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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Northern Colorado Water Resources: Using Earth Observations to Assess Relationships between Snowpack and Wildfires for Water Utility Management

In recent years, wildfires in the western U.S. have increased in size, frequency, and severity. Colorado is no exception to this trend, with many recent wildfires raising concerns. The Cameron Peak and East Troublesome Fires, the two largest recorded wildfires in Colorado history, burned over 400,000 acres in 2020. Wildfires pose a significant threat to high-elevation ecosystems, especially in terms of disturbances to watershed resources. Colorado’s annual water supply is dependent upon the melt and runoff of high-elevation snowpack, thus understanding wildfire effects is crucial. This project partnered with Northern Water, a water management company in Colorado, to explore fire impacts on Colorado Front Range watersheds and water supply forecasts. We investigated the use of remote sensing to study the influences of wildfire on snow depth, as Northern Water had previously relied on field-based observations of snowpack for their water supply forecasts. This project utilized airborne LiDAR data from Airborne Snow Observatories, Inc., Landsat 8 OLI derived products, as well as in situ snow survey data from Colorado State University to assess and model changes in snowpack over time. We uncovered key drivers of change in snowpack such as burn severity and snow zone and created a random forest model to determine and investigate their relationships. Despite temporal data availability limitations, analysis also showed that remotely-sensed snow depth measurements were strongly correlated with in situ snow depth measurements, revealing the accuracy and feasibility of using remote sensing technologies to study landscape-scale snowpack characteristics for water utility management purposes.

airborne LiDAR↗
DOE OSTI2025

Radio Frequency Transients Correlated with Electron Flux Measured On-Board the STP-Sat6

We analyzed transient electromagnetic signatures, referred to as spacecraft environment discharges (SEDs) or on-board discharges (OBDs), and the in-situ particle environment simultaneously measured by the Radio Frequency Sensor (RFS) and the Space and Atmospheric Burst Reporting System Z-plasma spectrometer (SABRS-ZPS), respectively. These sensors are on-board the U.S. Department of Defense Space Test Program Satellite 6 (STP-Sat6) in geostationary orbit. Radio frequency signatures of SEDs on STP-Sat6 have relatively high peak amplitudes; they often caused amplitude-saturation in the so-called high band (120–140 MHz frequency range) of the RFS likely due to the proximity of their source to the RFS’s dipole antennas. We examined the occurrence rate of SEDs reported by the RFS and its temporal relationship to electron flux in the 7.9–12.2 keV range. Peaks in SED count rates were time-correlated with peaks in electron flux. The electron-flux peaks appeared to lead the SED count rate peaks by 24–45 min for the 7.9–12.2 keV energies. This indicates that incidence of electrons at this relatively low-energy range likely resulted in ramping up of the charging of the spacecraft leading to periods of high occurrence rates of discharges in and around the spacecraft.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Abstract Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

36 MATERIALS SCIENCE↗
NASA NTRS1989

The effect of spatial and temporal wet-troposphere fluctuations on connected element interferometry

Numerical integrations of the structure function of tropospheric inhomogeneities have been performed to assess the impact of water vapor fluctuations on connected element interferometry (CEI). The expectation value of the RMS troposphere error for a differential spacecraft-quasar observation is derived by integrating the spatial refractivity structure function along raypaths to both the spacecraft and quasar from two spatially separated sites. Correlations between the tropospheric conditions at the two sites, which can become significant for short baseline observations, are fully accounted for in this calculation. Temporal effects are treated by assuming a frozen-flow model in which a fixed spatial distribution blows over both sites. Two nominal observation scenarios are considered, along with variations to study the dependence of the resultant differential troposphere errors on baseline length, observation time, source separation angle, and elevation. Consecutive differential observations are found to be almost completely uncorrelated, implying that averaging many repeated differential observations can quickly reduce the troposphere error.

Edwards, C. D.↗
NASA NTRS1983

An ISEE 3 high time resolution study of interplanetary parameter correlations with magnetospheric activity

The coupling between the solar wind and the geomagnetic disturbances was examined using data from the ISEE-3 spacecraft at an earth-sun libration point and ground-based data. One minute data were used to avoid aliasing in determining the internal magnetospheric response to solar wind conditions. Attention was given to the cross-correlations between the geomagnetic index (AE), the total energy dissipation rate (UT), and the solar wind parameters, as well as the spatial and temporal scales on which the magnetosphere reacts to the solar wind conditions. It was considered necessary to characterize the physics of the solar wind-magnetosphere coupling in order to define the requirements for a spacecraft like the ISEE-3 that could be used as a real time monitoring system for predicting storms and substorms. The correlations among all but one parameter were lower during disturbance intervals; UT was highly correlated with all parameters during the disturbed times. An intrinsic 25-40 min delay was detected between interplanetary activity and magnetospheric response in quite times, diminishing to no more than 15 min during disturbed times.

