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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Driving terrestrial ecosystem models from space

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

Waring, R. H.↗
NASA NTRS2012

Closing the Seasonal Ocean Surface Temperature Balance in the Eastern Tropical Oceans from Remote Sensing and Model Reanalyses

The Eastern tropical ocean basins are regions of significant atmosphere-ocean interaction and are important to variability across subseasonal to decadal time scales. The numerous physical processes at play in these areas strain the abilities of coupled general circulation models to accurately reproduce observed upper ocean variability. Furthermore, limitations in the observing system of important terms in the surface temperature balance (e.g., turbulent and radiative heat fluxes, advection) introduce uncertainty into the analyses of processes controlling sea surface temperature variability. This study presents recent efforts to close the surface temperature balance through estimation of the terms in the mixed layer temperature budget using state-of-the-art remotely sensed and model-reanalysis derived products. A set of twelve net heat flux estimates constructed using combinations of radiative and turbulent heat flux products - including GEWEX-SRB, ISCCP-SRF, OAFlux, SeaFlux, among several others - are used with estimates of oceanic advection, entrainment, and mixed layer depth variability to investigate the seasonal variability of ocean surface temperatures. Particular emphasis is placed on how well the upper ocean temperature balance is, or is not, closed on these scales using the current generation of observational and model reanalysis products. That is, the magnitudes and spatial variability of residual imbalances are addressed. These residuals are placed into context within the current uncertainties of the surface net heat fluxes and the role of the mixed layer depth variability in scaling the impact of those uncertainties, particularly in the shallow mixed layers of the Eastern tropical ocean basins.

Roberts, J. Brent↗
NASA NTRS2022

The Importance of Internal Climate Variability in Climate Impact Projections

Uncertainty in climate projections is driven by three components: scenario uncertainty, intermodel uncertainty, and internal variability. Although socioeconomic climate impact studies increasingly take into account the first two components, little attention has been paid to the role of internal variability, although underestimating this uncertainty may lead to underestimating the socioeconomic costs of climate change. Using large ensembles from seven coupled general circulation models with a total of 414 model runs, we partition the climate uncertainty in classic dose–response models relating county-level corn yield, mortality, and per-capita gross domestic product to temperature in the continental United States. The partitioning of uncertainty depends on the time frame of projection, the impact model, and the geographic region. Internal variability represents more than 50% of the total climate uncertainty in certain projections, including mortality projections for the early 21st century, although its relative influence decreases over time. We recommend including uncertainty due to internal variability for many projections of temperature-driven impacts, including early-century and midcentury projections, projections in regions with high internal variability such as the Upper Midwest United States, and impacts driven by nonlinear relationships.

climate impacts↗
NASA NTRS1984

Dyads and triads at 35,000 feet - Factors affecting group process and aircrew performance

The task of flying a multipilot transport aircraft is a classic small-group performance situation where a number of social, organizational, and personality factors are relevant to important outcome variables such as safety. The aviation community is becoming increasingly aware of the importance of these factors but is hampered in its efforts to improve the system because of research psychology's problems in defining the nature of the group process. This article identifies some of the problem areas as well as methods used to address these issues. It is argued that high fidelity flight simulators provide an environment that offers unique opportunities for work meeting both basic and applied research criteria.

Foushee, H. C.↗
NASA NTRS1987

Dyads and triads at 35,000 feet: Factors affecting group process and aircrew performance

The task of flying a multipilot transport aircraft is a classic small-group performance situation where a number of social, organizational, and personality factors are relevant to important outcome variables such as safety. The aviation community is becoming increasingly aware of the importance of these factors but is hampered in its efforts to improve the system because of research psychology's problems in defining the nature of the group process. This article identifies some of the problem areas as well as methods used to address these issues. It is argued that high fidelity flight simulators provide an environment that offers unique opportunities for work meeting both basic and applied research criteria.

Foushee, H. Clayton↗
NASA NTRS1988

Seasat - Results of the mission

The scientific results of the Seasat mission are reviewed, including altimeter, scatterometer, microwave radiometer, and imaging radar studies. The analyses of Seasat data showed that global calibrations of satellite observations are much more accurate than measurements made at points on the ocean. It is found that the accuracy of satellite measurements of a particular variable are improved if the variable is measured by different instruments on the same satellite. The results suggest that important oceanographic variables can be mapped from space with accuracies required by climatological and scientific studies.

