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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 325 records · Page 18

Thermophysical property data and safety information

Precision measurements of the properties of oxygen over a wide range of temperature and pressure are complete. The primary remaining effort, which is in progress, is the representation of these data in the most usable format such as tables, equations, diagrams, and computer programs. In addition, safety data are essential to proper design, operation, and failure analysis. All of the available information on oxygen safety is being reviewed, evaluated and indexed for quick retrieval through the NASA Aerospace Safety Research and Data Institute program. The availability of data, where the major gaps in data occur, and retrieval of bibliographic information are discussed.

Kropschot, R. H.↗

Expansion of the Direct Feed High-Level Waste Glass Composition in the High Al Range

Baseline glass compositions have been developed and demonstrated for successful immobilization of Hanford high-level waste (HLW) prepared through a pretreatment process. Recent enhanced waste glass formulations have shown promise to increase the waste loading of pretreated sludge compositions from a broader range of HLW feeds. This project proposes to increase the loading of minimally pretreated Hanford HLW in glass by expanding the existing database and glass property-composition models. Estimated direct-feed high level waste (DFHLW) compositions were generated by the Hanford Tank Operations Contractor and used by Pacific Northwest National Laboratory to determine target glass compositions. Gaps in existing data were identified including one high-priority gap in the high Al compositional region. This report summarizes the data collected during the characterization of the DFHLW High Al Glass Matrix. These glasses were intentionally designed with high aluminum concentrations (15 to 30 wt%) and a high likelihood of nepheline formation, which is known to negatively affect glass durability. Some glasses were expected to either fail or approach property constraints to fill data gaps in poorly understood regions of the compositional space due to lack of data. Out of the 50 glasses tested, 14 glasses formed nepheline, while the model predicted nepheline formation in 20 glasses. All quenched glasses met the product consistency test durability constraint; however, 8 glasses failed this constraint after undergoing the canister centerline cooling treatment. Additionally, 17 glasses did not meet the viscosity constraints, 4 failed the EC constraints, and 2 exceeded the allowable T2% for spinel crystal formation. All glasses satisfied the SO 3 solubility limit. The resulting dataset provides valuable information to improve model accuracy and reduce prediction uncertainty. These insights will ultimately support the development of more robust glass formulation strategies, enabling higher waste loadings, reducing operational risks, and expanding the processing envelope.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Prediction of in-depth gap heating ratios from wing glove model test data

In-depth gap heating ratios were predicted down RSI tile sidewalls based on temperature measurements obtained from the JSC arc-jet Wing Glove model tests in order to develop gap heating ratios which resulted in the best possible fit of test data and to produce a set of engineering verification heating ratios similar in shape to one another which could be used at various body points on the Orbiter during reentry. The Rockwell TPS Multidimensional heat conduction program was used to perform 3-D thermal analyses using a 3.0 in. thick section of a curved RSI tile with 283 nodal points. Correlation with test data shows that the predicted heating ratios were significantly higher down in the gap than the zero pressure values for T/C stacks 39 and 38 on the Wing Glove model. For stack 37 (in a low pressure region), the baseline heating ratio overpredicted the temperature data. This analysis, which showed that the heating ratios were a strong function of the product of pressure and pressure gradient, will be used to compare with recent Gap/Step and Ames Double Wedge test/analysis results in the effort to identify the Orbiter gap response to high delta P flight environment.

Source record↗

Using Quality Attributes to Bridge Systems Engineering Gaps : A Juno Ground Data Systems Case Study

The Juno Mission to Jupiter is the second mission selected by the NASA New Frontiers Program. Juno launched August 2011 and will reach Jupiter July 2016. Juno's payload system is composed of nine instruments plus a gravity science experiment. One of the primary functions of the Juno Ground Data System (GDS) is the assembly and distribution of the CFDP (CCSDS File Delivery Protocol) product telemetry, also referred to as raw science data, for eight out of the nine instruments. The GDS accomplishes this with the Instrument Data Pipeline (IDP). During payload integration, the first attempt to exercise the IDP in a flight like manner revealed that although the functional requirements were well understood, the system was unable to meet latency requirements with the as-is heritage design. A systems engineering gap emerged between Juno instrument data delivery requirements and the assumptions behind the heritage flight-ground interactions. This paper describes the use of quality attributes to measure and overcome this gap by introducing a new systems engineering activity, and a new monitoring service architecture that successfully delivered the performance metrics needed to validate Juno IDP.

