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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves

A thorough understanding of the neuroanatomy of peripheral nerves is required for a better insight into their function and the development of neuromodulation tools and strategies. In biophysical modeling, it is commonly assumed that the complex spatial arrangement of myelinated and unmyelinated axons in peripheral nerves is random, however, in reality the axonal organization is inhomogeneous and anisotropic. Present quantitative neuroanatomy methods analyze peripheral nerves in terms of the number of axons and the morphometric characteristics of the axons, such as area and diameter. In this study, we employed spatial statistics and point process models to describe the spatial arrangement of axons and Sinkhorn distances to compute the similarities between these arrangements (in terms of first- and second-order statistics) in various vagus and pelvic nerve cross-sections. We utilized high-resolution transmission electron microscopy (TEM) images that have been segmented using a custom-built high-throughput deep learning system based on a highly modified U-Net architecture. Our findings show a novel and innovative approach to quantifying similarities between spatial point patterns using metrics derived from the solution to the optimal transport problem. We also present a generalizable pipeline for quantitative analysis of peripheral nerve architecture. Our data demonstrate differences between male- and female-originating samples and similarities between the pelvic and abdominal vagus nerves.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Research in solar physics: Some techniques for analyzing data from the ultraviolet spectrometer and polarimeter

Useful information for certain aspects of the analysis of data obtained by the Ultraviolet Spectrometer and Polarimeter (UVSP) on the Solar Maximum Mission (SMM) are contained. The meaning of the UVSPCO-ordinate system and the SMM roll, pitch, and yaw are described and the process for overlaying UVSP images is explained. The various computer programs that calculate the line of sight component of the SMM spacecraft velocity from the spacecraft to the Sun is described. The spacecraft velocity is used to correct or interpret the signal observed in USVP dopplergrams. A method of using the spacecraft velocity to calibrate UVSP dopplergrams and magnetograms, i.e., determine the width of the observed emission line is applied. The UVSP polarization analysis procedures are described and the expressions for the statistical uncertainties in various quantities obtained from UVSP measurements are given.

Henze, W., Jr.↗
NASA NTRS2011

Space Transportation System Liftoff Debris Mitigation Process Overview

Liftoff debris is a top risk to the Space Shuttle Vehicle. To manage the Liftoff debris risk, the Space Shuttle Program created a team with in the Propulsion Systems Engineering & Integration Office. The Shutt le Liftoff Debris Team harnesses the Systems Engineering process to i dentify, assess, mitigate, and communicate the Liftoff debris risk. T he Liftoff Debris Team leverages off the technical knowledge and expe rtise of engineering groups across multiple NASA centers to integrate total system solutions. These solutions connect the hardware and ana lyses to identify and characterize debris sources and zones contribut ing to the Liftoff debris risk. The solutions incorporate analyses sp anning: the definition and modeling of natural and induced environmen ts; material characterizations; statistical trending analyses, imager y based trajectory analyses; debris transport analyses, and risk asse ssments. The verification and validation of these analyses are bound by conservative assumptions and anchored by testing and flight data. The Liftoff debris risk mitigation is managed through vigilant collab orative work between the Liftoff Debris Team and Launch Pad Operation s personnel and through the management of requirements, interfaces, r isk documentation, configurations, and technical data. Furthermore, o n day of launch, decision analysis is used to apply the wealth of ana lyses to case specific identified risks. This presentation describes how the Liftoff Debris Team applies Systems Engineering in their proce sses to mitigate risk and improve the safety of the Space Shuttle Veh icle.

Mitchell, Michael↗
NASA NTRS2010

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station a are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS- derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant trend toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management.

Hall, Dorothy K.↗
NASA NTRS2010

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS-derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant end toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management

Hall, Dorothy K.↗
DOE OSTI2025

Evaluating User Errors and Temporal Trends in Marine Fish Communities Using 360-Degree Underwater Photography

The use of environmental DNA (eDNA) sampling has been proposed as a complementary method to monitor fish species in marine environments, offering a non-invasive and potentially more efficient approach to marine species observations. eDNA monitoring could be especially useful in and around sites targeted for marine energy generation as these regions need regular monitoring that would be impractical with traditional techniques. Before we can fully rely upon eDNA, we must first verify its accuracy against other proven methods, such as the use of underwater photography. In this study, I deployed a 360-degree camera in the tidal channel of Sequim Bay once a month during several hours overlapping slack tide. I investigated how having multiple people identify and count fish on underwater images could affect the overall results. Using chi square tests in R, I compared my fish identifications and counts to those made by another intern on the same images recorded in August. I found significant differences in the number of species identified and the total individual counts between the two different datasets. I also tested the statistical differences in both Shannon diversity and Pielou evenness indices between the August, September, and November camera deployments using a Hutcheson t-test. Only one significant difference was found in the Shannon index comparisons, and none were found between the Pielou evenness comparisons. These findings show that if multiple identifiers are used to process underwater images, quality control checks must be made to reduce the potential for error. This also points toward the possibility to leverage more advanced image analysis processes, such as automated image analysis software. The findings from this study also show that the dynamics of marine fish communities can vary over a few months; however, further analysis is needed to determine the extent of the seasonal changes in Sequim Bay.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

