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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 127 records · Page 7

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Maxwell, Thomas↗

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

White, Kristopher D.↗

FAIR Data Meets FAIR Software

Modern scientific research is increasingly defined by the interplay between data, software, and the workflows that connect them. Yet while the FAIR (Findable, Accessible, Interoperable, Reusable) principles have become foundational for scientific data stewardship, the same level of structure and expectation has only recently begun to extend to research software. This talk covers why and how FAIR principles are being applied to data and software to support data reuse. It outlines the gaps in current sharing norms, the growing federal emphasis on persistent identifiers and public access, and the opportunities created when datasets, computational workflows, code, and models are linked through rich, standardized metadata. Practical implementation pathways for the EIC and JLab communities are described, including datacards for structured dataset documentation and provenance-aware workflows. By aligning data lifecycle management with FAIR-aligned software practices, the scientific community can advance toward autonomous knowledge graphs, generative workflows, and high-quality, AI-ready scientific datasets.

McSpadden, Diana [Thomas Jefferson National Accele↗

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗

CANDELS: The Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey

The Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) is designed to document the first third of galactic evolution, from z approx. 8 - 1.5. It will image > 250,000 distant galaxies using three separate cameras on the Hubble Space Tele8cope, from the mid-UV to near-IR, and will find and measure Type Ia supernovae beyond z > 1.5 to test their accuracy as standard candles for cosmology. Five premier multi-wavelength sky regions are selected, each with extensive ancillary data. The use of five widely separated fields mitigates cosmic variance and yields statistically robust and complete samples of galaxies down to a stellar mass of 10(exp 9) solar mass to z approx. 2, reaching the knee of the UV luminosity function of galaxies to z approx. 8. The survey covers approximately 800 square arc minutes and is divided into two parts. The CANDELS/Deep survey (5(sigma) point-source limit H =27.7mag) covers approx. 125 square arcminutes within GOODS-N and GOODS-S. The CANDELS/Wide survey includes GOODS and three additional fields (EGS, COSMOS, and UDS) and covers the full area to a 50(sigma) point-source limit of H ? or approx. = 27.0 mag. Together with the Hubble Ultradeep Fields, the strategy creates a three-tiered "wedding cake" approach that has proven efficient for extragalactic surveys. Data from the survey are non-proprietary and are useful for a wide variety of science investigations. In this paper, we describe the basic motivations for the survey, the CANDELS team science goals and the resulting observational requirements, the field selection and geometry, and the observing design.

Grogin, Norman A.↗

Provenance Representation in the Global Change Information System (GCIS)

Global climate change is a topic that has become very controversial despite strong support within the scientific community. It is common for agencies releasing information about climate change to be served with Freedom of Information Act (FOIA) requests for everything that led to that conclusion. Capturing and presenting the provenance, linking to the research papers, data sets, models, analyses, observation instruments and satellites, etc. supporting key findings has the potential to mitigate skepticism in this domain. The U.S. Global Change Research Program (USGCRP) is now coordinating the production of a National Climate Assessment (NCA) that presents our best understanding of global change. We are now developing a Global Change Information System (GCIS) that will present the content of that report and its provenance, including the scientific support for the findings of the assessment. We are using an approach that will present this information both through a human accessible web site as well as a machine readable interface for automated mining of the provenance graph. We plan to use the developing W3C PROV Data Model and Ontology for this system.

Tilmes, Curt↗

Fast Lossless Compression of Multispectral-Image Data

An algorithm that effects fast lossless compression of multispectral-image data is based on low-complexity, proven adaptive-filtering algorithms. This algorithm is intended for use in compressing multispectral-image data aboard spacecraft for transmission to Earth stations. Variants of this algorithm could be useful for lossless compression of three-dimensional medical imagery and, perhaps, for compressing image data in general.

Klimesh, Matthew↗

Automating spectral unmixing of AVIRIS data using convex geometry concepts

Spectral mixture analysis, or unmixing, has proven to be a useful tool in the semi-quantitative interpretation of AVIRIS data. Using a linear mixing model and a set of hypothesized endmember spectra, unmixing seeks to estimate the fractional abundance patterns of the various materials occurring within the imaged area. However, the validity and accuracy of the unmixing rest heavily on the 'user-supplied' set of endmember spectra. Current methods for emdmember determination are the weak link in the unmixing chain.

