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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Tidal Disruptions of Main Sequence Stars - II. Simulation Methodology and Stellar Mass Dependence of the Character of Full Tidal Disruptions

This paper introduces a series of papers presenting a quantitative theory for the tidal disruption of main-sequence stars by supermassive black holes. Using fully general relativistic hydrodynamics simulations and MESA-model initial conditions, we explore the pericenter-dependence of tidal disruption properties for eight stellar masses (0.15 < M_/M<10)and six black hole masses( ́10<MM105 105BH7). We present here the results most relevant to observations. The effects of internal stellar structure and relativity decouple for both the disruption cross section and the characteristic energy width of the debris. Moreover, the full disruption cross section is almost independent of Må for Må/Me3. Independent of Må, relativistic effects increase the critical pericenter distance for full disruption events by up to a factor of ∼3 relative to the Newtonian prediction. The probability of a direct capture is also independent of Må; at MBH/Me5×106this probability is equal to the probability of a complete disruption. The breadth of the debris energy distribution ΔE can differ from the standard estimate by factors of 0.35−2, depending on Må and MBH, implying a corresponding change(∝(ΔE)−3/2)in the characteristic mass-return timescale. We provide analytic forms, suitable for use in both event rate estimates and parameter inference, to describe all these trends. For partial disruptions, we find a nearly universal relation between the star’s angular momentum and the fraction of Må remaining. Within the “empty loss-cone” regime, partial disruptions must precede full disruptions. These partial disruptions can drastically affect the rate and appearance of subsequent total disruptions

Taeho Ryu↗
NASA NTRS2014

Frequency Estimator Performance for a Software-Based Beacon Receiver

As propagation terminals have evolved, their design has trended more toward a software-based approach that facilitates convenient adjustment and customization of the receiver algorithms. One potential improvement is the implementation of a frequency estimation algorithm, through which the primary frequency component of the received signal can be estimated with a much greater resolution than with a simple peak search of the FFT spectrum. To select an estimator for usage in a QV-band beacon receiver, analysis of six frequency estimators was conducted to characterize their effectiveness as they relate to beacon receiver design.

Frequency Domain Analysis↗
NASA NTRS2014

Frequency Estimator Performance for a Software-Based Beacon Receiver

As propagation terminals have evolved, their design has trended more toward a software-based approach that facilitates convenient adjustment and customization of the receiver algorithms. One potential improvement is the implementation of a frequency estimation algorithm, through which the primary frequency component of the received signal can be estimated with a much greater resolution than with a simple peak search of the FFT spectrum. To select an estimator for usage in a Q/V-band beacon receiver, analysis of six frequency estimators was conducted to characterize their effectiveness as they relate to beacon receiver design.

Radio Transmission↗
DOE OSTI2021

Changes in Climate and Its Effect on Timing of Snowmelt and Intensity-Duration-Frequency Curves

Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find rainfall intensities at several return levels. Generally, our results showed a decreasing trend in historical and future snow duration, rain-on-snow events, and snowmelt runoff. This decreasing trend in snowpack could reduce water resources. A statistically significant increase in maximum streamflow for most rivers at the Washington and North Dakota sites occurred for several months of the year. In Colorado, only a few months indicated such an increase. Future IDF curves for Colorado and North Dakota indicated a slight increase in rainfall intensity whereas the Washington site had about a twofold increase. This increase in rainfall intensity could result in major flood events, demonstrating the importance of accounting for climate changes in infrastructure planning.

58 GEOSCIENCES↗
NASA NTRS2019

Global and Regional Trends of Atmospheric Sulfur

The profound changes in global SO[subscript 2] emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and europe. europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and east Asia. the uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. the agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget.

Aas, Wenche↗
NASA NTRS2019

SO2 Emission Estimates Using OMI SO2 Retrievals for 2005-2017

SO2 column densities from OMI provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three OMI SO2 retrieval products (NASA standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4DVar/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in US, India and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA) 48% (BIRA) in India, but decrease in China by 23% (NASA) 33% (BIRA) since 2008. Compared to insitu measurements, the posterior GEOSChem surface SO2 concentrations have reduced NMB in China, the US, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using OMI observations.