Stewart, Robert H.↗
NASA NTRS2010

New and Improved GLDAS and NLDAS Data Sets and Data Services at HDISC/NASA

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. Generating global fields of these variables, however, is still a challenge. The goal of a land data assimilation system (LDAS)is to ingest satellite-and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes data and, thereby, facilitate hydrology and climate modeling, research, and forecast.

Rui, Hualan↗
DOE OSTI2025

Characterization of Arsenic and Selenium in Coal Fly Ash to Improve Evaluations for Disposal and Reuse Potential (Final Technical Report)

Coal fly ash is a high volume waste material that is discarded in landfills and surface water impoundments across the U.S. and is also widely recycled for a variety of applications. The leaching of potential of contaminants of concern, such as arsenic (As) and selenium (Se), is often the driver of risk assessments for coal ash disposal and reuse. The extent of leachable As and Se depends on several factors related to environmental conditions and fly ash characteristics. Previous studies employed various methods to delineate the concentration, chemical form, and distribution of As and Se in fly ash materials. However, few studies have attempted to directly correlate these properties to mobilization parameters relevant to disposal and reuse. Instead, the coal residuals industries often rely upon standardized leaching protocols that can be laborious or involve hazardous chemicals. The goals of the project were to: 1) Develop and evaluate a characterization protocol that can be used to screen fly ash samples for leachability of As and Se; 2) Characterize As, Se, and associated constituents of fly ash particles at multiple length scales (nanometer to micrometer) to determine if elemental associations differ as a function of the resolution of characterization; and 3) Establish a predictive model for the chemical composition of coal ash produced annually at major U.S. coal fired power facilities on 50-year national coal supply records. For the first objective, we performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic coal regions. For this work, we assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition (LOI) and pH. The results of regression models indicated that major elements (Fe, Ca, Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As, but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash. For the second objective, we utilized nanoscale 2-D imaging (30-50 nm spot size) with the Hard X-ray Nanoprobe (HXN) in combination with microprobe X-ray capabilities (~5 µm resolution) to determine As and Se elemental associations in fly ash particles. Speciation of As and Se was also measured at the nano- to microscale with X-ray absorption spectroscopy. The enhanced resolution of HXN showed As and Se that were diffusely located around or comingled with Ca- and Fe-rich particles. The results also showed nanoparticles of Se attached to the surface of fly ash grains. Overall, a comparison of As and Se species across scales highlights the heterogeneity and complexity of chemical associations for these trace elements of concern in coal fly ash. For the final objective, we developed a predictive model for major element composition of coal ash in reserve at disposal sites of major U.S. coal fired power plants. This model was constructed from coal purchase records of 705 power stations from 1973-2022 and was trained on coal ash composition data showing that coal ash elemental composition is strongly associated with the source of feedstock coal. The model showed regional shifts in the major element contents of ash produced by power plants in the last 50 years, particularly for calcium and iron (expressed as %CaO and %Fe 2 O 3 ), as coal-fired power stations changed their source of coal over this time frame. Our approach enables an estimation of coal ash chemical composition that is stored in waste impoundments at individual power stations. Such information can help delineate the regional market potential for material applications that would utilize coal ash harvested from disposal sites across the U.S.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2000

Physiological basis for human autonomic rhythms

Oscillations of arterial pressures, heart periods, and muscle sympathetic nerve activity have been studied intensively in recent years to explore otherwise obscure human neurophysiological mechanisms. The best-studied rhythms are those occurring at breathing frequencies. Published evidence indicates that respiratory fluctuations of muscle sympathetic nerve activity and electrocardiographic R-R intervals result primarily from the action of a central 'gate' that opens during expiration and closes during inspiration. Parallel respiratory fluctuations of arterial pressures and R-R intervals are thought to be secondary to arterial baroreflex physiology: changes in systolic pressure provoke changes in the R-R interval. However, growing evidence suggests that these parallel oscillations result from the influence of respiration on sympathetic and vagal-cardiac motoneurones rather than from baroreflex physiology. There is a rapidly growing literature on the use of mathematical models of low- and high-frequency (respiratory) R-R interval fluctuations in characterizing instantaneous 'sympathovagal balance'. The case for this approach is based primarily on measurements made with patients in upright tilt. However, the strong linear relation between such measures as the ratio of low- to high-frequency R-R interval oscillations and the angle of the tilt reflects exclusively the reductions of the vagal (high-frequency) component. As the sympathetic component does not change in tilt, the low- to high-frequency R-R interval ratio provides no proof that sympathetic activity increases. Moreover, the validity of extrapolating from measurements performed during upright tilt to measurements during supine rest has not been established. Nonetheless, it is clear that measures of heart rate variability provide important prognostic information in patients with cardiovascular diseases. It is not known whether reduced heart rate variability is merely a marker for the severity of disease or a measurement that identifies functional reflex abnormalities contributing to terminal dysrhythmias.