Ground Data Systems (GDS)↗

Error analysis for reducing noisy wide-gap concentric cylinder rheometric data for nonlinear fluids - Theory and applications

This work discusses the propagation of errors for the recovery of the shear rate from wide-gap concentric cylinder viscometric measurements of non-Newtonian fluids. A least-square regression of stress on angular velocity data to a system of arbitrary functions is used to propagate the errors for the series solution to the viscometric flow developed by Krieger and Elrod (1953) and Pawlowski (1953) ('power-law' approximation) and for the first term of the series developed by Krieger (1968). A numerical experiment shows that, for measurements affected by significant errors, the first term of the Krieger-Elrod-Pawlowski series ('infinite radius' approximation) and the power-law approximation may recover the shear rate with equal accuracy as the full Krieger-Elrod-Pawlowski solution. An experiment on a clay slurry indicates that the clay has a larger yield stress at rest than during shearing, and that, for the range of shear rates investigated, a four-parameter constitutive equation approximates reasonably well its rheology. The error analysis presented is useful for studying the rheology of fluids such as particle suspensions, slurries, foams, and magma.

Borgia, Andrea↗

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services.

54 ENVIRONMENTAL SCIENCES↗

Exploring the Use of DSCOVR/EPIC Satellite Observations to Monitor Vegetation Phenology

Vegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1–2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.

Weber, Maridee A.↗

Simulating PBX 9501 Gap-stick Experiment

It has previously been shown that the rate parameters of the SURF reactive burn model can be adjusted to fit the gap-stick data for PBX 9501 [Johnson et al., 2018, fig 4]. A recent recalibration of the SURF model for PBX 9501 (lot 730-010 at ρ = 1.837 g/cc 3 ) used different reactants and products EOS and an updated fitting form for the burn rate [Menikoff, 2021]. The new calibration fit gap-stick data [Hill et al., 2021] together with data from SDT experiments and curvature effect data. Here the results of gap-stick simulations using the xRage code are shown. They provide insight into the reactive flow in the gap-stick experiment.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Pulsar Polar Cap and Slot Gap Models: Confronting Fermi Data

Rotation-powered pulsars are excellent laboratories for studying particle acceleration as well as fundamental physics of strong gravity, strong magnetic fields and relativity. I will review acceleration and gamma-ray emission from the pulsar polar cap and slot gap. Predictions of these models can be tested with the data set on pulsars collected by the Large Area Telescope on the Fermi Gamma-Ray Telescope over the last four years, using both detailed light curve fitting and population synthesis.

Harding, Alice K.↗

Mission-oriented requirements for updating MIL-H-8501. Volume 2: STI background and rationale

A supplement to the structure of a new flying and ground handling qualities specification for military rotorcraft structure is presented in order to explain the background and rationale for the specification structure, the proposed forms of criteria, and the status of the existing data base. Critical gaps in the data base for the new structure are defined, and recommendations are provided for the research required to address the most important of these gaps.

Clement, W. F.↗

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open-forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap-filled. These data are available to download from Bonner, Smyth, et al. at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process-based snow model. We demonstrate the utility of these data with a modeling experiment that explores open-forest differences and identifies opportunities for improvements in model representation.

54 ENVIRONMENTAL SCIENCES↗

Jovian equatorial H2 emission from 1979-1987

Ninety two IUE observations of the Jovian equatorial region taken between 2 Dec. 1978 and 1 Feb. 1988 were averaged together by date of observation, resulting in 22 averaged spectra which were fit with a model to determine the amount of H2 Lyman band emission in the region 1552 to 1624A. The data suggest that the H2 emission may vary with time. Especially suggestive is the marked downward trend of the emission between 1983 and 1987, during which time the strength of the emission in the 1552 to 1624A region decreases by a factor of 10. Uncertainty in the existing data and a gap in the data in 1980 and 1981 preclude a positive identification of a correlation between the brightness of the H2 emission and the major solar cycle.

