Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spatial Characterization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,621 records · Page 90

WFIRST CGI Integral Field Spectrograph Performance and Post-Processing in the OS6 Observing Scenario

The WFIRST coronagraph instrument (CGI) will have an integral field spectrograph (IFS) backend to disperse the entire field of view at once and obtain spatially-resolved, low-resolution spectra of the speckles and science scene. The IFS will be key to understanding the spectral nature of the speckles, obtain science spectra of planets and disks, and will be used for broadband wavefront control. In order to characterize, predict, and optimize the performance of the instrument, we present a detailed model of the IFS in the context of the new OS6 observing scenario. The simulation includes spatial, spectral, and temporal variations of the speckle field on the IFS detector plane, which allows us to explore several post-processing methods and assess what gains can be expected. The simulator includes the latest models of the detector behavior when operating in photon-counting mode.

WFIRST coronagraph instrument (CGI)↗

Secondary ion mass spectrometry: The application in the analysis of atmospheric particulate matter

Currently, considerable attention has been paid to atmospheric particulate matter (PM) investigation due to its importance in human health and global climate change. Surface characterization of PM is important since the chemical heterogeneity between the surface and bulk may vary its impact on the environment and human being. Secondary ion mass spectrometry (SIMS) is a surface technique with high surface sensitivity, capable of high spatial chemical imaging and depth profiling. Recent research shows that SIMS holds great potential in analyzing both surface and bulk chemical information of PM. In this review, we presented the working principal of SIMS in PM characterization, summarized recent applications in PM analysis from different sources, discussed its advantages and limitations, and proposed the future development of this technique with a perspective in environmental sciences.

aerosol↗

Evaluating Coastal Landscape Response to Sea-Level Rise in the Northeastern United States - Approach and Methods

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

terrain↗

Spatial hole burning and spectral stability of a quantum-dot laser

The inhomogeneous intensity distribution of the optical model along the axis of a semiconductor quantum-dot laser results in spatial hole burning. The influence of this phenomenon on the stability of the multifrequency emission spectrum is studied when the optical transition of the quantum dots is characterized by considerable homogeneous broadening. The results of two models—in which inhomogeneous broadening is disregarded and taken into account—regarding the stability of the radiation spectrum under the influence of slight variation of the spectral loss dependence in the resonator are compared. Inhomogeneous distribution of the charge carriers (spatial hole burning) is found to be a critical factor in determining the form and stability of the spectrum.

36 MATERIALS SCIENCE↗

Integrative molecular and microanalytical studies of syntrophic partnerships linking C, S, and N cycles in anoxic environments

Syntrophy and other forms of symbiotic associations between microorganisms are central to carbon and nutrient cycling in the environment. However, the inherent interdependence of these interactions, dynamic behavior, and frequent existence at thermodynamic limits has hindered our ability to both recognize syntrophic partnerships in nature and effectively study their behavior in the laboratory. To characterize and understand the underlying factors influencing syntrophic associations within complex communities requires a suite of tools that extend beyond basic molecular identification and cultivation. This specifically includes methods that preserve the natural spatial relationships between metabolically interdependent microorganisms while allowing downstream geochemical and/or molecular analysis. With support from this award, we have developed and applied new combinations of molecular, microscopy, and stable isotope-based methodologies that enable the characterization of fundamental links between phylogenetically-identified microorganisms and their specific metabolic activities and interactions in the environment. Through the coupling of fluorescence in situ hybridization (FISH) with cell capture and targeted metagenomics (Magneto-FISH), and FISH + secondary ion mass spectrometry (i.e. FISH-SIMS or FISH-nanoSIMS), we have defined new microbial interactions and the ecophysiology of anaerobic microorganisms involved in environmental methane cycling.

03 NATURAL GAS↗

Population dynamics, information transfer, and spatial organization in a chemical reaction network under spatial confinement and crowding conditions

Here, we investigate, via Brownian dynamics simulations, the reaction dynamics of a generic, nonlinear chemical network under spatial confinement and crowding conditions. In detail, the Willamowski-Rossler chemical reaction system has been “extended” and considered as a prototype reaction-diffusion system. These results are potentially relevant to a number of open problems in biophysics and biochemistry, such as the synthesis of primitive cellular units (protocells) and the definition of their role in the chemical origin of life and the characterization of vesicle-mediated drug delivery processes. More generally, the computational approach presented in this work makes the case for the use of spatial stochastic simulation methods for the study of biochemical networks in vivo where the “well-mixed” approximation is invalid and both thermal and intrinsic fluctuations linked to the possible presence of molecular species in low number copies cannot be averaged out.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiple dataset water-quality analyses in the vicinity of an ocean wastewater plume

