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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation

Experimentation with several potentially promising techniques led to the selection of a fairly simple scheme for registration of data from the HCMM using an affine transformation. A method based solely on remote sensing was developed to estimate those meteorological effects which are required for thermal inertia mapping. It assumes that the atmospheric fluxes are spatially invariant and that the solar, sky and sensible heat fluxes can be approximated by a simple mathematical form. Coefficients are determined from least squares method by fitting observational data to the thermal model.

Watson, K.↗
NASA NTRS1985

Bolometric albedos of Titan, Uranus, and Neptune

The energy budgets of Titan, Uranus, and Neptune are reevaluated using new observational data on energy input as well as unpublished data on energy output. The bolometric geometric albedo of each object was determined, and preliminary determinations of the phase functions were used to compute the Bond albedos and effective temperatures. The values for the latter are 83 + or - 2 K for Titan, 57 + or - 2 K for Uranus, and 47 + or - 2 K for Neptune. The effective temperature of Titan is greater than the observed brightness temperatures in the thermal infrared region of the spectrum, indicating that the emissivity is less than unity for this part of the spectrum. An internal luminosity of (3.9 + or 1.1) x 10 to the 15th W is found for Neptune, and an upper limit of (0.6 + or - 1.4) x 10 to the 15th W is found for Uranus.

Neff, J. S.↗
DOE OSTI2020

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term, high-frequency measurements from ARM in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Multi-band, multi-epoch observations of the transiting warm Jupiter WASP-80b

WASP-80b is a warm Jupiter transiting a bright late-K/early-M dwarf, providing a good opportunity to extend the atmospheric study of hot Jupiters toward the lower temperature regime. We report multi-band, multi-epoch transit observations of WASP-80b by using three ground-based telescopes covering from optical (g', R{sub c}, and I{sub c} bands) to near-infrared (NIR; J, H, and K{sub s} bands) wavelengths. We observe 5 primary transits, each in 3 or 4 different bands simultaneously, obtaining 17 independent transit light curves. Combining them with results from previous works, we find that the observed transmission spectrum is largely consistent with both a solar abundance and thick cloud atmospheric models at a 1.7σ discrepancy level. On the other hand, we find a marginal spectral rise in the optical region compared to the NIR region at the 2.9σ level, which possibly indicates the existence of haze in the atmosphere. We simulate theoretical transmission spectra for a solar abundance but hazy atmosphere, finding that a model with equilibrium temperature of 600 K can explain the observed data well, having a discrepancy level of 1.0σ. We also search for transit timing variations, but find no timing excess larger than 50 s from a linear ephemeris. In addition, we conduct 43 day long photometric monitoring of the host star in the optical bands, finding no significant variation in the stellar brightness. Combined with the fact that no spot-crossing event is observed in the five transits, our results confirm previous findings that the host star appears quiet for spot activities, despite the indications of strong chromospheric activities.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Comments on the course of solar activity during the declining phase of solar cycle 20 /1970-74/

Observational data on sunspots, the 2800-MHz flux, and calcium plages are interpreted which were obtained during the declining phase of solar cycle 20. It is shown that three pulses of activity occurred during this period and resulted in two conspicuous 'stillstands' in the smooth means of the sunspot, 2800-MHz, and plage data. The longitudes of centers of sunspot and flare activity are found to have clustered in identifiable zones or hemispheres for relatively long periods of time. The sun is seen to have had a relatively inactive hemisphere centered about zero deg longitude, and certain well defined coronal holes were apparently located near the middle of this hemisphere. The first sunspot groups of cycle 21 are observed to have formed in the longitude zones associated with relatively high levels of activity during cycle 20.

Dodson, H. W.↗
DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

US wildfire potential: a historical view and future projection using high-resolution climate data

Abstract Recent wildfires in the western United States have led to substantial economic losses and social stresses. There is a great concern that the new climatic state may further increase the intensity, duration, and frequency of wildfires. To examine temporal and spatial features of historical wildfire trends and future changes, a common fire index, the Keetch–Byram Drought Index (KBDI), is calculated over the contiguous United States (CONUS) and Alaska. We introduce an efficient initialization method and calculate 36 years (1982–2017) of historical KBDI at 4 km using a high-quality observational dataset. KBDIs are also calculated at 12 km using regional climate models and extended into the mid- and late-21st century. Based on the observational data, annual mean (and 95th percentile) KBDI over forested regions in the southwestern and northwestern CONUS has risen since 1982 at a rate of 5.2 (4.0) and 2.9 (3.3) per year, respectively, indicating a persistent drying trend fostering fire activities; the number of days exceeding the top 5% historical KBDI has increased by 16 and 25 d in the 36 years. Multiple regional climate model simulations project increasing wildfire potential and longer fire seasons over broader areas based on the estimated KBDI for the mid- and late-21st century. By the end of the century, most of the CONUS would experience about 90–189 more days per year exceeding the historical local maximum KBDI; areas with high KBDI (>600), whose occurrence correlates with large burned area, are projected to broaden by nearly 60 times in the southern CONUS. While both temperature and precipitation contribute to future KBDI changes, warming is the main driver of more frequent, intense and wide-spread extreme wildfires indicated by high KBDIs in future projections.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Global correlation of topographic heights and gravity anomalies