Data assimilation↗
NASA NTRS1985

Geometry of miocene extensional deformation, lower Colorado River Region, Southeastern California and Southwestern Arizona: Evidence for the presence of a regional low-angle normal fault

The geometry of Miocene extensional deformation, which changes along a 120 km-long, northeast-trending transect from the southestern Chocolate Mountains, southeastern California, to the Trigo and southern Dome Rock Mountains, southwestern Arizona is discussed. Based upon regional differences in the structural response to extension and estimated extensional strain, the transet can be divided into three northwesterly-trending structural domains. From southwest to northeast, these domains are: (1) southestern Chocolate-southernmost Trigo Mountains; (2) central to northern Trigo Mountains; and (3) Trigo Peaks-southern Dome Rock Mountains. All structures formed during the deformation are brittle in style; fault rocks are composed of gouge, cohesive gouge, and local microbreccia. In each structural domain, exposed lithologic units are composed of Mesozoic crystalline rocks unconformably overlain by Oligocene to Early Miocene volcanic and minor interbedded sedimentary rocks. Breccia, conglomerate, and sandstone deposited synchronously with regional extension locally overlie the volcanic rocks. Extensional deformation largely postdated the main phase of volcanic activity, but rare rhyolitic tuff and flows interbedded with the syndeformational clastic rocks suggest that deformation began during the waning stages of valcanism. K-Ar isotopic ages indicate that deformation occurred in Miocene time, between about 22 and m.y. ago.

Tosdal, R. M.↗
NASA NTRS2015

Uncertainties in Isoprene Photochemistry and Emissions: Implications for the Oxidative Capacity of Past and Present Atmospheres and for Climate Forcing Agents

Current understanding of the factors controlling biogenic isoprene emissions and of the fate of isoprene oxidation products in the atmosphere has been evolving rapidly. We use a climate-biosphere-chemistry modeling framework to evaluate the sensitivity of estimates of the tropospheric oxidative capacity to uncertainties in isoprene emissions and photochemistry. Our work focuses on trends across two time horizons: from the Last Glacial Maximum (LGM, 21 000 years BP) to the preindustrial (1770s); and from the preindustrial to the present day (1990s). We find that different oxidants have different sensitivities to the uncertainties tested in this study, with OH being the most sensitive: changes in the global mean OH levels for the LGM-to-preindustrial transition range between -29 and +7, and those for the preindustrial-to-present day transition range between -8 and +17, across our simulations. Our results suggest that the observed glacial-interglacial variability in atmospheric methane concentrations is predominantly driven by changes in methane sources as opposed to changes in OH, the primary methane sink. However, the magnitudes of change are subject to uncertainties in the past isoprene global burdens, as are estimates of the change in the global burden of secondary organic aerosol (SOA) relative to the preindustrial. We show that the linear relationship between tropospheric mean OH and tropospheric mean ozone photolysis rates, water vapor, and total emissions of NOx and reactive carbon first reported in Murray et al. (2014) does not hold across all periods with the new isoprene photochemistry mechanism. Our results demonstrate that inadequacies in our understanding of present-day OH and its controlling factors must be addressed in order to improve model estimates of the oxidative capacity of past and present atmospheres.

methane↗
NASA NTRS1993

Accuracy requirements

Satellite and surface measurements, if they are to serve as a climate monitoring system, must be accurate enough to permit detection of changes of climate parameters on decadal time scales. The accuracy requirements are difficult to define a priori since they depend on unknown future changes of climate forcings and feedbacks. As a framework for evaluation of candidate Climsat instruments and orbits, we estimate the accuracies that would be needed to measure changes expected over two decades based on theoretical considerations including GCM simulations and on observational evidence in cases where data are available for rates of change. One major climate forcing known with reasonable accuracy is that caused by the anthropogenic homogeneously mixed greenhouse gases (CO2, CFC's, CH4 and N2O). Their net forcing since the industrial revolution began is about 2 W/sq m and it is presently increasing at a rate of about 1 W/sq m per 20 years. Thus for a competing forcing or feedback to be important, it needs to be of the order of 0.25 W/sq m or larger on this time scale. The significance of most climate feedbacks depends on their sensitivity to temperature change. Therefore we begin with an estimate of decadal temperature change. Presented are the transient temperature trends simulated by the GISS GCM when subjected to various scenarios of trace gas concentration increases. Scenario B, which represents the most plausible near-term emission rates and includes intermittent forcing by volcanic aerosols, yields a global mean surface air temperature increase Delta Ts = 0.7 degrees C over the time period 1995-2015. This is consistent with the IPCC projection of about 0.3 degrees C/decade global warming (IPCC, 1990). Several of our estimates below are based on this assumed rate of warming.

