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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Characterizing the LANDSAT Global Long-Term Data Record

The effects of global climate change are fast becoming politically, sociologically, and personally important: increasing storm frequency and intensity, lengthening cycles of drought and flood, expanding desertification and soil salinization. A vital asset in the analysis of climate change on a global basis is the 34-year record of Landsat imagery. In recognition of its increasing importance, a detailed analysis of the Landsat observation coverage within the US archive was commissioned. Results to date indicate some unexpected gaps in the US-held archive. Fortunately, throughout the Landsat program, data have been downlinked routinely to International Cooperator (IC) ground stations for archival, processing, and distribution. These IC data could be combined with the current US holdings to build a nearly global, annual observation record over this 34-year period. Today, we have inadequate information as to which scenes are available from which IC archives. Our best estimate is that there are over four million digital scenes in the IC archives, compared with the nearly two million scenes held in the US archive. This vast pool of Landsat observations needs to be accurately documented, via metadata, to determine the existence of complementary scenes and to characterize the potential scope of the global Landsat observation record. Of course, knowing the extent and completeness of the data record is but the first step. It will be necessary to assure that the data record is easy to use, internally consistent in terms of calibration and data format, and fully accessible in order to fully realize its potential.

Arvidson, T.↗
NASA NTRS2019

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Marine Food Security Challenges

External interaction:The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency's new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

Schollaert Uz, Stephanie↗
NASA NTRS1972

Ultrasonic investigation of the superconducting properties of the Nb-Mo system

The superconducting properties of single crystals of Nb and two alloys of Nb with Mo were investigated by ultrasonic techniques. The results of measurements of the ultrasonic attenuation and velocities as a function of temperature, Mo composition, crystallographic direction, and ultrasonic frequency are reported. The attenuation and small velocity changes associated with the superconductivity of the samples are shown to be dependent on the sample resistivity ratio which varied from 4.3 for Nb-9% Mo to 6500 for pure Nb. The ultrasonic attenuation data are analyzed in terms of the superconducting energy gap term of the BCS theory. A new model is proposed for the analysis of ultrasonic attenuation in pure superconductors with two partially decoupled energy bands. To analyze the attenuation in pure superconducting Nb, the existence of two energy gaps was assumed to be associated with the two partially decoupled energy bands. One of the gaps was found to have the normal BCS value of 3.4 and the other gap was found to have the anomalously large value of 10. No experimental evidence was found to suggest that the second energy gap had a different transition temperature. The interpretation of the results for the Nb-Mo alloys is shown to be complicated by the possible existence of a second superconducting phase in Nb-Mo alloys with a transition temperature of 0.35 of the transition temperature of the first phase. The elastic constants of Nb and Nb-Mo alloys are shown to be approximately independent of Mo composition to nine atomic percent Mo. These results do not agree with the current microscopic theory of transition temperature for the transition elements.

Lacy, L. L.↗
NASA NTRS1978

Arc-jet test and analysis of Orbiter TPS inter-tile heating in high pressure gradient flow

During entry of the Space Shuttle Orbiter, the convective heating within inter-tile gaps of the Thermal Protection System (TPS) material produces elevated tile sidewall temperatures in regions of high surface pressure gradient. Arc-jet tests have been conducted recently to obtain a measure of the gap heating down the TPS tile sidewalls at test conditions representative of Orbiter flight environments. The object of this paper is to present the gap heating correlations that were developed from a thermal analysis for 3-D curved and flat TPS tile segments. Predictions of gap sidewall temperature were obtained within 30 F of test data on both Wing Glove and Double Wedge models. Derived heating ratios were obtained for a range of test conditions (pressure, pressure gradient, enthalpy, boundary layer thickness, gap width, surface temperature, etc.). The results of the study, which showed that heating ratios varied with the pressure gradient times the square root of the surface pressure, are being used to provide an assessment of gap filler requirements on Orbiter forward fuselage/chine and wing glove regions.