Review, Tutorial↗
NASA NTRSDate not supplied

Multi-source Estimates of Land / Ocean Moisture Transport Variability over the Satellite Era

It is widely appreciated that atmospheric transport of water from the world’s oceans is a process key to planetary energy balance as well as Earth's habitability. What is not yet clear is the extent of variability in moisture transports, the relative importance of interdecadal variability versus climate change signals, and importantly, our ability to quantify these changes. This work assesses variations in moisture transport variability during the satellite era (~1980 to present) by comparing several different estimates. (i) The most direct estimate is the vertically integrated flux convergence of moisture from reanalyses which use observed wind and moisture information. (ii) One alternative estimate comes from P-ET over land taken from global hydrologic models constrained with precipitation and near-surface meteorology. Here we use an ensemble of six models. An adjunct to this method is to employ satellite derive ET (e.g., GLEAM or DOLCE). (iii) Complementary to this is E-P over the global oceans derived from satellite estimates of P such as TRMM, GPM and GPCP and SeaFlux V3 or J-OFURO3 estimates of E, all relying heavily upon microwave measurements. Transport between land and oceans must essentially balance at monthly scales, i.e., vanish globally. (iv) a fourth perspective comes from estimate of terrestrial RO + storage rate, delta S. G-RUN Ensemble which uses observed streamflow and P measurements to calibrate a statistical model provides the former while GRACE, GRACE-FO provide total water storage anomalies used to calculate storage rate changes. GRACE REC uses GRACE data to train a precipitation-driven statistical model to extend storage estimates before the GRACE era. (All of these alternatives to reanalysis estimates also consider the small atmospheric column water vapor contribution.) We examine the transport changes from these three different methodologies, their relative accuracies and discuss the origin of their differences. Regional trends in moisture flux divergence and their role in multi-decadal trends are considered. Interannual variability arising in connection with ENSO variability is a dominant signal, driven largely by P changes. Trends since 1980 include reductions in moisture delivery to the western U.S., eastern Brazil, and central Africa with recovery of moisture convergence to the Sahel and parts of eastern North America.

Franklin Robertson↗
NASA NTRS1993

Pseudospectral simulation of compressible turbulence using logarithmic variables

The direct numerical simulation of dissipative, highly compressible turbulent flow is performed using a pseudospectral Fourier technique. The governing equations are cast in a form where the important physical variables are the fluid velocity and the natural logarithms of the fluid density and temperature. Bulk viscosity is utilized to model polyatomic gases more accurately and to ensure numerical stability in the presence of strong shocks. Numerical examples include three-dimensional supersonic homogeneous turbulence and two-dimensional shock-turbulence interactions.

Shebalin, John V.↗
NASA NTRSDate not supplied

Review of Controllers for Low-Power Free-Piston Stirling Convertors

In this paper, a review of various controller approaches for free-piston Stirling convertors (FPSCs) for low-power radioisotope power systems (RPS) is conducted to compare their performances in terms of critical metrics and provide an insight for designing better controllers for future flight projects. Design variables and general analysis methods for the controllers are described and the controllers are classified into different categories based on important design variables, followed by discussions on the operating principles and properties of various controller approaches in each classification category. Moreover, key features of the state-of-the-art controller approaches are summarized whose designs are hypothetically extended to flight designs to compare their critical metrics such as the estimated size, weight, and power with cost (SWaP-C) and reliability. Finally, design suggestions are made to improve certain metrics for future flight development projects. Along with maturation of free-piston Stirling convertor technologies for radioisotope power systems over the last three decades, various types of controllers have been proposed, among which a couple of them were developed to the Engineering Model (EM) for the Advanced Stirling Radioisotope Generator (ASRG) flight development project. Further improvements of the controllers have been made recently at NASA GRC and the improvements will continue for future flight development projects.

