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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final global uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Wavelength domain spatial frequency modulation imaging: enabling fiber optic delivery and detection

Spatial frequency modulation imaging (SPIFI) provides a simple architecture for modulating an extended illumination source that is compatible with single pixel imaging. We demonstrate wavelength domain SPIFI (WD-SPIFI) by encoding time-varying spatial frequencies in the spectral domain that can produce enhanced resolution images, like its spatial domain counterpart, spatial domain (SD) SPIFI. However, contrary to SD-SPIFI, WD-SPIFI enables remote delivery by single mode fiber, which can be attractive for applications where free-space imaging is not practical. Finally, we demonstrate a cascaded system incorporating WD-SPIFI in-line with SD-SPIFI enabling single pixel 2D imaging without any beam or sample scanning.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

High-harmonic spin-shearing interferometry for spatially resolved EUV magneto-optical spectroscopy

We present a method for achieving hyperspectral magnetic imaging in the extreme ultraviolet (EUV) region based on high-harmonic generation (HHG). By interfering two mutually coherent orthogonally-polarized and laterally-sheared HHG sources, we create an EUV illumination beam with spatially-dependent ellipticity. By placing a magnetic sample in the beamline and sweeping the relative time delay between the two sources, we record a spatially resolved interferogram that is sensitive to the EUV magnetic circular dichroism of the sample. This image contains the spatially-resolved magneto-optical response of the sample at each harmonic order, and can be used to measure the magnetic properties of spatially inhomogeneous magnetic samples.

Optics↗
DOE OSTI2014

Spatial Heterogeneity in Human Activities Favors the Persistence of Wolves in Agroecosystems

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Spatially Averaged Ice Contents of Ice-Wedge Polygon Cross-Sections to 3-m Depth, July 2013, Utqiagvik, Alaska

This dataset contains spatially averaged estimates of ice content (volume percent) for two-dimensional cross-sectional profiles (from trough center to trough center to a depth of 3 meters) of low- and flat-centered ice-wedge polygons (three of each type) located near Utqiagvik, Alaska. A combination of soil pits, trenches, and cores were used to describe, sample, and map the cross-section stratigraphy of soil horizons and ice wedges for each polygon at 6 depth intervals. Observed soil horizons were assigned to four types with increasing amounts of organic components (mineral, mineral/organic, organic/mineral, and organic). The average ice contents of each soil horizon type below the permafrost boundary and wedge ice were weighted by their cross-sectional area fractions to calculate spatially averaged estimates of ice content for each polygon. In the active layer, spatially averaged estimates of volumetric water contents were similarly determined and reported here as “ice” content to enable estimates of the soil’s structurally competent porosity and excess ice in permafrost layers. In this dataset, the file AK13_ice_contents.csv includes cross-sectional area fractions and spatially averaged ice contents for soil layers and horizon types at the six depth intervals. The file AK13_permafrost_ice_fractions.csv contains the calculated partitioning of ice contents into pore ice and excess ice fractions for the three permafrost-dominated depth intervals. In addition, there is a data dictionary file for each of these data files and a file-level metadata file. These data were generated by the Department of Energy’s Soil Carbon Response to Environmental Change Scientific Focus Area and were used as inputs to model simulations examining the consequences of thaw-affected subsidence and microtopography change on active layer thickness of low-relief polygonal tundra landscapes in a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Spatializing Global Urban Extent: A Source Driven Approach

“Urban” is something that intuitively feels very well defined; however, when it comes time to express this idea on a map, things get complicated. Definitions of “urban” vary globally, and as such there is not universal understanding of what makes a given place “urban”. The common approach to spatially defining urban extents is through remotely sensed imagery. The alternative approach presented in this paper uses the percent of population in urban areas, which is a common macroeconomic (country-level) variable with the definition for urban generally defined by each country’s statistical office, along with temporally-aligned highresolution population data to spatially define urban extents for each country. Because the percent urban number is defined by the same producer as other urban/rural defined statistical data, such as household characteristics or birth rate, understanding the spatial aspect of urban from the same perspective is ideal for high resolution spatial modeling of these other phenomena.

Moehl, Jessica↗
DOE OSTI2014

Investigation of Spatial Variation of Sea States Offshore of Humboldt Bay CA Using a Hindcast Model.