Rochelle, W. C.↗
NASA NTRSDate not supplied

Developing A Continuous Ozone Record Through the SAGE and Aura Missions With NASA Reanalysis Products

During the last quarter of the 20th century, the Stratospheric Aerosol and Gas Experiment (SAGE) missions were crucial in monitoring the loss and subsequent recovery of the stratospheric ozone layer. Due to the employed solar occultation and self-calibration method, the SAGE monitors have produced stable data throughout the lifetime of each instrument. However, over ten years passed between the end of the SAGE II and SAGE III/M3M missions in 2005 and the launch of SAGE III/ISS instrument in 2017, leaving a gap in the data that must be bridged in order to assess trends in the ozone record. The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis product, with output available starting in 1980, is an attractive candidate for trend analysis due to the statistically optimized combination of multiple observing systems and the regular temporal and spatial coverage. However, changes in the assimilated observation systems can introduce discontinuities within the MERRA-2 ozone record, such as in 2004 when the MERRA-2 system shifted from assimilating ozone retrievals collected by SBUV instruments to those collected by instruments onboard the Aura satellite. In this study, we explore using the SAGE II record as a transfer function to develop a stable reanalysis data product, suitable for trend analysis, from the start of the SAGE II record in 1984 through the present. We follow the procedure outlined by Wargan et al. (2018) to address discontinuities in the MERRA-2 ozone dataset at the 2004 transition and during the Aura record. SAGE II ozone profiles are used to correct discontinuities in upper stratospheric ozone associated with changes in the MERRA-2 meteorological observing system in 1998 and 1995. We will then assess the relative performance of the data from different SAGE sensors using the resulting bias-corrected MERRA-2 ozone fields.

Pamela Wales↗
NASA NTRS2018

Bridging the Engineering and Medicine Gap

A primary challenge NASA faces is communication between the disparate entities of engineers and human system experts in life sciences. Clear communication is critical for exploration mission success from the perspective of both risk analysis and data handling. The engineering community uses probabilistic risk assessment (PRA) models to inform their own risk analysis and has extensive experience managing mission data, but does not always fully consider human systems integration (HSI). The medical community, as a part of HSI, has been working 1) to develop a suite of tools to express medical risk in quantitative terms that are relatable to the engineering approaches commonly in use, and 2) to manage and integrate HSI data with engineering data. This talk will review the development of the Integrated Medical Model as an early attempt to bridge the communication gap between the medical and engineering communities in the language of PRA. This will also address data communication between the two entities in the context of data management considerations of the Medical Data Architecture. Lessons learned from these processes will help identify important elements to consider in future communication and integration of these two groups.

Walton, M.↗
NASA NTRS2014

Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

Landsat satellites↗
NASA NTRS2022

An Isolated Mass-gap Black Hole or Neutron Star Detected with Astrometric Microlensing

We present the analysis of five black hole candidates identified from gravitational microlensing surveys. Hubble Space Telescope astrometric data and densely sampled light curves from ground-based microlensing surveys are fit with a single-source, single-lens microlensing model in order to measure the mass and luminosity of each lens and determine if it is a black hole. One of the five targets (OGLE-2011-BLG-0462/MOA-2011-BLG-191 or OB110462 for short) shows a significant >1 mas coherent astrometric shift, little to no lens flux, and has an inferred lens mass of 1.6–4.4 M ⨀ . This makes OB110462 the first definitive discovery of a compact object through astrometric microlensing and it is most likely either a neutron star or a low-mass black hole. This compact-object lens is relatively nearby (0.70–1.92 kpc) and has a slow transverse motion of <30 kms -1 . OB110462 shows significant tension between models well fit to photometry versus astrometry, making it currently difficult to distinguish between a neutron star and a black hole. Additional observations and modeling with more complex system geometries, such as binary sources, are needed to resolve the puzzling nature of this object. For the remaining four candidates, the lens masses are <2M ⨀ , and they are unlikely to be black holes; two of the four are likely white dwarfs or neutron stars. We compare the full sample of five candidates to theoretical expectations on the number of black holes in the Milky Way (∼10 8 ) and find reasonable agreement given the small sample size.

Astrophysical black holes↗
NASA NTRS1988

Extension of a drought monitoring and vegetation classification methodology to the western Sahel

Biomass of growing vegetation over large semiarid regions can be estimated by digital manipulation of data from the AVHRR on NOAA polar-orbiting satellites. Here, the African Sahel is classified using a methodology which incorporates both the normalized difference and CAUSE procedures for the monitoring of vegetation during drought conditions. Preliminary analysis of color IR photographs taken on Space Shuttle missions indicates that such photographs can be digitized, registered to maps and other images, and utilized to fill temporal gaps in the historical record of data from unmanned satellites.

