Costa Rica. Flight lines were repeated with a 15 to 30 minute time difference for measurement of forest canopy thermal response over time. Concurrent radiosonde measurements of atmospheric profiles of air temperature and moisture provided inputs to LOWTRAN6 for atmospheric radiance corrections of the TIMS data. Techniques for using calibrated aircraft-based thermal scanner data to examine tropical forest canopy thermal properties are described. Forest canopy temperature changes over time assessed between repeated, duplicated flight lines were combined with estimates of surface radiative energy measurements from towers above the forest canopy to determine temperature spatial variability, calculate Thermal Response Numbers (TRN), and estimate evapotranspiration along the elevation gradient from selected one hectare forest inventory plots.

Luvall, Jeffrey C.↗

ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling

Traditional entropy-based methods—such as cross-entropy loss in classification problems—have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence algorithms. However, the rapid growth of data across various domains has introduced new challenges, particularly the integration of heterogeneous datasets with intrinsic disparities. To address this, we introduce a zentropy-enhanced neural network (ZENN), extending zentropy theory into the data science domain via intrinsic entropy, enabling more effective learning from heterogeneous data sources. ZENN simultaneously learns both energy and intrinsic entropy components, capturing the underlying structure of multisource data. To support this, we redesign the neural network architecture to better reflect the intrinsic properties and variability inherent in diverse datasets. We demonstrate the effectiveness of ZENN on classification tasks and energy landscape reconstructions, showing its superior generalization capabilities and robustness-particularly in predicting high-order derivatives. In image and text classification tasks, ZENN demonstrates superior generalization by introducing a learnable temperature variable that models latent multisource heterogeneity, allowing it to surpass state-of-the-art models on CIFAR-10/100, BBC News, and AG News. As a practical application in materials science, we employ ZENN to reconstruct the Helmholtz energy landscape of Fe3Pt using data generated from density functional theory and capture key material behaviors, including negative thermal expansion and the critical point in the temperature–pressure space. Overall, this work presents a zentropy-grounded framework for data-driven machine learning, positioning ZENN as a versatile and robust approach for scientific problems involving complex, heterogeneous datasets.

36 MATERIALS SCIENCE↗

The Lunar Neon Exosphere Seen in LACE Data

Using the LACE data from Apollo 17 we have found measured neon densities consistent with the 20Ne surface number densities reported by Cook et al. (2013) for normal conditions, terminator surface densities of 3 (±1.5) × 10(exp 3) per cu.cm. These values are almost an order of magnitude less than those reported by Benna et al. (2015) for CME conditions. Using a Monte Carlo model and assuming the normal solar wind and a photoionization lifetime for Ne of 300 days, our result was more consistent with the Benna (2015) result than our measured result. Two lunations showed an increase in Ne during the night, consistent with the simulation, but two of the lunations showed a decrease in surface number density through the night. We have shown that explaining the Ne distribution is not as simple as assuming dynamic equilibrium with the solar wind and an exosphere accommodated to the local surface temperature.

LACE Data↗

A novel approach for calculating galaxy rotation curves using spaxel cross-correlation and iterative smoothing

ABSTRACT Precise measurements of the internal dynamics of galaxies have proven of great importance for understanding the internal dark matter distribution of galaxies. We present a novel method for measuring the line-of-sight (LOS) velocities across the face of galaxies by cross-correlation of spectral pixels (spaxels) and an iterative method of smoothing. On simulated data the method can accurately recover the input LOS velocities for different types of spectra (absorption-line dominated, emission-line dominated, and differing shapes of the continuum), and can handle stellar population radial gradients. Most important of all, it continues to provide reliable measurements of LOS velocities with reasonable uncertainties even when the spectra are very low signal-to-noise ratio (approaching ∼1), which is a challenge for traditional template-fitting approaches. We apply our method to data from a real MaNGA galaxy as a demonstration and find promising results with good precision. This novel approach can be complementary to existing methods primarily based on template fitting.