The short wavelength features were obtained by subtracting a calculated 24th-degree-and-order field from observed data written in 1 deg x 1 deg squares. The correlation between the two residual fields was examined by a program of linear regression. When run on a worldwide scale over oceans and continents separately, the program did not exhibit any correlation; this can be explained by the fact that the worldwide autocorrelation function for residual gravity anomalies falls off much faster as a function of distance than does that for residual topographic heights. The situation was different when the program was used in restricted areas, of the order of 5 deg x 5 deg square. For 30% of the world,fair-to-good correlations were observed, mostly over continents. The slopes of the regression lines are proportional to apparent densities, which offer a large spectrum of values that are being interpreted in terms of features in the upper mantle consistent with available heat-flow, gravity, and seismic data.

Roufosse, M. C.↗
DOE OSTI2017

Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies

We propose a Bayesian approach for seismic inversion to estimate acoustic impedance, porosity and lithofacies within the reservoir conditioned to post-stack seismic and well data. The link between elastic and petrophysical properties is given by a joint prior distribution for the logarithm of impedance and porosity, based on a rock-physics model. The well conditioning is performed through a background model obtained by well log interpolation. Two different approaches are presented: in the first approach, the prior is defined by a single Gaussian distribution, whereas in the second approach it is defined by a Gaussian mixture to represent the well data multimodal distribution and link the Gaussian components to different geological lithofacies. The forward model is based on a linearized convolutional model. For the single Gaussian case, we obtain an analytical expression for the posterior distribution, resulting in a fast algorithm to compute the solution of the inverse problem, i.e. the posterior distribution of acoustic impedance and porosity as well as the facies probability given the observed data. For the Gaussian mixture prior, it is not possible to obtain the distributions analytically, hence we propose a Gibbs algorithm to perform the posterior sampling and obtain several reservoir model realizations, allowing an uncertainty analysis of the estimated properties and lithofacies. Both methodologies are applied to a real seismic dataset with three wells to obtain 3D models of acoustic impedance, porosity and lithofacies. The methodologies are validated through a blind well test and compared to a standard Bayesian inversion approach. Using the probability of the reservoir lithofacies, we also compute a 3D isosurface probability model of the main oil reservoir in the studied field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Assessing Clouds in GFDL's AM4.0 With Different Microphysical Parameterizations Using the Satellite Simulator Package COSP

We evaluate cloud simulations using satellite simulators against multiple observational data sets. These simulators have been run within the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0), as well as an alternative configuration where a fully two‐moment Morrison‐Gettelman cloud microphysical parameterization with prognostic precipitation (MG2) is applied, denoted as AM4‐MG2. The modeled cloud spatial distributions, vertical profiles, phase partitioning, cloud‐to‐precipitation transitions, and radiative effects compare reasonably well with satellite observations. Model biases include the under‐prediction of total and low‐level clouds, especially optically thin/intermediate clouds with cloud optical depth of less than 23, but the over‐prediction of thick clouds, indicating “too few, too bright” biases. These biases counteract each other, and give rise to reasonable estimates of cloud radiative effects. The underestimate of low‐level clouds is associated with too early and too frequent drizzle/precipitation formation. The precipitation bias is improved in AM4‐MG2, where the autoconversion scheme initiates the precipitation more realistically. There also exist discrepancies between models and observations for midlevel and high‐level clouds. Additional biases include the underestimate of liquid cloud fraction and the overestimate of ice cloud fraction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1962

A STATISTICAL OPTIMIZING NAVIGATION PROCEDURE FOR SPACE FLIGHT

In a typical self-contained space navigation system, celestial observation data are gathered and processed to produce estimated velocity corrections. The results of this paper provide a basis for determining the best celestial measurements and the proper time s to implement velocity corrections. Fundamental to the navigation system is a procedure for processing celestial measurement data which permits incorporation of each individual measurement as it is made in order to provide an improved estimate of position and velocity. In order to "optimize" the navigation, a statistical evaluation of a number of alternative courses of action is made. The various alternatives, which form the basis of a decision process, concern the following: 1) which star and planet combination provides the "best" available observation; 2) whether the best observation gives a sufficient reduction in the predicted target error to warrant making the measurement; and 3) whether the uncertainty in the indicated velocity correction is a small enough percentage of the correction itself to justify an engine re-start and propellant expenditure. Numerical results are presented which illustrate the effectiveness of this approach to the space navigation problem.