Mcgrath, M. A.↗

A Miniaturized Laser Heterodyne Radiometer for a Global Ground-Based Column Carbon Monitoring Network

We present progress in the development of a passive, miniaturized Laser Heterodyne Radiometer (mini-LHR) that will measure key greenhouse gases (C02, CH4, CO) in the atmospheric column as well as their respective altitude profiles, and O2 for a measure of atmospheric pressure. Laser heterodyne radiometry is a spectroscopic method that borrows from radio receiver technology. In this technique, a weak incoming signal containing information of interest is mixed with a stronger signal (local oscillator) at a nearby frequency. In this case, the weak signal is sunlight that has undergone absorption by a trace gas of interest and the local oscillator is a distributive feedback (DFB) laser that is tuned to a wavelength near the absorption feature of the trace gas. Mixing the sunlight with the laser light, in a fast photoreceiver, results in a beat signal in the RF. The amplitude of the beat signal tracks the concentration of the trace gas in the atmospheric column. The mini-LHR operates in tandem with AERONET, a global network of more than 450 aerosol sensing instruments. This partnership simplifies the instrument design and provides an established global network into which the mini-LHR can rapidly expand. This network offers coverage in key arctic regions (not covered by OCO-2) where accelerated warming due to the release of CO2 and CH4 from thawing tundra and permafrost is a concern as well as an uninterrupted data record that will both bridge gaps in data sets and offer validation for key flight missions such as OCO-2, OCO-3, and ASCENDS. Currently, the only ground global network that routinely measures multiple greenhouse gases in the atmospheric column is TCCON (Total Column Carbon Observing Network) with 18 operational sites worldwide and two in the US. Cost and size of TCCON installations will limit the potential for expansion, We offer a low-cost $30Klunit) solution to supplement these measurements with the added benefit of an established aerosol optical depth measurement. Aerosols induce a radiative effect that is an important modulator of regional carbon cycles. Changes in the diffuse radiative flux fraction (DRF) due to aerosol loading have the potential to alter the terrestrial carbon exchange.

Wilson, Emily L.↗

Report priority gaps in high temperature thermodynamic data (Interim Progress Report)

This interim progress report (Level 4 Milestone Number M4SF-26LL010203023) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite Host Rock Properties & Processes SF-26LL01020302. Our focus is to assess gaps in data availability and understanding for radionuclide thermodynamics within the context of a “hot repository” concept and expand SUPCRT-NE database development to address higher temperatures needed for a DPC DGR disposal concept. The database is intended to inform the argillite GDSA baseline model. The leading European thermochemical database (Thermochimie) is only applicable to temperatures below 80°C. Thus, a US effort to integrate and expand upon other international thermodynamics database efforts is needed, particular if a “hot repository” concept moves forward.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data-driven building energy modeling with feature selection and active learning for data predictive control

Three gaps impede the development of cost-effective and accurate data-driven building energy modeling/models (DBEM) for energy forecasting and predictive control strategies. Gap 1: data bias is common in building operation data, but this topic is hardly studied in DBEM; Gap 2: high data dimensionality is common in DBEM, but a systematic and scalable methodology is lacking to solve the problem; Gap 3: the interactions between data bias and high dimensionality have not been systematically studied for DBEM and predictive control in buildings. In this work, to address the three gaps mentioned above, we develop a framework that integrates active learning and feature selection for DBEM used for whole building data predictive control (or DPC, which is a branch of model predictive control). The framework provides a systematic methodology and automatic workflow that starts with raw data from building automation systems to the establishment of data-driven energy models for DPC controllers. The developed strategies and framework are evaluated in a virtual testbed based on EnergyPlus and BCVTB. Improved performance and reduced computational complexity are observed from the DBEM built with the developed framework, as well as the DPC controller based on that DBEM, indicating the effectiveness of the developed framework.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advancing Open Science in Atmospheric Research: Integrating Data Usability and Machine Learning

In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences." "In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences.

Jennifer Wei↗