Free-Piston Stirling Convertor Controller↗
NASA NTRSDate not supplied

Review of Controllers for Low-Power Free-Piston Stirling Convertors

In this paper, a review of various controller approaches for free-piston Stirling convertors (FPSCs) for low-power radioisotope power systems (RPS) is conducted to compare their performances in terms of critical metrics and provide an insight for designing better controllers for future flight projects. Design variables and general analysis methods for the controllers are described and the controllers are classified into different categories based on important design variables, followed by discussions on the operating principles and properties of various controller approaches in each classification category. Moreover, key features of the state-of-the-art controller approaches are summarized whose designs are hypothetically extended to flight designs to compare their critical metrics such as the estimated size, weight, and power with cost (SWaP-C) and reliability. Finally, design suggestions are made to improve certain metrics for future flight development projects. Along with maturation of free-piston Stirling convertor technologies for radioisotope power systems over the last three decades, various types of controllers have been proposed, among which a couple of them were developed to the Engineering Model (EM) for the Advanced Stirling Radioisotope Generator (ASRG) flight development project. Further improvements of the controllers have been made recently at NASA GRC and the improvements will continue for future flight development projects.

Free-Piston Stirling Convertor Controller↗
NASA NTRS2009

Statistical and Scaling Properties of Remotely-Sensed Soil Moisture in Two Contrasting Domains in the North American Monsoon Region

Characterizing soil moisture (theta) variability is important for inferring high-resolution information from coarse estimates provided by remote sensors. In this study, we analyze the spatial variability and scale invariance of high-resolution theta estimates collected in two contrasting semiarid areas, Arizona (AZ) and Sonora (SON), during the Soil Moisture Experiment - North American Monsoon in 2004 (SMEX04- NAME). Results reveal that as the mean theta condition ( ) becomes drier, the spatial standard deviation becomes smaller in both domains. The coefficient of variation of theta decreases with in SON, but does not display a clear tendency with in AZ. We also found the presence of scale invariance and multifractality in the range of support scales from 51.2 km to 0.8 km for all soil moisture fields in the two regions. The multifractal properties of theta are clearly linked to in SON, while the relation is affected by more dispersion in AZ. We argue this is due to differences in the dynamic (rainfall) and static (vegetation) controls on theta in the two domains.

Mascaro, Giuseppe↗
NASA NTRS2009

Modeling Bird Migration under Climate Change: A Mechanistic Approach

How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this behavior can be maintained over increasing and sustained environmental change. Also, the problem is much more complex than described by the current processes captured in our model. We have taken some important and interesting steps, and our model does demonstrate how local scale information about individual stop-over sites can be linked into the migratory flyway as a whole. We are incorporating additional, species specific, mechanistic processes to better reflect different climate change scenarios

Smith, James A.↗
NASA NTRS1983

Characterization of terrestrial ecosystems for biogeochemical studies using remote sensing

Work is in progress to estimate leaf area index (LAI) of temperate closed canopy coniferous forests using transects in Oregon and California. This variable will be measured using remote sensing techniques including correlations of ground dimensional analysis with linear waveband combinations. LAI will be related to important biological variables such as net primary productivity, biomass, and biogenic gas emission fluxes. The spatial variation in LAI, when coupled with species composition, will be used in part to describe the spatial variation and temporal dynamics of biogeochemical cycling.

Peterson, D. L.↗
NASA NTRS1983

Large-scale energy transformations in the high latitudes of the Northern Hemisphere

The kinetic energy balance and kinetic energy sources are studied for high latitudes north of 55 deg N with twice daily upper air observations during a seven-year period from 1973 to 1979. Energy variables are presented for 5 deg latitudinal zones from 55 to 75 deg N and for the polar cap north of 75 deg N. Spatial distributions of important energy variables are also presented. The upper level maximum of the cross-isobaric generation in high latitudes is observed in th lower stratosphere above the tropopause level in the winter and becomes insignificant during the summer. The flux convergence of potential energy from the source in lower latitudes is identified as the single major source for kinetic energy in higher latitudes. The contribution of the baroclinic conversion is minor. Examination during the First GARP Global Experiment winter indicates that the cold air outbreaks of the Asian winter monsoon are associated with noticeable changes in the hemispherical distributions of the fields of vertical motion and energetics in the high latitudes.

Kung, E. C.↗
DOE OSTI2026

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