NAVIGATION↗
NASA NTRS1993

Cloud fields derived from satellite and surface data during FIRE cirrus phase 2

The interpretation of surface and aircraft measurements of cloud properties taken during field programs must take into account the large-scale cloud and meteorological conditions. Cloud properties are also required at scales beyond the point and line data taken from ground and aircraft platforms. Satellite data can provide a quantitative description of these large-scale cloud properties. When derived from geostationary satellite data, the cloud fields constitute a unique source for evaluating the development and demise of a cloud system. Satellites, however, can only see the tops of clouds, so that cloud layers below the uppermost cloud deck may remain undetected resulting in a incomplete depiction of the cloud system. Some multilayer clouds are amenable to detection from satellites. Many, especially in midlatitude cyclonic systems, can only be observed from the surface. A combination of surface and satellite cloud observations should be the most complete quantification of large-scale cloudiness if there are sufficient surface measurements. During the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Phase 2 (FIRE-2) Cirrus Intensive Field Observation (IFO) period (November 13 - December 7, 1991) conducted at Coffeyville, Kansas, cirrus observations were taken in a variety of conditions. The IFO area was selected for a variety of reasons including the relatively dense network of surface weather stations and special surface instrumentation sites. Thus, the FIRE-2 IFO presents an excellent opportunity to combine cloud observations from surface and satellite observations. This paper presents an analysis of cloud properties on a mesoscale grid using satellite cloud property retrievals, surface observer data, and rawinsonde temperature and humidity profiles.

Minnis, Patrick↗
NASA NTRS1996

Relationship of 133Xe cerebral blood flow to middle cerebral arterial flow velocity in men at rest

Cerebral blood flow (CBF) was measured by 133Xe clearance simultaneously with the velocity of blood flow through the left middle cerebral artery (MCA) over a wide range of arterial PCO2 in eight normal men. Average arterial PCO2, which was varied by giving 4% and 6% CO2 in O2 and by controlled hyperventilation on O2, ranged from 25.3 to 49.9 mm Hg. Corresponding average values of global CBF15 were 27.2 and 65.0 ml 100 g min-1, respectively, whereas MCA blood-flow velocity ranged from 42.8 to 94.2 cm/s. The relationship of CBF to MCA blood-flow velocity over the imposed range of arterial PCO2 was described analytically by a parabola with the equation: CBF = 22.8 - 0.17 x velocity + 0.006 x velocity2 The observed data indicate that MCA blood-flow velocity is a useful index of CBF response to change in arterial PCO2 during O2 breathing at rest. With respect to baseline values measured while breathing 100% O2 spontaneously, percent changes in velocity were significantly smaller than corresponding percent changes in CBF at increased levels of arterial PCO2 and larger than CBF changes at the lower arterial PCO2. These observed relative changes are consistent with MCA vasodilation at the site of measurement during exposure to progressive hypercapnia and also during extreme hyperventilation hypocapnia.

NASA Discipline Cardiopulmonary↗
NASA NTRS2021

Satellite imaging reveals increased proportion of population exposed to floods

Flooding affects more people than any other environmental hazard and hinders sustainable development. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods. Where and how floods occur and who is exposed are changing as a result of rapid urbanization4, flood mitigation infrastructure and increasing settlements in floodplains6. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255–290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58–86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods.

B.Tellman↗
DOE OSTI2023

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material is highly nonlinear in nature, as is common in biological tissue. In this work, we identify unknown material properties in continuum solid mechanics via physics-informed neural networks (PINNs). To improve the accuracy and efficiency of PINNs, we develop efficient strategies to nonuniformly sample observational data. We also investigate different approaches to enforce Dirichlet-type boundary conditions (BCs) as soft or hard constraints. Finally, we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space. The estimated material parameters achieve relative errors of less than 1%. As such, this work is relevant to diverse applications, including optimizing structural integrity and developing novel materials.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Study of bubble behavior in weightlessness (effects of thermal gradient and acoustic stationary wave) (M-16)