The White's Point ocean outfall is the method of disposal for approximately 374 million gallons of treated wastewater per day from Los Angeles County. The photosynthetic characteristics and particle distributions have well-defined properties that can be exploited to yield information on transport of the plume, mixing dynamics, and resuspension of bottom sediments during periods of bottom current velocity in excess of ca. 0.1 m/s. This plume of particles serves as a conservative tracer, which was studied using a number of sampling platforms and strategies, including underway sawtooth, or 'tow-yo' sampling, moored arrays of instruments, stationary profiling, and now for the first time with remotely-sensed multispectral color imagery. Research in this area previously focused on examination of the plume as it relates to the local current field and transport of particles, and on the resuspension of bottom sediments during periods of increased currents. In addition, Wu et al elucidated techniques for separating the particle signal into photosynthetic and nonphotosynthetic components, based on the beam attenuation to chlorophyll fluorescence ratio. High-frequency time series measurements of the current field and bio-optical characteristics at a site close to the waste diffusers were also collected. These are being analyzed for the spectral characteristics of the longer-timescale variability, in order to predict particle transport through simple meteorological measurements. With the advent of high spectral and spatial resolution imaging spectrometers such as AVIRIS, it is now possible to construct causal relationships between particle distributions and signature of the upwelled radiance from the surface. The availability of a constant and well-characterized source of material lends itself well to models which predict upwelled radiance from the surface. The availability of a constant and well-characterized source of material lends itself well to models which predict upwelled light as a function of particle distributions, photosynthetic pigments, colored dissolved organic material, and detrital and degradation products of photosynthesis. In addition, the spatial coverage provided by the tow-yo sampling device, combined with the profile measurements of the light field, should facilitate the best inverse modeling attempts possible thus far.

Hamilton, Michael↗

Dynamic granularity of imaging systems

Imaging systems that include a specific source, imaging concept, geometry, and detector have unique properties such as signal-to-noise ratio, dynamic range, spatial resolution, distortions, and contrast. Some of these properties are inherently connected, particularly dynamic range and spatial resolution. It must be emphasized that spatial resolution is not a single number but must be seen in the context of dynamic range and consequently is better described by a function or distribution. We introduce the “dynamic granularity” G dyn as a standardized, objective relation between a detector’s spatial resolution (granularity) and dynamic range for complex imaging systems in a given environment rather than the widely found characterization of detectors such as cameras or films by themselves. We found that this relation can partly be explained through consideration of the signal’s photon statistics, background noise, and detector sensitivity, but a comprehensive description including some unpredictable data such as dust, damages, or an unknown spectral distribution will ultimately have to be based on measurements. Measured dynamic granularities can be objectively used to assess the limits of an imaging system’s performance including all contributing noise sources and to qualify the influence of alternative components within an imaging system. Our article explains the construction criteria to formulate a dynamic granularity and compares measured dynamic granularities for different detectors used in the X-ray backlighting scheme employed at Sandia’s Z-Backlighter facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Colorectal Cancer Metastases in the Liver Establish Immunosuppressive Spatial Networking between Tumor-Associated SPP1 + Macrophages and Fibroblasts

Abstract Purpose: The liver is the most frequent metastatic site for colorectal cancer. Its microenvironment is modified to provide a niche that is conducive for colorectal cancer cell growth. This study focused on characterizing the cellular changes in the metastatic colorectal cancer (mCRC) liver tumor microenvironment (TME). Experimental Design: We analyzed a series of microsatellite stable (MSS) mCRCs to the liver, paired normal liver tissue, and peripheral blood mononuclear cells using single-cell RNA sequencing (scRNA-seq). We validated our findings using multiplexed spatial imaging and bulk gene expression with cell deconvolution. Results: We identified TME-specific SPP1-expressing macrophages with altered metabolism features, foam cell characteristics, and increased activity in extracellular matrix (ECM) organization. SPP1+ macrophages and fibroblasts expressed complementary ligand–receptor pairs with the potential to mutually influence their gene-expression programs. TME lacked dysfunctional CD8 T cells and contained regulatory T cells, indicative of immunosuppression. Spatial imaging validated these cell states in the TME. Moreover, TME macrophages and fibroblasts had close spatial proximity, which is a requirement for intercellular communication and networking. In an independent cohort of mCRCs in the liver, we confirmed the presence of SPP1+ macrophages and fibroblasts using gene-expression data. An increased proportion of TME fibroblasts was associated with the worst prognosis in these patients. Conclusions: We demonstrated that mCRC in the liver is characterized by transcriptional alterations of macrophages in the TME. Intercellular networking between macrophages and fibroblasts supports colorectal cancer growth in the immunosuppressed metastatic niche in the liver. These features can be used to target immune-checkpoint–resistant MSS tumors.