Spatial variability of sea states is an important consideration when performing wave resource assessments and wave resource characterization studies for wave energy converter (WEC) test sites and commercial WEC deployments. This report examines the spatial variation of sea states offshore of Humboldt Bay, CA, using the wave model SWAN . The effect of depth and shoaling on bulk wave parameters is well resolved using the model SWAN with a 200 m grid. At this site, the degree of spatial variation of these bulk wave parameters, with shoaling generally perpendicular to the depth contours, is found to depend on the season. The variation in wave height , for example, was higher in the summer due to the wind and wave sheltering from the protruding land on the coastline north of the model domain. Ho wever, the spatial variation within an area of a potential Tier 1 WEC test site at 45 m depth and 1 square nautical mile is almost negligible; at most about 0.1 m in both winter and summer. The six wave characterization parameters recommended by the IEC 6 2600 - 101 TS were compared at several points along a line perpendicular to shore from the WEC test site . As expected, these parameters varied based on depth , but showed very similar seasonal trends.

Dallman, Ann Renee↗
DOE OSTI2021

Understanding the Design Space of Sparse/Dense Multiphase Dataflows for Mapping Graph Neural Networks on Spatial Accelerators

Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applications in cloud and HPC. Owing to their unique compute and memory characteristics that come from an interplay between dense and sparse phases of computations, the emergence of reconfigurable dataflow (aka spatial) accelerators offers promise for acceleration by mapping optimized dataflows (i.e., computation order and parallelism) for both phases. The goal of this work is to characterize and understand the design-space of dataflow choices for running GNNs on spatial accelerators in order for the compilers to optimize the dataflow based on the workload. Specifically, we propose a taxonomy to describe all possible choices for mapping the dense and sparse phases of GNNs spatially and temporally over a spatial accelerator, capturing both the intra-phase dataflow and the inter-phase (pipelined) dataflow. Using this taxonomy, we do deep-dives into the cost and benefits of several dataflows and perform case studies on implications of hardware parameters for dataflows and value of flexibility to support pipelined execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Light-Dependent Changes in the Spatial Localization of Metabolites in Solenostemon scutellarioides (Coleus Henna) Visualized by Matrix-Free Atmospheric Pressure Electrospray Laser Desorption Ionization Mass Spectrometry Imaging

The visualization of foliage color in plants provides immediate insight into some of the compounds that exist in the leaf. However, many non-colored compounds are also present; their cellular distributions are not readily identifiable optically. In this study we evaluate the applicability of mass spectrometry imaging (MSI) via electrospray laser desorption ionization (ELDI) to reveal the spatial distribution of metabolites. ELDI-MSI is a matrix free, atmospheric pressure ionization method that utilizes a UV laser coupled with supplemental ionization by electrospray. We specifically applied ELDI-MSI to determine the spatial distribution of metabolites in Coleus Henna half leaves that were grown with half-sections either fully illuminated or shaded. We monitored dynamic changes in the spatial distribution of metabolites in response to the change of illumination every 7 days for a 28 day period. A novel source-sink relationship was observed between the 2 halves of the experimental leaf. Furthermore, Coleus Henna leaves present visually recognizable sectors associated with the differential accumulation of flavonoids. Thus, we correlated the effect of differential illumination and presence or absence of flavonoids with metabolic changes revealed by the accumulation of carbohydrates, amino acids, and organic acids. Here, the results show the potential of ELDI-MSI to provide spatial information for a variety of plant metabolites with little sample preparation.

Coleus (Solenostemon scuttellarioides)↗
DOE OSTI2015

Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures

Although water temperature is important to stream biota, it is difficult to collect in a spatially and temporally continuous fashion. We used remotely-sensed Land Surface Temperature (LST) data to estimate mean daily stream temperature for every confluence-to-confluence reach in the John Day River, OR, USA for a ten year period. Models were built at three spatial scales: site-specific, subwatershed, and basin-wide. Model quality was assessed using jackknife and cross-validation. Model metrics for linear regressions of the predicted vs. observed data across all sites and years: site-specific r2 = 0.95, Root Mean Squared Error (RMSE) = 1.25 °C; subwatershed r2 = 0.88, RMSE = 2.02 °C; and basin-wide r2 = 0.87, RMSE = 2.12 °C. Similar analyses were conducted using 2012 eight-day composite LST and eight-day mean stream temperature in five watersheds in the interior Columbia River basin. Mean model metrics across all basins: r2 = 0.91, RMSE = 1.29 °C. Sensitivity analyses indicated accurate basin-wide models can be parameterized using data from as few as four temperature logger sites. This approach generates robust estimates of stream temperature through time for broad spatial regions for which there is only spatially and temporally patchy observational data, and may be useful for managers and researchers interested in stream biota.