79 ASTRONOMY AND ASTROPHYSICS↗

Airspace Safety Threshold Study: NAS-Wide Encounter Rate Evaluation Using Historical Radar Data and ACES

Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 (SC-228) is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements as well as the safety substantiation and end-to-end assessment of DAA system performance. With regard to the safety aspect being studied by the SC-228 DAA Safety sub-group, NASA has conducted a study using the ACES (Airspace Concept Evaluation System) simulation capability to determine: 1) the rate at which IFR aircraft encounter other IFR and VFR aircraft, and 2) the rate at which UAS aircraft encounter VFR aircraft as well as the corresponding encounter geometries. Five different separation thresholds were used (two for encounter and one each for well-clear, near mid-air collision, and closest point of approach). The results will be used by the SC-228 DAA Safety sub-group to inform decisions about the safety aspect of UAS DAA systems and future requirements development and validation efforts.

encounter geometry↗

Soft X-ray observation of supernova remnant IC 443

The low-energy X-ray spectrum (0.15-3.0 keV) and X-ray centroid position of the supernova remnant IC 443 have been determined using data obtained by the HEAO-1 A-2 experiment. The spectrum exhibits a low-energy excess over and above that predicted by an extrapolation of the higher-energy spectrum determined by Parkes et al (1976). The excess can be attributed to line emission, predominately from high-ionization states of iron from a plasma at a temperature of 7.7 + or - 0.6 or -4.3 x 10 to the 6th K. Other models which fit the data are discussed, in particular, a lower-temperature component required to explain the Fe X optical emission.

Galas, C. M. F.↗

Yellowstone Ecological Forecasting: Assessing Change in Aspen Extent in Northern Yellowstone National Park

The removal and reintroduction of the gray wolf (Canis lupus) in Yellowstone National Park have shaped the ecological composition of this distinct landscape, representing a textbook example of trophic dynamics. With particular importance to conservation science, researchers have studied the trophic cascades between wolves and species such as elk (Cervus canadensis) and quaking aspen (Populus tremuloides). In conjunction with the National Park Service, Yellowstone National Park, Utah State University, and the University of Wisconsin–Stevens Point, this project utilized satellite remote sensing to investigate the long-term trends in aspen extent. Through random forest modeling and phenological approaches, Landsat 5 Thematic Mapper (TM; years 1986–2011) and Sentinel-2 Multispectral Instrument (MSI; years 2017–2019) datasets were used to derive color composites, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Tasseled Cap Indices (Brightness, Greenness, Wetness). The International Space System (ISS) Global Ecosystem Dynamics Investigation (GEDI) provided canopy height data. The team consolidated results into maps and time-series which provide an in-depth depiction of aspen stand extent. The National Park Service will use these end products to assist in its management practices and inform wildlife restoration decisions within and beyond Yellowstone National Park.

Kyle Steen↗

Determination of Chlorophyll Content in Selected Grass Communities of Krkonoše Mts. Tundra Based on Laboratory Spectroscopy and Aerial Hyperspectral Data

The study focuses on the determination of chlorophyll content in four prevailing grasses in the relict arctic-alpine tundra located in the Krkonoše Mountains National Park, Czech Republic. We compared two methods for determination of leaf chlorophyll content (LCC) – spectrophotometric determination in the laboratory, and the LCC assessed by fluorescence portable chlorophyll meter CCM-300. Relationships were established between the LCCs and vegetation indices calculated from leaf spectra acquired with contact probe coupled with an ASD FieldSpec4 Wide-Res spectroradiometer. Canopy chlorophyll contents (CCC) were computed from the LCCs and green leaf area index (LAI), and modelled based on the field spectra measured by the spectroradiometer and the hyperspectral images acquired by Headwall Nano-Hyperspec® mounted on the DJI Matrice 600 Pro drone. The calculations are performed on datasets acquired in June, July and August 2020 together and separately for species and months. In general, the correlations based on June datasets work the best at both levels: median R 2 for all indices was 0.52 for all species together at leaf level and median R 2 = 0.47 at the canopy level (vegetation indices computed from field spectra). Canopy chlorophyll content map was created based on the results of stepwise multiple linear regression. The R 2 was 0.42 when using four wavelengths from the red and red edge spectral region. We attribute the weak model performance to a combination of several factors: leaf structure may bias LCC from laboratory measurements, effects of LAI variability on CCC, and the sampling design, probably not covering the whole phenology equally for all studied species.

L. Cervena↗

Wind Turbine / Reviewed Data

The SUMR-D CART2 turbine data are recorded by the CART2 wind turbine's supervisory control and data acquisition (SCADA) system for the Advanced Research Projects Agency–Energy (ARPA-E) SUMR-D project located at the National Renewable Energy Laboratory (NREL) Flatirons Campus. For the project, the CART2 wind turbine was outfitted with a highly flexible rotor specifically designed and constructed for the project. More details about the project can be found here: https://sumrwind.com/. The data include power, loads, and meteorological information from the turbine during startup, operation, and shutdown, and when it was parked and idle.

17 WIND ENERGY↗