Baker, D. N.↗
NASA NTRS1997

Collective Interaction of a Compressible Periodic Parallel Jet Flow

A linear instability model for multiple spatially periodic supersonic rectangular jets is solved using Floquet-Bloch theory. The disturbance environment is investigated using a two dimensional perturbation of a mean flow. For all cases large temporal growth rates are found. This work is motivated by an increase in mixing found in experimental measurements of spatially periodic supersonic rectangular jets with phase-locked screech. The results obtained in this paper suggests that phase-locked screech or edge tones may produce correlated spatially periodic jet flow downstream of the nozzles which creates a large span wise multi-nozzle region where a disturbance can propagate. The large temporal growth rates for eddies obtained by model calculation herein are related to the increased mixing since eddies are the primary mechanism that transfer energy from the mean flow to the large turbulent structures. Calculations of growth rates are presented for a range of Mach numbers and nozzle spacings corresponding to experimental test conditions where screech synchronized phase locking was observed. The model may be of significant scientific and engineering value in the quest to understand and construct supersonic mixer-ejector nozzles which provide increased mixing and reduced noise.

Miles, Jeffrey Hilton↗
NASA NTRS2023

Multiyear Dry Periods in Southern Africa

Characteristics and physical features related to low precipitation across many years in Southern Africa that lead to societal disruptions are diagnosed using observed analyses and an ensemble of historical coupled climate model simulations during 1921 to 2014. Four regions are evaluated, as identified through a hierarchical clustering algorithm applied to the Standardized Precipitation Index (SPI) during the October–April precipitation season. Although dryness spanning many October–April occurs periodically in each region, they seldom occur simultaneously, consistent with largely insignificant SPI cross-correlations between them. However, characteristics relevant to low precipitation across many years are generalizable between the four regions, including the serial persistence of October–April precipitation, the likelihood of consecutive dry October–April, and the likelihood of dry October–April in temporal extents of up to 10 consecutive such 7-month seasons. Systematic precipitation persistence is not a feature in any of the four Southern Africa regions, as serial correlations of October–April SPI are not statistically significant at any time lags. It follows that there is an exponential-folding decay in the likelihood of consecutive October–April for various SPI thresholds and that there is a large spread in the likelihood of low October–April SPI across many years. In terms of physical features, low October–April SPI in each Southern Africa region is closely related to local atmospheric circulations; however, they are not as closely related to sea surface temperatures (SSTs). These results suggest that dryness spanning many years is determined primarily by persistent local circulations related to atmospheric variability and to a lesser extent variability related to SST anomalies, including the El Niño–Southern Oscillation.

subtropical Indian Ocean dipole↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Human influence on joint changes in temperature, rainfall and continental aridity

Despite the pervasive impact of drought on human and natural systems, the large-scale mechanisms conducive to regional drying remain poorly understood. Here we use a multivariate approach to identify two distinct externally forced fingerprints from multiple ensembles of Earth system model simulations. The leading fingerprint, F M1 (x), is characterized by global warming, intensified wet–dry patterns and progressive large-scale continental aridification, largely driven by multidecadal increases in greenhouse gas (GHG) emissions. The second fingerprint, F M2 (x), captures a pronounced interhemispheric temperature contrast, associated meridional shifts in the intertropical convergence zone and correlated anomalies in precipitation and aridity over California, the Sahel and India. F M2 (x) exhibits nonlinear temporal behaviour: the intertropical convergence zone moves southwards before 1975 in response to increases in hemispherically asymmetric sulfate aerosol emissions, and it shifts northwards after 1975 due to reduced sulfur dioxide emissions and the GHG-induced warming of Northern Hemisphere landmasses. Both fingerprints are statistically identifiable in observations of joint changes in temperature, rainfall and aridity during 1950–2014. Furthermore, we show that the reliable simulation of these changes requires combined forcing by GHGs, direct and indirect effects of aerosols, and large volcanic eruptions. Our results suggest that GHG-induced aridification may be modulated regionally by future reductions in sulfate aerosol emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Are Methanol-Derived Foliar Methyl Acetate Emissions a Tracer of Acetate-Mediated Drought Survival in Plants?

