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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Experimental analysis of spatial correlation effects on capillary trapping of supercritical CO 2 at the intermediate laboratory scale in heterogeneous porous media

Several numerical studies have demonstrated that the heterogeneous nature of typical sedimentary formations can favorably dampen the accumulation of mobile CO 2 phase underneath the caprock. Core flooding experiments have also shown that contrasts in capillary entry pressure can lead to buildup of nonwetting fluid phase (NWP) at interfaces between facies. Explicit representation of geological heterogeneity at the intermediate (cm-to-m) scale is a powerful approach to identify the key mechanisms that control multiphase flow dynamics in porous media. The ability to carefully control flow regime and permeability contrast at a scale that is relevant to CO 2 plume dynamics in saline formations offers valuable information to understand immiscible displacement processes and provides a benchmark for mathematical models. To provide insight into the impact of capillary heterogeneity on flow dynamics and trapping efficiency of supercritical CO 2 under successive drainage and imbibition conditions, we present an experimental investigation conducted in a synthetic sand reservoir. By mimicking the interplay of governing forces at reservoir conditions via application of surrogate fluids, we performed three immiscible displacement experiments to observe the entrapment of NWP in heterogeneous porous media. Capillary trapping performance is evaluated for each scenario through spatial and temporal variations of NWP saturation; for this reason we adopted X-ray attenuation to precisely measure phase saturation throughout the flow domain and apply spatial moment analysis. Furthermore, the sweeping performance of two different permeability fields with comparable variance but distinct spatial correlation was compared against a homogeneous base case with equivalent mean permeability by means of spatial moment analysis.

58 GEOSCIENCES↗
DOE OSTI2018

Quantifying the relative contribution of factors to household vehicle miles of travel

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and healthy communities. Although there is considerable understanding of the various factors that influence household vehicular travel, there is little knowledge of their relative contribution to explaining variance in household VMT. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes, residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT generation. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 33 percent, density (as a key measure of built environment attributes) explaining 12 percent, and self-selection effects explaining 11 percent of the total variance in the logarithm of household VMT. The remaining 44 percent remains unexplained and attributable to omitted variables and unobserved idiosyncratic factors, calling for further research in this domain to better understand the relative contribution of various drivers of household VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1983

On the error in crop acreage estimation using satellite (LANDSAT) data

The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.

Chhikara, R.↗
NASA NTRS1986

Toward the application of the Kalman filter to regional open ocean modeling

A partial differential equation model is defined for ocean meteorological prediction and synoptic analysis. The Kalman filter used for data assimilation is described and applied to the one-dimensional linear barotropic quasi-geostrophic model with periodic and open boundary conditions. The model accounts for eddy scale dynamics in the ocean. The assumptions made in the forecast model are discussed, along with comparisons of the error variances expected with the filter and from an objective analysis method. The effectiveness of the Kalman filter is demonstrated and subsequent efforts to extend the filter to two dimensions are indicated.

Miller, R. N.↗
DOE OSTI2026

UV–Vis–NIR Reflectance Spectroscopy and Chemometrics for Monitoring Pu Directly on an Ion Exchange Column

Here, we present a fiber-optic UV–vis–NIR reflectance spectroscopy method for direct, noninvasive monitoring of Pu(IV) in a glass ion exchange column during dynamic loading and elution in a glovebox. A movable probe enables spatially resolved spectral acquisition along the column axis, capturing distinct features associated with Pu(IV) nitrate complexes during loading and free ions during elution. Principal component analysis was applied to extract the dominant spectral variance and resolve relative concentration profiles without requiring precise knowledge of optical penetration depth or species identity. This in situ approach reveals spatial gradients and speciation dynamics in real time, which provides actionable insight into Pu(IV) ion migration, resin saturation, and breakthrough behavior under evolving flow conditions. The method offers a practical, fiber-compatible strategy to monitor glass column–based separations for Pu and other lanthanides or actinides and to characterize metal–resin interactions in flow-through systems.

actinide↗
DOE OSTI2016

Angular dependence of primordial trispectra and CMB spectral distortions

Under the presence of anisotropic sources in the inflationary era, the trispectrum of the primordial curvature perturbation has a very specific angular dependence between each wavevector that is distinguishable from the one encountered when only scalar fields are present, characterized by an angular dependence described by Legendre polynomials. We examine the imprints left by curvature trispectra on the TT μ bispectrum, generated by the correlation between temperature anisotropies (T) and chemical potential spectral distortions (μ) of the Cosmic Microwave Background (CMB). Due to the angular dependence of the primordial signal, the corresponding TT μ bispectrum strongly differs in shape from TT μ sourced by the usual g {sub NL} or τ{sub NL} local trispectra, enabling us to obtain an unbiased estimation. From a Fisher matrix analysis, we find that, in a cosmic-variance-limited (CVL) survey of TT μ, a minimum detectable value of the quadrupolar Legendre coefficient is d {sub 2} ∼ 0.01, which is 4 orders of magnitude better than the best value attainable from the TTTT CMB trispectrum. In the case of an anisotropic inflationary model with a f (φ) F {sup 2} interaction (coupling the inflaton field φ with a vector kinetic term F {sup 2}), the size of the curvature trispectrum is related to that of quadrupolar power spectrum asymmetry, g {sub *}. In this case, a CVL measurement of TT μ makes it possible to measure g {sub *} down to 10{sup −3}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Performance and community structure dynamics of microbial electrolysis cells operated on multiple complex feedstocks