Evaluating Approaches Relating Ecosystem Productivity with Desis Spectral Information

Data from the DLR Earth Sensing Imaging Spectrometer (DESIS), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. Twenty DESIS images were used from three widely separated forested study sites representing deciduous and conifer forests. Gross primary production (GPP) values from eddy covariance flux towers at the sites were matched with DESIS spectral reflectances collected on the same days. Multiple algorithms were successful relating spectral reflectance with GPP, including: spectral vegetation indices (SVI) sensitive to chlorophyll content, SVI used in a photosynthetic light-use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to multiband hyperspectral indices from partial least squares regression. Successful algorithms were able to achieve R2 better than 0.7 using a diverse set of observations combining data from different sites from multiple years and at multiple times during the year. The demonstrated robustness of the algorithms provides some confidence in using DESIS imagery to map spatial patterns of GPP.

K F Huemmrich↗
NASA NTRS2022

Evaluating Approaches Relating Ecosystem Productivity with DESIS Spectral Information

Data from the DLR Earth Sensing Imaging Spectrometer (DESIS), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. Twenty DESIS images were used from three widely separated forested study sites representing deciduous and conifer forests. Gross primary production (GPP) values from eddy covariance flux towers at the sites were matched with DESIS spectral reflectances collected on the same days. Multiple algorithms were successful relating spectral reflectance with GPP, including: spectral vegetation indices (SVI) sensitive to chlorophyll content, SVI used in a photosynthetic light-use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to multiband hyperspectral indices from partial least squares regression. Successful algorithms were able to achieve R2 better than 0.7 using a diverse set of observations combining data from different sites from multiple years and at multiple times during the year. The demonstrated robustness of the algorithms provides some confidence in using DESIS imagery to map spatial patterns of GPP.

Gross Primary Productivity (GPP)↗
NASA NTRS1986

Global radar units on Venus derived from statistical analysis of Pioneer Venus Orbiter radar data

The classification of surface radar units on Venus using an unsupervised cluster analysis of Pioneer Venus radar reflectivity and root-mean-square (rms)-slope data is described. The advantages of the unsupervised analysis are discussed. F tests are utilized to evaluate the numerical significance of the clusters. The derived rms-slope data and reflectivity for 15 radar units are presented. The relations between radar data bases and elevation are studied. The lowlands, rolling plains, highlands, and mountainous surface of Venus are examined. The geology of Venus landing sites and radar properties, and the surface radar reflectivity images and earth-based images are compared. The spatial relations between classification units are calculated. It is concluded that the unsupervised analysis data correlate well with Head et al. (1985b) data and produce more detailed classification images.

Davis, P. A.↗
NASA NTRS1992

Multi-resolution processing for fractal analysis of airborne remotely sensed data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals.

Jaggi, S.↗
DOE OSTI2021

CryoEM reveals the stochastic nature of individual ATP binding events in a group II chaperonin

Chaperonins are homo- or hetero-oligomeric complexes that use ATP binding and hydrolysis to facilitate protein folding. ATP hydrolysis exhibits both positive and negative cooperativity. The mechanism by which chaperonins coordinate ATP utilization in their multiple subunits remains unclear. Here we use cryoEM to study ATP binding in the homo-oligomeric archaeal chaperonin from Methanococcus maripaludis (MmCpn), consisting of two stacked rings composed of eight identical subunits each. Using a series of image classification steps, we obtained different structural snapshots of individual chaperonins undergoing the nucleotide binding process. We identified nucleotide-bound and free states of individual subunits in each chaperonin, allowing us to determine the ATP occupancy state of each MmCpn particle. We observe distinctive tertiary and quaternary structures reflecting variations in nucleotide occupancy and subunit conformations in each chaperonin complex. Detailed analysis of the nucleotide distribution in each MmCpn complex indicates that individual ATP binding events occur in a statistically random manner for MmCpn, both within and across the rings. Our findings illustrate the power of cryoEM to characterize a biochemical property of multi-subunit ligand binding cooperativity at the individual particle level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Quantitative Particle Analysis of Neptunium-237 Oxides: Optimization of MAMA Analysis for Modified Direct Denitration Products

The production of plutonium-238 through irradiation of neptunium-237 ( 237 Np) target materials for the use in radioisotope thermoelectric generators is paramount for continued deep space exploration. This work employs scanning electron microscopy to analyze 237 Np materials coupled with a well-developed image analysis framework (Morphological Analysis for Material Attribution, or MAMA) to determine the degree of micron-scale homogeneity in the materials. This work demonstrated how the quantification of particle characteristics can validate production materials and affirm the qualitative similarities observed in micrographs. The 237 Np oxide particle analysis determined that the materials from five production runs were quantitatively homogenous (significant at α = 0.05) in particle area, circularity, equivalent circular diameter, and ellipse aspect ratio, with two of the sampling dates having statistically significant different means for one of the four characteristics. Furthermore, these metrics not only confirm general homogeneity of the material but also expand the application of MAMA workflows to 237 Np materials, demonstrating the utility of MAMA analysis for a wider breadth of nuclear materials than previously reported. In the open literature, this study is the first time that these microanalytical techniques were applied to 237 Np materials to this degree.