Boardman, Joseph W.↗

Consist v0.1.0

A Python library for provenance tracking, intelligent caching, and data virtualization in scientific simulation workflows. It automatically records code, configuration, and input data to skip redundant computations and enables querying results across many runs without manual bookkeeping. Designed to support multi-model simulation workflows like the BEAM CORE toolset at LBL, but designed to be extensible to a wide range of research workflows. Combines lineage tracking features as provided by OpenLineage with deterministic hashing like SnakeMake, and adds powerful analysis tools on model outputs.

Needell, Zachary [Lawrence Berkeley National Labor↗

Trophic status of inland lakes from LANDSAT

A first-cut assessment of the trophic status of inland lakes in Wisconsin was obtained from LANDSAT data. To satisfy the criteria of the project, a large and versatile computer program was developed to gain access to LANDSAT data. This analysis technique has proven to be a cost-effective method of classifying inland lakes in Wisconsin.

Fisher, L. T.↗

Study of an astronomical extreme ultraviolet rocket spectrometer for use on shuttle missions

The adaptation of an extreme ultraviolet astronomy rocket payload for flight on the shuttle was studied. A sample payload for determining integration and flight procedures for experiments which may typically be flown on shuttle missions was provided. The electrical, mechanical, thermal, and operational interface requirements between the payload and the orbiter were examined. Of particular concern was establishing a baseline payload accommodation which utilizes proven common hardware for electrical, data, command, and possibly real time monitoring functions. The instrument integration and checkout procedures necessary to assure satisfactory in-orbit instrument performance were defined and those procedures which can be implemented in such a way as to minimize their impact on orbiter integration schedules were identified.

Bowyer, C. S.↗

Verification of an analytic modeler for capillary pump loop thermal control systems

A number of computer programs have been written to model two-phase heat transfer systems for space use. These programs support the design of thermal control systems and provide a method of predicting their performance in the wide range of thermal environments of space. Predicting the performance of one such system known as the capillary pump loop (CPL) is the intent of the CPL Modeler. By modeling two developed CPL systems and comparing the results with actual test data, the CPL Modeler has proven useful in simulating CPL operation. Results of the modeling effort are discussed, together with plans for refinements to the modeler.

Schweickart, R. B.↗

Centaurus A: Source Populations in the Nearest Bright Elliptical

The XMM/Newton observations of the nearby radio galaxy, Centaurus A, have proven to be a rich data set and has given us new insights into several important processes present in Centaurus A. A list of publications, conference proceedings, and conference abstracts related to these data are attached at the end of this document. We have used the XMM/Newton observations to study the interaction between the relativistic, radio emitting plasma emitted from active nuclei with the hot interstellar medium. Centaurus A is the nearest radio galaxy, so that we have been able to study these features at a linear resolution unattainable for any similar object.

Mushotzky, Richard↗

Lunar Meteorites Sayh Al Uhaymir 449 and Dhofar 925, 960, and 961: Windows into South Pole

In 2003, three lunar meteorites were collected in close proximity to each other in the Dhofar region of Oman: Dhofar 925 (49 g), Dhofar 960 (35 g), and Dhofar 961 (22 g). In 2006, lunar meteorite Sayh al Uhaymir (SaU) 449 (16.5 g) was found about 100 km to the NE. Despite significant differences in the bulk composition of Dhofar 961 relative to Dhofar 925/960 and SaU 449 (which are identical to each other), these four meteorites are postulated to be paired based on their find locations, bulk composition, and detailed petrographic analysis. Hereafter, they will collectively be referred to as the Dhofar 961 clan. Comparison of meteorite and component bulk compositions to Lunar Prospector 5-degree gamma-ray data suggest the most likely provenance of this meteorite group is within the South Pole-Aitken Basin. As the oldest, largest, and deepest recognizable basin on the Moon, the composition of the material within the SPA basin is of particular importance to lunar science. Here we review and expand upon the geochemistry and petrography of the Dhofar 961 clan and assess the likelihood that these meteorites come from within the SPA basin based on their bulk compositions and the compositions and characteristics of the major lithologic components found within the breccia.