Microbial electrolysis is a promising technology for converting aqueous wastes into hydrogen. However, substrate adaptability is an important feature, seldom documented in microbial electrolysis cells (MECs). In addition, the correlation between substrate composition and community structure has not been well established. This study used an MEC capable of producing over 10 L/L-day of hydrogen from a switchgrass-derived bio-oil aqueous phase and investigated four additional substrates, tested in sequence on a mature biofilm. The additional substrates included a red oak-derived bio-oil aqueous phase, a corn stover fermentation product, a mixture of phenol and acetate, and acetate alone. The MECs fed with the corn stover fermentation product resulted in the highest performance among the complex feedstocks, producing an average current density of 7.3 ± 0.51 A/m 2 , although the acetate fed MECs outperformed complex substrates, producing 12.3 ± 0.01 A/m 2 . 16S rRNA gene sequencing showed that community structure and community diversity were not predictive of performance, and replicate community structures diverged despite identical inoculum and enrichment procedure. The trends in each replicate, however, were indicative of the influence of the substrates. Geobacter was the most dominant genus across most of the samples tested, but its abundance did not correlate strongly to current density. High-performance liquid chromatography (HPLC) showed that acetic acid accumulated during open circuit conditions when MECs were fed with complex feedstocks and was quickly degraded once closed circuit conditions were applied. The largest net acetic acid removal rate occurred when MECs were fed with red oak bio-oil aqueous phase, consuming 2.93 ± 0.00 g/L-day. Principal component analysis found that MEC performance metrics such as current density, hydrogen productivity, and chemical oxygen demand removal were closely correlated. Net acetic acid removal was also found to correlate with performance. However, no bacterial genus appeared to correlated to these performance metrics strongly, and the analysis suggested that less than 70% of the variance was accounted for by the two components. This study demonstrates the robustness of microbial communities to adapt to a range of feedstocks and conditions without relying on specific species, delivering high hydrogen productivities despite differences in community structure. The results indicate that functional adaptation may play a larger role in performance than community composition. Further investigation of the roles each microbe plays in these communities will help MECs to become integral in the 21st-century bioeconomy to produce zero-emission fuels.

09 BIOMASS FUELS↗
DOE OSTI2020

Utah FORGE: Phase 3 Microgravity Data

A 4D microgravity survey began in early 2019 in order to benchmark surface and subsurface elevations prior to Phase 3 drilling and stimulation campaigns. Microgravity stations are collocated with GPS deformation benchmarks and use the same location survey data. Surveys are undertaken on a quarterly basis. The focus of current activities is comparative analysis of GPS survey results and InSAR analysis (see GDR Submission 1251) to check seasonal variance and to evaluate possible changes in the groundwater elevation. The attached zip file contains a text file and an Excel spreadsheet containing Utah FORGE Phase 3 processed "final" microgravity data through time. The data are identical in both files. The spreadsheet is only supplied for convenience. There is also a ReadMe.txt file that describes the field headings.

15 GEOTHERMAL ENERGY↗
NASA NTRS1972

Evaluation of Skylab IB sensitivity to on-pad winds with turbulence

Computer simulation was performed to estimate displacements and bending moments experienced by the SKYLAB 1B vehicle on the launch pad due to atmospheric winds. The vehicle was assumed to be a beam-like structure represented by a finite number of generalized coordinates. Wind flow across the vehicle was treated as a nonhomogeneous, stationary random process. Response computations were performed by the assumption of simple strip theory and application of generalized harmonic analysis. Displacement and bending moment statistics were obtained for six vehicle propellant loading conditions and four representative reference wind profile and turbulence levels. Means, variances and probability distributions are presented graphically for each case. A separate analysis was performed to indicate the influence of wind gradient variations on vehicle response statistics.

Coffin, T.↗
NASA NTRS1977

Scintillation statistics measured in an earth-space-earth retroreflector link

Scintillation was measured in a vertical path from a ground-based laser transmitter to the Geos 3 satellite and back to a ground-based receiver telescope and, the experimental results were compared with analytical results presented in a companion paper (Bufton, 1977). The normalized variance, the probability density function and the power spectral density of scintillation were all measured. Moments of the satellite scintillation data in terms of normalized variance were lower than expected. The power spectrum analysis suggests that there were scintillation components at frequencies higher than the 250 Hz bandwidth available in the experiment.