60 APPLIED LIFE SCIENCES↗

Western Rainier Seismic Zone Airborne Laser Swath Mapping

Airborne laser swath mapping (ALSM) of the Puget Lowland conducted by TerraPoint LLC for the Purget Sound Lidar Concortium (PSLC), has been successful in revealing Holocene fault scarps and lendsliders hidden beneath the dense, temperate rain forest cover and in quantifying shoreline terrace uplift. Expanding the PSLC efforts, NASA-USGS collaboration is now focusing on topographic mapping of seismogenic zones adjacent to volcanois in the western Cascades range in order to assess the presence of active faulting and tectonic deformation, better define the extend of lahars and understand their flow processes, and characterize landslide occurrence. Mapping of the western Rainier zone (WRZ) was conducted by TerraPoint in late 2002, after leaf fall and before snow accumulation. The WRZ is a NNW-trending, approx. 30 km-long zone of seismicity west of Mount Rainier National Park. The Puget Lowland ALSM methods were modified to accommodate challenges posed by the steep, high relief terrian. The laser data, acquired with a density of approx. 2 pulses /sq m, was filtered to identify returns from the ground from which a bare Earth digital elevation model (DEM) was produced with a grid size of 1.8 m. The RMS elevation accuracy of the DEM in flat, unvegetated areas is approx. 10cm based on consistency between overlapping flight swaths and comparisons to ground control points. The resulting DEM substantially improves upon Shuttle Radar Topography Mission and USGS photogrammetric mapping. For example, the DEM defines the size and spatial distribution of flood erratics left by the Electron lahar and of megaclasts within the Round Pass lahar, important for characterizing the lahar hydraulics. A previously unknown lateral levee on the Round Pass lahar is also revealed. In addition, to illustrating geomorfic feature within the WRZ, future plans for laser mapping of the Saint Helens and Darrington seismic zones will be described.

Harding, David J.↗

Goniometric and Polarized Imaging Spectroscopic Lab Measurements of Spacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using directional reflectance spectroscopy and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation (MLI) commonly used on spacecraft for initial measurements. The directional spectral data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a lab and field goniometer incorporating two AnalyticalSpectral Device (ASD) spectrometers, a small Lab sphere integrating sphere also paired with an ASD spectrometer, and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer measures spectral bi-directional reflectance factor (BRF) data over a broad range from 350−2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. With the same spectral capabilities, the integrating sphere measures hemispherical-directional reflectance (HDR) in a 45◦-nadir configuration. The Headwall imager covers a spectral range from 400−1000 nm with 1.6 nm spectral resolution.Our initial BRF measurements show interference effects for both materials typically observed with thin films and high infrared reflectivity. In contrast, the interference effects are not present in the HDR measurements of the MLI likely due to the interference effects being averaged out over the reflecting hemisphere. Spatially resolved polarization ratio maps show variability across the materials due to the varying surface structure. We outline a plan for expanding our analysis to a broader range of materials to characterize their directional reflectance spectroscopy.

Chris H. Lee↗

Experimental realization of neutron helical waves

Methods of preparation and analysis of structured waves of light, electrons, and atoms have been advancing rapidly. Despite the proven power of neutrons for material characterization and studies of fundamental physics, neutron science has not been able to fully integrate these techniques because of small transverse coherence lengths, the relatively poor resolution of spatial detectors, and low fluence rates. Here, we demonstrate methods that are practical with the existing technologies and show the experimental achievement of neutron helical wavefronts that carry well-defined orbital angular momentum values. We discuss possible applications and extensions to spin-orbit correlations and material characterization techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Eastern Pacific ITCZ during the Boreal Spring