Mohler, Robert R. J.↗
NASA NTRS1982

Geographic science: Executive summary

The role that TM and MSS data play in the analysis of spatial patterns for land use/land cover, geomorphology studies, and the development of cartographic products is discussed. Tables listing geographic science data gaps, mission data requirements, and possible future remote sensing missions are included.

Source record↗
NASA NTRS2025

Mind the Gap: Addressing Data Gaps and Assessing Noise Mismodeling in LISA

Due to the sheer complexity of the Laser Interferometer Space Antenna (LISA) space mission, data gaps arising from instrumental irregularities and/or scheduled maintenance are unavoidable. Focusing on merger-dominated massive black hole binary signals, we test the appropriateness of the Whittle-likelihood on gapped data in a variety of cases. From first principles, we derive the likelihood valid for gapped data in both the time and frequency domains. Cheap-to-evaluate proxies to p-p plots are derived based on a Fisher-based formalism, and verified through Bayesian techniques. Our tools allow to predict the altered variance in the parameter estimates that arises from noise mismodeling, as well as the information loss represented by the broadening of the posteriors. The result of noise mismodeling with gaps is sensitive to the characteristics of the noise model, with strong low-frequency (red) noise and strong high-frequency (blue) noise giving statistically significant fluctuations in recovered parameters. We demonstrate that the introduction of a tapering window reduces statistical inconsistency errors, at the cost of less precise parameter estimates. We also show that the assumption of independence between inter-gap segments appears to be a fair approximation even if the data set is inherently coherent. However, if one instead assumes fictitious correlations in the data stream, when the data segments are actually independent, then the resultant parameter recoveries could be inconsistent with the true parameters. The theoretical and numerical practices that are presented in this work could readily be incorporated into global-fit pipelines operating on gapped data.

LISA↗
NASA NTRS2017

Validation of a Thermo-Ablative Model of Elastomeric Internal Insulation Materials

In thermo-ablative material modeling, as in many fields of analysis, the quality of the existing models significantly exceeds that of the experimental data required for their validation. In an effort to narrow this gap, a laboratory-scale internal insulation test bed was developed that exposes insulation samples to realistic solid rocket motor (SRM) internal environments while being instrumented to record real-time rates of both model inputs (i.e., chamber pressure, total surface heat flux, and radiative heat flux) as well as model outputs (i.e., material decomposition depths (MDDs) and in-depth material temperatures). In this work, the measured SRM internal environment parameters were used in conjunction with equilibrium thermochemistry codes as inputs to one-dimensional thermo-ablative models of the PBINBR and CFEPDM insulation samples used in the lab-scale test firings. The computed MDD histories were then compared with those deduced from real-time X-ray radiography of the insulation samples, and the calculated in-depth temperatures were compared with those measured by embedded thermocouples. The results of this exercise emphasize the challenges of modeling and testing elastomeric materials in SRM environments while illuminating the path forward to improved fidelity.