McNyset, Kristina↗
DOE OSTI2016

Spatially offset active galactic nuclei. I. Selection and spectroscopic properties

We present a sample of 18 optically selected and X-ray-detected spatially offset active galactic nuclei (AGNs) from the Sloan Digital Sky Survey (SDSS). In nine systems, the X-ray active galactic nucleus (AGN) is spatially offset from the galactic stellar core that is located within the 3″ diameter SDSS spectroscopic fiber. In 11 systems, the X-ray AGN is spatially offset from a stellar core that is located outside the fiber, with an overlap of two. To build the sample, we cross-matched Type II AGNs selected from the SDSS galaxy catalog with archival Chandra imaging and employed our custom astrometric and registration procedure. The projected angular (physical) offsets span a range of 0.″6 (0.8 kpc) to 17.″4 (19.4 kpc), with a median value of 2.″7 (4.6 kpc). The offset nature of an AGN is an unambiguous signature of a galaxy merger, and these systems can be used to study the properties of AGNs in galaxy mergers without the biases introduced by morphological merger selection techniques. In this paper (Paper I), we use our sample to assess the kinematics of AGN photoionized gas in galaxy mergers. We find that spectroscopic offset AGN selection may be up to 89{sub −16}{sup +7}% incomplete due to small projected velocity offsets. We also find that the magnitude of the velocity offsets are generally larger than expected if our spatial selection introduces a bias toward face-on orbits, suggesting the presence of complex kinematics in the emission line gas of AGNs in galaxy mergers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

THE EFFECTS OF SPATIAL SMOOTHING ON SOLAR MAGNETIC HELICITY PARAMETERS AND THE HEMISPHERIC HELICITY SIGN RULE

The hemispheric preference for negative/positive helicity to occur in the northern/southern solar hemisphere provides clues to the causes of twisted, flaring magnetic fields. Previous studies on the hemisphere rule may have been affected by seeing from atmospheric turbulence. Using Hinode /SOT-SP data spanning 2006–2013, we studied the effects of two spatial smoothing tests that imitate atmospheric seeing: noise reduction by ignoring pixel values weaker than the estimated noise threshold, and Gaussian spatial smoothing. We studied in detail the effects of atmospheric seeing on the helicity distributions across various field strengths for active regions (ARs) NOAA 11158 and NOAA 11243, in addition to studying the average helicities of 179 ARs with and without smoothing. We found that, rather than changing trends in the helicity distributions, spatial smoothing modified existing trends by reducing random noise and by regressing outliers toward the mean, or removing them altogether. Furthermore, the average helicity parameter values of the 179 ARs did not conform to the hemisphere rule: independent of smoothing, the weak-vertical-field values tended to be negative in both hemispheres, and the strong-vertical-field values tended to be positive, especially in the south. We conclude that spatial smoothing does not significantly affect the overall statistics for space-based data, and thus seeing from atmospheric turbulence seems not to have significantly affected previous studies’ ground-based results on the hemisphere rule.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spatial and Kinematic Clustering of Stars in the Galactic Disk

The Galactic disk is expected to be spatially and kinematically clustered on many scales due to both star formation and the Galactic potential. In this work we calculate the spatial and kinematic two-point correlation functions (TPCF) using a sample of 1.7 × 10 6 stars with radial velocities from Gaia DR2. Clustering is detected on spatial scales of 1–300 pc and a velocity scale of 15 km s –1 . After removing bound structures, the data have a power-law index of γ ≈ –1 for 1 pc < Δr < 100 pc and γ ≲ –1.5 for Δr > 100 pc. We interpret these results with the aid of a star-by-star simulation of the Galaxy, in which stars are born in clusters orbiting in a realistic potential that includes spiral arms, a bar, and giant molecular clouds. We find that the simulation largely agrees with the observations at most spatial and kinematic scales. In detail, the TPCF in the simulation is shallower than the data at ≲20 pc scales, and steeper than the data at ≳30 pc. We also find a persistent clustering signal in the kinematic TPCF for the data at large Δv (>5 km s –1 ) that is not present in the simulations. We speculate that this mismatch between observations and simulations may be due to two processes: hierarchical star formation and transient spiral arms. Furthermore, we also predict that the addition of ages and metallicities measured with a precision of 50% and 0.05 dex, respectively, will enhance the clustering signal beyond current measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Dissecting Nearby Galaxies with piXedfit. I. Spatially Resolved Properties of Stars, Dust, and Gas as Revealed by Panchromatic SED Fitting