Delgenio, Anthony↗
DOE OSTI2021

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi Nuclear Power Plant

In this paper, we have developed a methodology to estimate the spatiotemporal distribution of radiation air dose rates around the Fukushima Daiichi Nuclear Power Plant (FDNPP). In our exploratory data analysis, we found that (1) the temporal evolution of dose rates is composed of a log-linear decay trend and fluctuations of air dose rates that are spatially correlated among adjacent monitoring posts; and (2) the slope of the log-linear environmental decay trend can be represented as a function of the apparent initial dose rates, coordinate position, land-use type, and soil type. From these observations, we first estimated the log-linear decay trend at each location based on these predictors, using the random forest method. We then developed a modified Kalman filter coupled with a Gaussian process model to estimate the dose-rate time series at a given location and time. We applied this method to the Fukushima evacuation zone (as of March 2017), which included 17 monitoring post locations (with monitoring datasets collected between 2014 and 2018) and generated a time series of dose-rate maps. Our results show that this approach allows us to produce accurate spatial and temporal predictions of radiation dose-rate maps using limited spatiotemporal measurements.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2010

Assessment of the Jason-2 Extension to the TOPEX/Poseidon, Jason-l Sea-Surface Height Time Series for Global Mean Sea Level Monitoring

The Jason-2 (OSTM) follow-on mission to Jason-I provides for the continuation of global and regional mean sea level estimates along the ground-track of the initial phase of the TOPEX/Poseidon mission. During the first several months, Jason-I and Jason-2 flew in formation separated by only 55 seconds, enabling the isolation of intermission instrument biases through direct collinear differencing of near simultaneous observations. The Jason-2 Ku-band range bias with respect to Jason-I is estimated to be -84 +/- 9 mm, based on the orbit altitudes provided on the Geophysical Data Records. Modest improved agreement is achieved with the GSFC replacement orbits, which further enables the isolation of subtle 1 cm) instrument-dependent range correction biases. Inter-mission bias estimates are confirmed with an independent assessment from comparisons to a 64-station tide-gauge network, also providing an estimate of the stability of the 17-year time series to be less than 0.1 mm/yr +/- 0.4 mm/yr. The global mean sea level derived from the multi-mission altimeter sea-surface height record from January 1993 through September 2009 is 3.3 +/- 0.4 mm/yr. Recent trends over the period from 2004 through 2008 are smaller and estimated to be 2.0 +/- 0.4 mm/yr.

Beckley, B. D.↗
DOE OSTI2021

Optimal interpolation of global dissolved oxygen: 1965–2015

Oxygen inventory of the global ocean has declined in recent decades potentially due to the warming-induced reduction in solubility as well as the circulation and biogeochemical changes associated with ocean warming and increasing stratification. Earth System Models predict continued oxygen decline for this century with profound impacts on marine ecosystem and fisheries. Observational constraint on the rate of oxygen loss is crucial for assessing the ability of models to accurately simulate these changes. There are only a few observational assessments of the global oceanic oxygen inventory reporting a range of oxygen loss. This study develops a gridded data set of dissolved oxygen for the global oceans using optimal interpolation method. The resulting gridded product includes full-depth map of dissolved oxygen as 5-year moving average from 1965 to 2015 with uncertainty estimates. The uncertainty can come from unresolved small-scale and high-frequency variability and mapping errors. The multi-decadal trend of global dissolved oxygen is in the range of -281 to -373 Tmol/decade. This estimate is more conservative than previous works. In this study, the grid points far from the observations are essentially set equal to zero anomaly from the climatology. Calculating global inventory with this approach produces a relatively conservative estimate; thus, the results from this study likely provide a useful lower bound estimate of the global oxygen loss.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

An Analysis of Simulated and Observed Global Mean Near-Surface Air Temperature Anomalies from 1979 to 1999: Trends and Attribution of Causes