Martin, Heath T.↗
NASA NTRSDate not supplied

Spatiotemporal Methane Emissions from Global Lakes and Reservoirs

Inland aquatic systems, such as lakes and reservoirs, contribute substantially to global methane (CH4) emissions; yet are among the most uncertain components of the total CH4 budget. Lakes and reservoirs have received recent attention as they may generate high CH4 fluxes. Improved quantification of these CH4 fluxes, particularly their spatiotemporal distribution, is key to realistically incorporating them in CH4 modeling and budget studies. Here we report on a new global, gridded (0.25° lat × 0.25° lon) study of lake and reservoir CH4 emissions, accounting for new knowledge regarding lake and reservoir areal extent and distribution, and spatiotemporal emission patterns influenced by diurnal variability, temperature-dependent seasonality, satellite-derived freeze-thaw dynamics, and eco-climatic and physical CH4-centric type classification. The results of this new data set comprise daily CH4 emissions from lake and reservoirs throughout the full annual cycle and are tightly anchored to field observations, in situ measurements, and remote-sensing observations. Results show that reservoirs cover 297 × 103 km2 globally and emit 10.1 Tg CH4 yr-1 from diffusive (1.2 Tg CH4 yr-1) and ebullitive (8.9 Tg CH4 yr-1) emission pathways. On a global scale, CH4 emitting areas of lakes cover 1853 × 103 km2 and emit 37.1 Tg CH4 yr-1 from diffusive (17.1 Tg CH4 yr-1) and ebullitive (23.0 Tg CH4 yr-1) emission pathways and an additional ebullition flux of 5.2 Tg CH4 yr-1 upon ice-melt due to the accumulation of bubbles during the freeze period. This analysis of lakes and reservoir CH4 emission addresses multiple gaps and uncertainties in previous studies and represents an important contribution to studies of the global CH4 budget. The new data sets and methodologies from this study provide a framework to better understand and model the current and future role of lakes and reservoirs in the global CH4 budget and to guide efforts to mitigate inland aquatic system CH4 emissions. This presentation will describe the methodologies applied and the major results of this study focusing on the spatiotemporal distribution of lake and reservoir type classification, processes driving lake and reservoir emission seasonality, and the contribution of individual lake and reservoir types to the annual cycle of inland aquatic CH4 emissions.

Spatiotemporal↗
NASA NTRS1992

X ray observations of late-type stars using the ROSAT all-sky survey

The ROSAT mission made the first x ray survey of the entire sky using an imaging detector. Although ROSAT is a joint NASA/German project and involves direct American participation during its second phase of pointed observations, the all-sky survey remains the sole property of the German investigators. NASA grant represented the first use of ROSAT data analysis funds to support direct American participation in the ROSAT all-sky survey. The project involved a collaborative agreement between the Joint Institute for Laboratory Astrophysics (JILA) and the Max-Planck-Institut fur Extraterrestrische Physik (MPE) where JILA supplied MPE with a post-doctoral research associate with experience in the field of stellar (coronal) x ray emission to work within their ROSAT group. In return, members of the cool star research group at JILA were given the opportunity to collaborate on projects involving ROSAT all-sky survey data. Both sides have benefitted (and still benefit) from this arrangement since MPE suffers from a shortage of researchers who are interested in x ray emission from 'normal' stars and white dwarfs. MPE has also drawn upon experience in optical identification of x ray sources from the Einstein Extended Medium Sensitivity Survey in planning their own identification strategies for the ROSAT all-sky survey. The JILA cool stars group has benefitted since access to all-sky survey data has expanded the scope of their already extensive research programs involving multiwavelength observations of late-type stars. ROSAT was successfully launched on 1 June 1990 and conducted the bulk of the survey from 30 July 1990 to 25 January 1991. Data gaps in the survey have subsequently been made up. At the time of this writing (February 1992), the survey data have been processed once with the Standard Analysis Software System (SASS). A second processing will soon begin with improvements made to the SASS to correct errors and bugs found while carrying out scientific projects with data from the first processing. We outline the major research activities of Dr. Fleming over the past year (detailed accounts of his activities during the first two years of this grant can be found in the first-year and second-year status reports on this grant). Regarding the three specific projects which were proposed in the original proposal, two of them (White Dwarfs and Late M Dwarfs) are near completion. The results are described in two conference proceedings which are appended.

Linsky, Jeffrey L.↗
NASA NTRS1990

Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

Strub, P. Ted↗
NASA NTRSDate not supplied

Urban Air Mobility Fleet Manager Gap Analysis and System Design

NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in re-search to facilitate the introduction of air taxis into the US National Airspace System. Given the history of conventional aircraft operations, it is clear that dispatcher support will be required for UAM. This paper presents a gap analysis, system requirements, and a workstation design concept for the UAM dispatcher or Fleet Manager (FM) position. The gap analysis focuses on the differences be-tween the tasks of the airline dispatcher and those projected for the FM. FM system capabilities and data requirements are then presented as foundations for soft-ware development. An initial user interface concept is provided. The FM software uses a single, large display. The system supports prediction, monitoring, and task execution. This paper is intended to support FM software design for future air taxi systems.

Richard Mogford↗
NASA NTRS2005

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Williams, Mathew↗