We study spatially resolved properties (on spatial scales of ~1–2 kpc out to at least 3 effective radii) of the stars, dust, and gas in 10 nearby spiral galaxies. The properties of the stellar population and dust are derived by fitting the spatially resolved spectral energy distribution (SED) with more than 20 photometric bands ranging from far-ultraviolet to far-infrared. Our newly developed software piXedfit performs point-spread function matching of images, pixel binning, and models the stellar light, dust attenuation, dust emission, and emission from a dusty torus heated by an active galactic nucleus simultaneously through the energy-balance approach. With this self-consistent analysis, we present the spatially resolved version of the IRX–βrelation, finding that it is consistent with the relationship from the integrated photometry. We show that the old stellar populations contribute to the dust heating, which causes an overestimation of the star formation rate (SFR) derived from the total ultraviolet and infrared luminosities on kiloparsec scales. With archival high-resolution maps of atomic and molecular gas, we study the radial variation of the properties of the stellar populations (including stellar mass, age, metallicity, and SFR), dust (including dust mass, dust temperature, and abundance of polycyclic aromatic hydrocarbon), and gas, as well as dust-to-stellar mass and dust-to-gas mass ratios. We observe a depletion of the molecular gas mass fraction in the central region of the majority of the galaxies, suggesting that the lack of available fuel is an important factor in suppressing the specific SFR at the center.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Exploring new topography-based subgrid spatial structures for improving land surface modeling

Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation, slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Altogether the local method and non-geo-located subgrid structures effectively and robustly capture topographic, climatic and vegetation variability, which is important for land surface modeling.

58 GEOSCIENCES↗
DOE OSTI2022

Spatial heterogeneity effects on land surface modeling of water and energy partitioning

Abstract. Understanding the influence of land surface heterogeneity on surface water and energy fluxes is crucial for modeling earth system variability and change. This study investigates the effects of four dominant heterogeneity sources on land surface modeling, including atmospheric forcing (ATM), soil properties (SOIL), land use and land cover (LULC), and topography (TOPO). Our analysis focused on their impacts on the partitioning of precipitation (P) into evapotranspiration (ET) and runoff (R), partitioning of net radiation into sensible heat and latent heat, and corresponding water and energy fluxes. An initial set of 16 experiments were performed over the continental US (CONUS) using the E3SM land model (ELMv1) with different combinations of heterogeneous and homogeneous datasets. The Sobol' total and first-order sensitivity indices were utilized to quantify the relative importance of the four heterogeneity sources. Sobol' total sensitivity index measures the total heterogeneity effects induced by a given heterogeneity source, consisting of the contribution from its own heterogeneity (i.e., the first-order index) and its interactions with other heterogeneity sources. ATM and LULC are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning, mainly contributed by their own heterogeneity and slightly contributed by their interactions with other heterogeneity sources. Their heterogeneity effects are complementary, both spatially and temporally. The overall impacts of SOIL and TOPO are negligible, except TOPO dominates the spatial variability of R/P across the transitional climate zone between the arid western and humid eastern CONUS. Accounting for more heterogeneity sources improves the simulated spatial variability of water and energy fluxes when compared with ERA5-Land reanalysis dataset. An additional set of 13 experiments identified the most critical components within each heterogeneity source, which are precipitation, temperature, and longwave radiation for ATM, soil texture, and soil color for SOIL and maximum fractional saturated area parameter for TOPO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Technical note: Modeling spatial fields of extreme precipitation – a hierarchical Bayesian approach

Abstract. We introduce a hierarchical Bayesian model for the spatial distribution of rainfall corresponding to an extreme event of a specified duration that could be used with regional hydrologic models to perform a regional hydrologic risk analysis. An extreme event is defined if any gaging site in the watershed experiences an annual maximum rainfall event and the spatial field of rainfall at all sites corresponding to that occurrence is modeled. Applications to data from New York City demonstrate the effectiveness of the model for providing spatial scenarios that could be used for simulating loadings into the urban drainage system. Insights as to the homogeneity in spatial rainfall and its implications for modeling are provided by considering partial pooling in the hierarchical Bayesian framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Characterizing permafrost soil active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models. In this study, we developed a spatially integrated modelling and analysis framework combining field observations, local scale (~ 50 m) active layer thickness (ALT) and soil moisture maps derived from airborne low frequency (L + P-band) radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Model simulated ALT results show good correspondence with in-situ measurements in higher permafrost probability (PP ≥ 70 %) areas (n = 33, R = 0.60, mean bias = 1.58 cm, RMSE = 20.32 cm). The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr -1 ) and much larger increases (> 3 cm yr -1 ) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). Uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was found to be the most important factor affecting model ALT accuracy. Here, potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of permafrost active layer conditions.

54 ENVIRONMENTAL SCIENCES↗