Upregulation of acetate fermentation in plants has recently been described as an evolutionarily conserved drought survival strategy, with the amount of acetate produced directly correlating to survival. However, destructive measurements are required to evaluate acetate-linked drought responses, limiting the temporal and spatial scales that can be studied. Here, 13C-labeling studies with poplar (Populus trichocarpa) branches confirmed that methyl acetate is produced in plants from the acetate-linked acetylation of methanol. Methyl acetate emissions from detached leaves were strongly stimulated during desiccation, with total emissions decreasing with the leaf developmental stage. In addition, diurnal methyl acetate emissions from whole physiologically active poplar branches increased as a function of temperature, and light-dark transitions resulted in significant emission bursts lasting several hours. During experimental drought treatments of potted poplar saplings, light-dark methyl acetate emission bursts were eliminated while strong enhancements in methyl acetate emissions lasting > 6 days were observed with their initiation coinciding with the suppression of transpiration and photosynthesis. The results suggest that methyl acetate emissions represent a novel non-invasive tracer of acetate-mediated temperature and drought survival response in plants. The findings may have important implications for the future understanding of acetate-mediated drought responses to transcription, cellular metabolism, and hormone signaling, as well as its associated changes in carbon cycling and water use from individual plants to whole ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Jovian H2 dayglow emission (1978-1989)

The IUE data set accumulated through 10 years of Jovian equatorial observations is used to measure the long-term temporal variation of the H2 dayglow emission. The model that best fits the data indicates a possible correlation between long-term solar activity and the Jovian H2 emission in the region 1500-1700 A between 1978 and 1989, which spans the decline in solar activity for solar cycle 21 and the rise in solar activity accompanying solar cycle 22. The magnitude of the observed variation is closer to that of the solar Ly-alpha flux than the 10.7 cm radio flux. Short-wavelength H2 band emission intensity is inconsistent with the amount of long-wavelength emission but may be reconciled if relatively low-energy excitation or fluorescence of solar radiation is invoked. No persistent longitudinal feature analogous to the H I Ly-alpha can be identified.

Mcgrath, M. A.↗
NASA NTRS2011

Solar Flares

Solar flares accelerate both ions and electrons to high energies, and their X-ray and gamma-ray signatures not only probe the relationship between their respective acceleration, but also allow for the measurement of accelerated and ambient abundances. RHESSI observations have shown a striking close linear correlation of gamma-ray line fluence from accelerated ions > approx.20 MeV and bremsstrahlung emission from relativistic accelerated electrons >300 keV, when integrated over complete flares, suggesting a common acceleration mechanism. SMM/GRS observations, however, show a weaker correlation, and this discrepancy might be associated with previously observed electron-rich episodes within flares and/or temporal variability of gamma-ray line fluxes over the course of flares. We use the latest RHESSI gamma-ray analysis techniques to study the temporal behavior of the RHESSI flares, and determine what changes can be attributed to an evolving acceleration mechanism or to evolving abundances.

Shih, Albert↗
NASA NTRS2017

Intracranial Fluid Redistribution During a Spaceflight Analog

The neural correlates of spaceflight-induced sensorimotor impairments are unknown. Head down-tilt bed rest (HDBR) serves as a microgravity analog because it mimics the headward fluid shift and limb unloading of spaceflight. We investigated focal brain white matter (WM) changes and fluid shifts during 70 days of 6 deg HDBR in 16 subjects who were assessed pre (2x), during (3x), and post-HDBR (2x). Changes over time were compared to those in control subjects (n=12) assessed four times over 90 days. Diffusion MRI was used to assess WM microstructure and fluid shifts. Free-Water Imaging, derived from diffusion MRI, was used to quantify the distribution of intracranial extracellular free water (FW). Additionally, we tested whether WM and FW changes correlated with changes in functional mobility and balance measures. HDBR resulted in FW increases in fronto-temporal regions and decreases in posterior-parietal regions that largely recovered by two weeks post-HDBR. WM microstructure was unaffected by HDBR. FW decreased in the post-central gyrus and precuneus. We previously reported that gray matter increases in these regions were associated with less HDBR-induced balance impairment, suggesting adaptive structural neuroplasticity. Future studies are warranted to determine causality and underlying mechanisms.