The 6-year (1998-2003) rainfall products from the Tropical Rainfall Measuring Mission (TRMM) are used to quantify the Intertropical Convergence Zone (ITCZ) in the eastern Pacific (defined by longitudinal averages over 90 degrees W-130 degrees W) during boreal spring (March-April). The double ITCZ phenomenon, represented by the occurrence of two maxima with respect to latitude in monthly mean rainfall, is observed in most but not all of the years studied. The relative spatial locations of maxima in sea surface temperature (SST), rainfall, and surface pressure are examined. Interannual and weekly variability are characterized in SST, rainfall, surface convergence, total column water vapor, and cloud water. There appears to be a competition for rainfall between the two hemispheres during this season. When one of the two rainfall maxima is particularly strong, the other tends to be weak, with the total rainfall integrated over the two varying less than does the difference between the rainfall integrated over each separately. There is some evidence for a similar competition between the SST maxima in the two hemispheres, but this is more ambiguous, and there is evidence that some variations in the relative strengths of the two rainfall maxima may be independent of SST. Using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP), four distinct ITCZ types during March-April are defined, based on the relative strengths of rainfall peaks north and south of, and right over the equator. Composite meridional profiles and spatial distributions of rainfall and SST are documented for each type. Consistent with previous studies, an equatorial cold tongue is essential to the existence of the double ITCZs. However, too strong a cold tongue may dampen either the southern or northern rainfall maximum, depending on the magnitude of SST north of the equator.

Gu, Guojun↗

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Dungan, Jennifer L.↗

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Quattrochi, Dale A.↗

Spatial Characteristics of F/A-18 Vertical Tail Buffet Pressures Measured in Flight

Buffeting is an aeroelastic phenomenon which plagues high performance aircraft, especially those with twin vertical tails, at high angles of attack. Previous wind-tunnel and flight tests were conducted to characterize the buffet loads on the vertical tails by measuring surface pressures, bending moments, and accelerations. Following these tests, buffeting estimates were computed using the measured buffet pressures and compared to the measured responses. The estimates did not match the measured data because the assumed spatial correlation of the buffet pressures was not correct. A better understanding of the partial (spatial) correlation of the differential buffet pressures on the tail was necessary to improve the buffeting estimates. Several wind-tunnel investigations were conducted for this purpose. When combined and compared, the results of these tests show that the partial correlation depends on and scales with flight conditions. One of the remaining questions is whether the windtunnel data is consistent with flight data. Presented herein, cross-spectra and coherence functions calculated from pressures that were measured on the high alpha research vehicle (HARV) indicate that the partial correlation of the buffet pressures in flight agrees with the partial correlation observed in the wind tunnel.

Moses, Robert W.↗

Active Mixing of Reactive Materials for 3D Printing

The mixing of materials during additive manufacturing is a major benefit which allows one to compositionally and spatially tailor material properties, for example to locally control the reactivity in fuel–oxidizer systems known as thermites. This work characterizes an active mixing printhead used in conjunction with a 3D printing process known as Direct Ink Writing. Besides compositional control, a major benefit of this approach is that it offers a safe method for working with these materials, which can otherwise be hazardous once mixed. Custom fuel and oxidizer inks are fed at fixed volumetric rates into an active mixing printhead, and both the rotational speed of the mixing impeller as well as the fuel–oxidizer ratio are varied. Upon ignition, the propagation speed increases with the rotational speed of the mixer and plateaus above a critical value of ≈750 rpm. The critical mixing speed is corroborated by computational fluid simulations and an analytical expression that considers the inks’ complex fluid behavior. Additionally, varying the composition results in a wide range of propagation speeds with peak reactivity corresponding to a fuel–rich formulation ( Φ = 1.5). As a result, a test article incorporating a fast– and slow–burning region demonstrates how spatial composition can manipulate the reactivity.

3D printing↗

Predicting Local Material Thickness from Steady-State Ultrasonic Wavefield Measurements Using a Convolutional Neural Network

Acoustic steady-state excitation spatial spectroscopy (ASSESS) is a full-field, ultrasonic non-destructive evaluation (NDE) technique used to locate and characterize defects in plate-like structures. ASSESS generates a steady-state, single-tone ultrasonic excitation in a structure and a scanning laser Doppler Vibrometer (LDV) measures the resulting full-field surface velocity response. Traditional processing techniques for ASSESS data rely on wavenumber domain analysis. This paper presents the alternative use of a convolutional neural network (CNN), trained using simulated ASSESS data, to predict the local plate thickness at every pixel in the wavefield measurement directly. The defect detection accuracy of CNN-based thickness predictions are shown to improve for defects of greater size, and for defects with higher thickness reductions. The CNN demonstrates the ability to predict thickness accurately in regions where Lamb wave dispersion relations are complex or unknown, such as near the boundaries of a test specimen, so long as the CNN is trained on data that accounts for these regions. The CNN also shows generalizability to ASSESS experimental data, despite an entirely simulated training dataset.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