The 1979 - 1999 response of the climate system to variations in solar spectral irradiance is estimated by comparing the global averaged surface temperature anomalies simulated by a 2D (two dimensional) energy balance climate model to observed temperature anomalies. We perform a multiple regression of southern oscillation index and the individual model responses to solar irradiance variations, stratospheric and tropospheric aerosol loading, stratospheric ozone trends, and greenhouse gases onto each of five near-surface temperature anomaly data sets. We estimate the observed difference in global mean near surface air temperature attributable to the solar irradiance difference between solar maximum and solar minimum to be between 0.06 and 0.11 K, and that 1.1 - 3.8% of the total variance in monthly mean near-surface air temperature data is attributable to nations in solar spectral irradiance. For the five temperature data sets used in our analysis, the trends in raw monthly mean temperature anomaly data have a large range, spanning a factor of 3 from 0.06 to 0.17 K/decade. However. our analysis suggests that trends in monthly temperature anomalies attributable to the combination of greenhouse gas, stratospheric ozone, and tropospheric sulfate aerosol variations are much more consistent among data sets, ranging from 0.16 to 0.24 K/decade. Our model results suggest that roughly half of the warming from greenhouse gases is cancelled by the cooling from changes in stratospheric ozone. Tropospheric sulfate aerosol loading in the present day atmospheric contributes significantly to the net radiative forcing of the present day climate system. However, because the change in magnitude and latitudinal distribution of tropospheric sulfate aerosol has been small over the past 20 years, the change in the direct radiative forcing attributable to changes in aerosol loading over this time is also small.

MacKay, R. M.↗
DOE OSTI2022

Internal variability and forcing influence model–satellite differences in the rate of tropical tropospheric warming

Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming. This approach allows us to disentangle the forced and unforced change in the model-simulated temperature of the midtroposphere (TMT). In applying the climate-model-trained machine-learning framework to observations, we estimate that external forcing has produced a tropical TMT trend of 0.25 ± 0.08 K⋅decade −1 between 1979 and 2014, but internal variability has offset this warming by 0.07 ± 0.07 K⋅decade −1 . Using the Community Earth System Model version 2 (CESM2) large ensemble, we also find that a discontinuity in the variability of prescribed biomass-burning aerosol emissions artificially enhances simulated tropical TMT change by 0.04 K⋅decade −1 . The magnitude of this aerosol-forcing bias will vary across climate models, but since the latest generation of climate models all use the same emissions dataset, the bias may systematically enhance climate-model trends over the satellite era. Our results indicate that internal variability and forcing uncertainties largely explain differences in satellite-versus-model warming and are important considerations when evaluating climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Commercial Building Fenestration Market Study

This study characterizes and assesses the U.S. commercial fenestration market. It analyzes a groundbreaking amount of data that will ultimately support an estimate of national savings potential of energy efficient fenestration products in commercial applications to demonstrate the benefits of efficient façade and fenestration systems. This study provides data and analysis on: commercial fenestration market and fenestration selection process, installed commercial fenestration stock across the U.S. and fenestration sales estimates, and current commercial building fenestration codes and market trends of installation to or above code.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1972

The transverse Poisson's ratio of composites.

An expression is developed that makes possible the prediction of Poisson's ratio for unidirectional composites with reference to any pair of orthogonal axes that are normal to the direction of the reinforcing fibers. This prediction appears to be a reasonable one in that it follows the trends of the finite element analysis and the bounding estimates, and has the correct limiting value for zero fiber content. It can only be expected to apply to composites containing stiff, circular, isotropic fibers bonded to a soft matrix material.

Foye, R. L.↗
NASA NTRS1988

Effect of a shallow low-viscosity zone on the formation of midplate swells

A finite-element numerical method is used here to analyze the effect of a low-viscosity zone on convection driven by heating from below in the upper mantle, in particular on the formation of midplate swells. The convective temperature and velocity solutions are calculated for different combinations of the viscosity in the top layer, the fluid layer thicknesses, and the Rayleigh number based on the viscosity in the bottom layer. The temperature solutions are used to calculate the geoid, topography, and heat flow anomalies, the elastic plate thickness, the depth of compensation, and an upper bound on the uplift time that result from the flow. The results are compared to data at the Hawaii, Bermuda, Cape Verde, and Marquesas swells. The magnitudes and the trend with age are consistent with theoretical and other estimates of the viscosity variation in the shallow upper mantle. Convective models can therefore explain the uplift and observed anomalies at midplate swells.

Robinson, E. M.↗