Koppelmans, Vincent↗
NASA NTRS2019

The Relationship between Workload, Performance and Fatigue in a Short-Haul Airline

Short-haul flights are associated with irregular work schedules and increased workload, due to frequent takeoffs and landings. We examined the relationship between pilot workload, performance and subjective fatigue during normal short-haul operations. Ninety airline pilots (8 female), mean age 33 (±8 years) completed a NASA-Task Load Index (NASA-TLX), a Psychomotor Vigilance Task (PVT; a reaction time test sensitive to sleep loss) and a Samn-Perelli (SP) fatigue scale, over a period of 20 duty days at top-of-descent on 2762 short-haul flights. The duty days included either 2 or 4 flights per day starting at different times as scheduled during normal operations. Workload was measured using the six NASA-TLX scales: mental demand, physical demand, temporal demand, effort, performance and frustration. Lapses (reaction times [RT] > 500ms) were calculated for the PVT. Spearman correlations were calculated to identify relationships between the NASA-TLX, PVT lapses, and SP. The six scales of NASA-TLX were positively correlated with the PVT lapses (p < 0.01) showing an increase in workload when lapses increased. There was a positive correlation between subjective fatigue as measured by the SP fatigue scale and each of the six scales of NASA-TLX (p < 0.001) suggesting that pilots reported higher workload when perceived levels of fatigue were higher. Of the six workload scales, mental demand and performance were rated the highest (mental: M = 40.99, SD = 20.32; performance: M = 41.61, SD = 20.71) and effort was rated the lowest (M = 15.59, SD = 8.98). Preliminary analyses suggest that high workload is associated with poorer PVT performance and increased self-reported fatigue in this population of short-haul pilots. Future studies should explore how other workload factors (i.e. flight hours, time of day) influence self-reported and objective fatigue measures.

TLX↗
NASA NTRS2020

Human influence on joint changes in temperature, rainfall and continental aridity

Despite the pervasive impact of drought on human and natural systems, the large-scale mechanisms conducive to regional drying remain poorly understood. Here we use a multivariate approach to identify two distinct externally forced fingerprints from multiple ensembles of Earth system model simulations. The leading fingerprint, F(M1)(x), is characterized by global warming, intensified wet–dry patterns and progressive large-scale continental aridification, largely driven by multidecadal increases in greenhouse gas (GHG) emissions. The second fingerprint, F(M2)(x), captures a pronounced interhemispheric temperature contrast, associated meridional shifts in the intertropical convergence zone and correlated anomalies in precipitation and aridity over California, the Sahel and India. F(M2)(x) exhibits nonlinear temporal behaviour: the intertropical convergence zone moves southwards before 1975 in response to increases in hemispherically asymmetric sulfate aerosol emissions, and it shifts northwards after 1975 due to reduced sulfur dioxide emissions and the GHG-induced warming of Northern Hemisphere landmasses. Both fingerprints are statistically identifiable in observations of joint changes in temperature, rainfall and aridity during 1950–2014. We show that the reliable simulation of these changes requires combined forcing by GHGs, direct and indirect effects of aerosols, and large volcanic eruptions. Our results suggest that GHG-induced aridification may be modulated regionally by future reductions in sulfate aerosol emissions.

Human influence↗
NASA NTRS2022

Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery

In mountainous environments, topography strongly affects the reflectance due to illumination effects and cast shadows, which introduce errors in land cover classifications. However, topographic correction is not routinely implemented in standard data pre-processing chains (e.g., Landsat Analysis Ready Data), and there is a lack of consensus whether topographic correction is necessary, and if so, how to conduct it. Furthermore, methods that correct simultaneously for atmospheric and topographic effects are becoming available, but they have not been compared directly. Our objects were to investigate (1) the effectiveness of two topographic correction approaches that integrate atmospheric and topographic correction, (2) improvements in classification accuracy when analyzing topographically corrected single-date imagery (14 July 2016 and 2 October 2016), versus a full Landsat time series from 2014 to 2016, and 3) improvements in classification accuracy when including additional terrain information (i.e., topographic slope, elevation, and aspect). We developed a physical based model and compared it with an enhanced C-correction, both of which integrate atmospheric and topographic correction. We compared classification accuracies with and without topographic correction using combinations of single-date imagery, image composites and spectral-temporal metrics generated from the full Landsat time series, and additional terrain information in the Caucasus Mountains. We found that both the enhanced C-correction and the physical model performed very well and largely eliminated the correlation (Pearson’s correlation coefficient r ranges from 0.06 to 0.24) between surface reflectance and illumination condition, but the physical model performed best (r ranges from 0.05 to 0.11). Both image composites, and spectral-temporal metrics generated from corrected imagery, resulted in significantly (p ≤ 0.05) higher classification accuracies and better forest classifications, especially for the mixed forests. Adding terrain information reduced classification error significantly, but not as much as topographic correction. In summary, topographic correction remains necessary, even when analyzing a full Landsat time series and including a digital elevation model in the classification. We recommend that topographic correction should be applied when analyzing Landsat satellite imagery in mountainous region for forest cover classification.

Atmospheric correction↗