Ziegler, Ryan A.↗

Simulation Technology at NASA

NASA Ames Research Center is home to several high-fidelity research flight and air-traffic control simulation facilities which, together with an experienced workforce, produce high-quality research data and findings that have proven to be applicable in the real world. These assets include the Vertical Motion Simulator (VMS), Crew Vehicle Systems Research Facility (CVSRF), Future Flight Central (FFC) air traffic control tower simulator, and several air-traffic control (ATC) simulators. The VMS combines a high-fidelity simulation capability with an adaptable simulation environment, enabling customization for numerous human-in-the-loop research applications. The distinctive feature of the VMS is its unparalleled large amplitude, high-fidelity motion capability. In over 30 years of continuous operation, the VMS has contributed significantly to the body of knowledge in a range of disciplines directly benefiting several aerospace programs and flight safety, including the design and development of flight control systems for the Joint Strike Fighter, Space Shuttle Orbiter, and rotorcraft. It continues to be used for researching new vehicle configurations, vehicle control and safety, transfer-of-training, etc., by NASA, other government agencies, and Industry.The CVSRF includes two motion-based flight simulators: a Boeing 747-400 full flight simulator and the reconfigurable Advanced Concepts Flight Simulator (ACFS). These simulators are primarily used to research air-traffic management concepts and procedures, advanced navigation and avionics concepts, and cockpit human factors. FFC is a full-sized control tower simulator with a 360-degree external field-of-view display system and reconfigurable system architecture. FFC and the ATC simulators are used for testing air-traffic management automation and decision support tools and demonstrate their feasibility in a realistic environment prior to technology transfer for implementation in the National Airspace System (NAS).To support integrated simulations and flight-tests for NASA's Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Project, NASA developed a distributed test environment incorporating Live, Virtual, Constructive, (LVC) concepts. Development of the software enabling the LVC is conducted primarily at the Distributed Simulation Research Lab (DSRL) at NASA Ames. The LVC components provide the core infrastructure supporting simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This provides the ability to conduct tests more efficiently by promoting the use of existing distributed assets. The LVC infrastructure was used in several human-in-the-loop simulations to evaluate acceptance of Detect and Avoid (DAA) advisories used by UAS pilots to maintain well clear of other virtual traffic and to negotiate maneuvers with air traffic control. It is currently being used to support testing of self-separation algorithms between unmanned and manned aircraft in live flight. Further simulations with more comprehensive air traffic scenarios mixing live and virtual aircraft is planned.In the current fiscal environment, maintaining and upgrading these high-fidelity simulation assets and retaining the skilled workforce necessary to meet future research needs is the primary non-technical challenge.

CVSRF↗

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

Germany, G. A.↗

Modeling and investigative studies of Jovian low frequency emissions

Jovian decametric (DAM) and hectometric (HOM) emissions were first observed over the entire spectrum by the Voyager 1 and 2 flybys of the planet. They display unusual arc-like structures on frequency-versus-time spectrograms. Software for the modeling of the Jovian plasma and magnetic field environment was performed. In addition, an extensive library of programs was developed for the retrieval of Voyager Planetary Radio Astronomy (PRA) data in both the high and low frequency bands from new noise-free, recalibrated data tapes. This software allows the option of retrieving data sorted with respect to particular sub-Io longitudes. This has proven to be invaluable in the analyses of the data. Graphics routines were also developed to display the data on color spectrograms.

Menietti, J. D.↗

Leverage Your Science Data Return by Flying with the International Earth Science Constellation (ESC)

Constellations have proven to be an effective and efficient way to acquire earth science data. By flying together, sensors on all satellites in a constellation take measurements of the same air, water, or land mass at essentially the same time. The sensors form a single "virtual satellite". The key to making a constellation effective and efficient is keeping the operations as independent as possible in order to minimize the operational burden and costs. The Earth Science Constellation (ESC) has been successful on all counts and continues to welcome new missions to continue its 18+ year record of coincidental earth science observations. The ESC also serves as a model for future constellation designs. This paper describes the ESC and its evolution from its initial launches in 1999 through the present and how new missions might benefit from joining the ESC.

Morning Constellation; Afternoon Constellation; Ea↗