Bufton, J. L.↗
NASA NTRS1980

Stratospheric pollutant transports by planetary waves and tropical circulations

Radiosonde and U-2 aircraft data from the Intertropical Convergence Zone experiment of July, 1977 were analyzed. The radiosonde data above 15 km was plotted in the form of time-height sections so that wave motions in the meteorological variables (temperature, zonal wind, and meridional wind) could be easily delineated. The results showed the presence of a planetary 16 day Kelvin wave. More significantly, large amplitude gravity waves with vertical wavelengths on the order of 3-6 km were found. Spectral analysis of frequencies showed peaks in meridional wind variance at 2-3 days and 5 days, with the shorter periods stronger at higher altitudes. In the time domain, two instances of organized wave groups propagating upward into the stratosphere were isolated. Associated with one of these wave groups was a region of very large vertical shear in which either turbulence or small scale (10 km wavelength or less) gravity wave activity had been found by the U-2 aircraft.

Riegel, C. A.↗
NASA NTRS1980

Ozone data and mission sampling analysis

A methodology was developed to analyze discrete data obtained from the global distribution of ozone. Statistical analysis techniques were applied to describe the distribution of data variance in terms of empirical orthogonal functions and components of spherical harmonic models. The effects of uneven data distribution and missing data were considered. Data fill based on the autocorrelation structure of the data is described. Computer coding of the analysis techniques is included.

Robbins, J. L.↗
NASA NTRS1985

A theorem of equivalence on the methods of least-squares estimation

A theorem on the methods of least-squares estimation is stated and proved. This theorem enables the replacement of a system of correlated measurements by an equivalent system of uncorrelated measurements without a whitening process, thus simplifying the analysis while resulting in the same minimum-variance estimate.

Wu, S.-C.↗
NASA NTRS1992

Landsat-TM identification of Amblyomma variegatum (Acari: Ixodidae) habitats in Guadeloupe

The feasibility of identifying specific habitats of the African bont tick, Amblyomma variegatum, from Landsat-TM images was investigated by comparing remotely sensed images of visible farms in Grande Terre (Guadeloupe) with field observations made in the same period of time (1986-1987). The different tick habitates could be separated using principal component analysis. The analysis clustered the sites by large and small variance of band values, and by vegetation and moisture indexes. It was found that herds in heterogeneous sites with large variances had more ticks than those in homogeneous or low variance sites. Within the heterogeneous sites, those with high vegetation and moisture indexes had more ticks than those with low values.

Hugh-Jones, M.↗
DOE OSTI2022

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic stochasticity in the process) and many different inputs can yield the same output (that is, the map is not injective). For example, imagine a sentiment analysis task where, due to linguistic ambiguity, a single statement can have a range of different sentiment interpretations while at the same time many distinct statements can represent the same sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it is frequently useful to be able to model the distribution on $f(x)$ for specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for specific output $y$. Such an analysis helps the user (i) better understand the variance intrinsic to the process they are studying and (ii) understand the range of specific input $x$ that can be used to achieve output $y$. Following existing work which used a fiber bundle framework to better model many-to-one processes we describe how morphisms of fiber bundles provide a template for building models which naturally capture the structure of many-to-many processes.

Coda, Elizabeth D.↗
DOE OSTI2026

The South Pole Telescope AGN Monitoring Campaign: First Release of SPTpol Bright AGN Light Curves

The South Pole Telescope (SPT) collaboration has recently embarked upon a campaign to monitor the brightness of a sample of active galactic nuclei (AGN), both in real time and in archival SPT data. The original design of the SPT was optimized for observations of the cosmic microwave background (CMB) at arc-minute and larger angular scales, and it has been used for this purpose for nearly twenty years, using three generations of CMB cameras. Recently it has been recognized that data from CMB experiments have the potential to be used for AGN monitoring. In this paper, we present the first public release of data from a full sample of SPT-monitored AGN, comprising 158 AGN light curves and associated data from the SPTpol camera, which was operational from 2012-2016. These light curves were created using observations from the SPTpol 500 deg$^{2}$ survey, in which the instrument was used to scan a 500 deg$^2$ patch of the sky several times per day with detectors sensitive to radiation in bands centered at 90 and 150 GHz. We provide a comprehensive description of the observations, the data processing methods, and the resulting light curve catalog. As an example of analyses that these data enable, we searched for a correlation between variability and spectral index, and we looked for ``bluer-when-brighter'' trends in the sample. Our analysis finds $> 10 σ$ correlation between fractional intrinsic variance and mean spectral index in the sample, but no significant evidence for bluer-when-brighter trends. The datasets from this study can be accessed through the SPT Treasury Record of AGN With Historical Activity and Time-Series or STRAWHAT catalog. This initial data release includes SPTpol light curves at 90 and 150 GHz, focusing on total intensity. In later updates, SPTpol polarization data and new observations from the SPT-3G instrument at 90, 150, and 220 GHz will be included.

Hood, J.C., II [Chicago U., KICP; Chicago U., Astr↗
DOE OSTI2015

A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties

This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.

54 ENVIRONMENTAL SCIENCES↗