MAMA↗
DOE OSTI2020

STRIDES: a 3.9 per cent measurement of the Hubble constant from the strong lens system DES J0408−5354

We present a blind time-delay cosmographic analysis for the lens system DES J0408−5354. This system is extraordinary for the presence of two sets of multiple images at different redshifts, which provide the opportunity to obtain more information at the cost of increased modelling complexity with respect to previously analysed systems. We perform detailed modelling of the mass distribution for this lens system using three band Hubble Space Telescope imaging. We combine the measured time delays, line-of-sight central velocity dispersion of the deflector, and statistically constrained external convergence with our lens models to estimate two cosmological distances. We measure the ‘effective’ time-delay distance corresponding to the redshifts of the deflector and the lensed quasar |$D_{\Delta t}^{\rm eff}=$||$3382_{-115}^{+146}$| Mpc and the angular diameter distance to the deflector D_d = |$1711_{-280}^{+376}$| Mpc, with covariance between the two distances. From these constraints on the cosmological distances, we infer the Hubble constant H_0= |$74.2_{-3.0}^{+2.7}$| km s^−1 Mpc^−^1 assuming a flat ΛCDM cosmology and a uniform prior for Ω_m as |$\Omega _{\rm m} \sim \mathcal {U}(0.05, 0.5)$|⁠. This measurement gives the most precise constraint on H_0 to date from a single lens. Our measurement is consistent with that obtained from the previous sample of six lenses analysed by the H_0 Lenses in COSMOGRAIL’s Wellspring (H0LiCOW) collaboration. It is also consistent with measurements of H_0 based on the local distance ladder, reinforcing the tension with the inference from early Universe probes, for example, with 2.2σ discrepancy from the cosmic microwave background measurement.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

An EPIC Tale of the Quiescent Particle Background

Extended Source Analysis Software Use Based Empirical Investigation: (1) Builds quiescent particle background (QPB) spectra and images for observations of extended sources that fill (or mostly fill) the FOV i.e., annular background subtraction won't work. (2) Uses a combination of Filter Wheel Closed (FWC) and corner data to capture the spectral, spatial, and temporal variation of the quiescent particle background. New Work: (1) Improved understanding of the QPB (aided by adding a whole lot of data since 2008). (2) Significantly improved statistics (did I mention a LOT more data?). (3) Better characterization and identification of anomalous states. (4) Builds backgrounds for some anomalous state. (5) New efficient method for non-anomalous states.

Snowden, S.L.↗
NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗
DOE OSTI2024

Divide and conquer: using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. Sometimes, the amount of roots in a sample is too much to fit into a single scanned image, so the sample is divided among several scans, and there is no standard method to aggregate the data. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image. These concatenated images and the original images were processed with RhizoVision Explorer, a free and open-source software. An R script was developed, which identifies rows of data belonging to the same sample and applies correct statistical methods to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Most root measurements were nearly identical between the two methods except median diameter, which cannot be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

Global View of Aerosol Vertical Distributions from CALIPSO Lidar Measurements and GOCART Simulations: Regional and Seasonal Variations

This study examines seasonal variations of the vertical distribution of aerosols through a statistical analysis of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations from June 2006 to November 2007. A data-screening scheme is developed to attain good quality data in cloud-free conditions, and the polarization measurement is used to separate dust from non-dust aerosol. The CALIPSO aerosol observations are compared with aerosol simulations from the Goddard Chemistry Aerosol Radiation Transport (GOCART) model and aerosol optical depth (AOD) measurements from the MODerate resolution Imaging Spectroradiometer (MODIS). The CALIPSO observations of geographical patterns and seasonal variations of AOD are generally consistent with GOCART simulations and MODIS retrievals especially near source regions, while the magnitude of AOD shows large discrepancies in most regions. Both the CALIPSO observation and GOCART model show that the aerosol extinction scale heights in major dust and smoke source regions are generally higher than that in industrial pollution source regions. The CALIPSO aerosol lidar ratio also generally agrees with GOCART model within 30% on regional scales. Major differences between satellite observations and GOCART model are identified, including (1) an underestimate of aerosol extinction by GOCART over the Indian sub-continent, (2) much larger aerosol extinction calculated by GOCART than observed by CALIPSO in dust source regions, (3) much weaker in magnitude and more concentrated aerosol in the lower atmosphere in CALIPSO observation than GOCART model over transported areas in midlatitudes, and (4) consistently lower aerosol scale height by CALIPSO observation than GOCART model. Possible factors contributing to these differences are discussed.

Yu, Hongbin↗