The aim of this experiment is to understand how bubbles behave in a thermal gradient and acoustic stationary wave under microgravity. In microgravity, bubble or bubbles in a liquid will not rise upward as they do on Earth but will rest where they are formed because there exists no gravity-induced buoyancy. We are interested in how bubbles move and in the mechanisms which support the movement. We will try two ways to make bubbles migrate. The first experiment concerns behavior of bubbles in a thermal gradient. It is well known than an effect of surface tension which is masked by gravity on the ground becomes dominant in microgravity. The surface tension on the side of the bubble at a lower temperature is stronger than at a higher temperature. The bubble migrates toward the higher temperature side due to the surface tension difference. The migration speed depends on the so-called Marangoni number, which is a function of the temperature difference, the bubble diameter, liquid viscosity, and thermal diffusivity. At present, some experimental data about migration speeds in liquids with very small Marangoni numbers were obtained in space experiments, but cases of large Marangoni number are rarely obtained. In our experiment a couple of bubbles are to be injected into a cell filled with silicon oil, and the temperature gradient is to be made gradually in the cell by a heater and a cooler. We will be able to determine migration speeds in a very wide range of Marangoni numbers, as well as study interactions between the bubbles. We will observe bubble movements affected by hydrodynamical and thermal interactions, the two kinds of interactions which occur simultaneously. These observation data will be useful for analyzing the interactions as well as understanding the behavior of particles or drops in materials processing. The second experiment concerns bubble movement in an acoustic stationary wave. It is known that a bubble in a stationary wave moves toward the node or the loop according to whether its diameter is larger or smaller than that of the main resonant radius. In our experiment fine bubbles will be observed to move according to an acoustic field formed in a cylindrical cell. The existence of bubbles varies the acoustic speed, and the interactive force between bubbles will make the bubble behavior collective and complicated. This experiment will be very useful to development of bubble removable technology as well as to the understanding of bubble behavior.

Azuma, H.↗
DOE OSTI2020

Dynamics of Gas Bubbles From a Submarine Hydrocarbon Seep Within the Hydrate Stability Zone

We validate a new model for mass transfer and bubble transport for natural seeps on the continental margins using an integrated observation of a seep at 883 m in the Northern Gulf of Mexico. In the model, mass transfer is assumed to transition from clean to dirty bubble mass transfer rates following a characteristic hydrate formation time that depends on the initial bubble surface area and the hydrate subcooling. We show that buoyancy-induced upwelling is negligible for the bubble stream. We initialize the model using precise data observed at the seafloor and validate the model results to optical and acoustic measurements within the bubble stream. The model accurately predicts the acoustic attenuation of the bubble flare by lateral spreading and bubble shrinkage throughout the water column. In conclusion, the model shows that up to 99.4% by mass of the released gases from this seep dissolves into the ocean within the hydrate stability zone.

03 NATURAL GAS↗
DOE OSTI2023

Pantropical Indo-Atlantic temperature gradient modulates multi-decadal AMOC variability in models and observations

Abstract Interconnections between ocean basins are recognized as an important driver of climate variability. Recent modeling evidence suggests that the North Atlantic climate can respond to persistent warming of the tropical Indian Ocean sea surface temperature (SST) relative to the rest of the tropics (rTIO). Here, we use observational data to demonstrate that multi-decadal changes in pantropical ocean temperature gradients lead to variations of an SST-based proxy of the Atlantic Meridional Overturning Circulation (AMOC). The largest contribution to this temperature gradient-AMOCconnection comes from gradients between the Indian and Atlantic Oceans. TherTIOindex yields the strongest connection of this tropical temperature gradient to theAMOC. Focusing on the internally generated signal in three observational products reveals that an SST-basedAMOCproxy index has closely followed low-frequency changes ofrTIOtemperature with about 26-year lag since 1870. Analyzing the pre-industrial control simulations of 44 CMIP6 climate models shows that theAMOCproxy index lags simulated mid-latitudeAMOCvariations by 4 ± 4 years. These model simulations reveal the mechanism connectingAMOCvariations to pantropical ocean temperature gradients at a 27 ± 2 years lag, matching the observed time lag in 28 out of the 44 analyzed models. rTIO temperature changes affect the North Atlantic climate through atmospheric planetary waves, impacting temperature and salinity in the subpolar North Atlantic, which modifies deep convection and ultimately the AMOC. Through this mechanism, observed internalrTIOvariations can serve as a multi-decadal precursor ofAMOCchanges with important implications forAMOCdynamics and predictability.

Meteorology & Atmospheric Sciences↗