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At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Salvaging Data Records with Missing Data: Data Imputation using the Multivariate t Distribution

When doing multivariate data analysis, one commonobstacle is the presence of incomplete observations, i.e., observationsfor which one or more key fields are blank. Missing datais often countered by deleting entire observations that containmissing data. The negative effects of deleting entire observationsare multiple: deleting observations reduces sample size andcan also result in biased inferences even if data is missing atrandom. In addition, knowledge contained within incompleteobservations is knowledge lost when they are deleted– and theeffort spent collecting that knowledge is effort wasted. Data imputationmethods, or methods of statistically “filling-in” missingdata, can help combat small sample sizes by using the existinginformation in partially complete observations with the end goalof producing less biased and higher confidence inferences. Whena sample from a multivariate normal population is only partiallycomplete, and the missing data meets appropriate assumptions(missing at random), robust data imputation of the missing datacan be implemented with monotone data augmentation (MDA)using the multivariate t distribution.Missing data imputation is applied to data from the NASA InstrumentCost Model (NICM) using the MDA algorithm underthe assumption of having a multivariate t distribution with fixeddegrees of freedom. A sensitivity analysis to the degrees offreedom parameter is presented to demonstrate robustness ofthe multivariate t distribution when dealing with small samplesas compared to the multivariate normal distribution.

DiNicola, Michael↗
NASA NTRSDate not supplied

Applications of Advanced Perception and Distributed Sensing Technology towards Autonomous Advanced Air Mobility Applications

Emerging concepts for Advanced Air Mobility (AAM) envisions responsive air transportation capabilities that can safely move people and cargo between places - including local, regional, intraregional, and urban - previously not served or underserved by aviation. Expanding traditional aviation services to these environments, particularly when autonomous operations are involved, face a number of challenges that will require advances beyond the state-of-the-art techniques for airborne sensing and perception, which goes beyond the limits of scalability and applicability of the current air transportation system infrastructure. Additionally, the emerging field of distributed sensing and ‘smart spaces’– where sensing, processing, communication, and actuation are embedded in the environment in which agents are acting and can be exploited by the agents through real-time wireless communication – may provide realistic near-time solutions to limitations imposed by traditional aviation techniques. This paper outlines the needs, challenges, and opportunities for advanced perception and distributed sensing techniques to meet the emerging needs for advanced AAM operations in the national airspace. A general roadmap for research, development, and maturation of perception and distributed sensing (P&DS) technologies is proposed to guide future development through verification, validation, certification into airborne systems. Through this analysis of challenges and the proposed roadmap for technology maturation, we hope to accelerate transition of advanced research techniques from other disciplines into this domain.

Autonomy↗
NASA NTRSDate not supplied

Deriving representative size distributions from UW OPC data for SAGE II extinction measurements

For the purposes of studying the impacts of aerosols on the chemistry and climate of the atmosphere, size distribution information has been inferred from extinction measurements for decades. Using the measurements from the University of Wyoming balloon-borne optical particle counter experiment we have derived representative size distributions at SAGE II channel wavelengths. These are bimodal lognormal size distributions grouped into bins of 525 to 1020 nm extinction ratio. Future work will include expanding this analysis to SAGE III’s channels and considering the effect of a absorbing channel in the IR would have.

Aerosol↗
NASA NTRSDate not supplied

Quantifying Uncertainty in Particle Size Distribution Parameters Inferred from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on their microphysical properties such as particle size distribution (PSD). The PSD is a mathematical description of the relative abundance of different sized particles within a sampling volume. If the PSD is accurately known then other key modeling parameters (e.g., surface area density) can be derived. Occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts failed to address two key issues with this methodology: 1. The measurement uncertainty was not accounted for; 2. They assumed the PSDs to be single-mode only, while “real-world” PSDs are predominantly bi-modal. Accounting for both issues in the retrieval will yield an expanded solution space to the inferred PSD parameters; the question is “by how much?” To address this knowledge gap, we propose to carry out a series of simulations and, for every valid SAGE III/ISS data point, determine the range of PSD parameters that yield extinction spectra that are indistinguishable from the SAGE III/ISS data, within the limits of the reported uncertainty. Further, we will expand the solution space, for the first time, to include bimodal distributions. The results of this work will advance Earth system modeling/prediction capability through identifying the uncertainty of PSD parameter estimates using SAGE III/ISS data. The key benefits of this study over previous studies are twofold: 1. we will provide PSD estimates that include bimodal distributions in the solution space, 2. we will provide an uncertainty estimate for these parameters. The results of this study may be used directly in current and future climate and chemistry models.

SAGE III/ISS↗
NASA NTRS2022

Comparisons Between the Distributions of Dust and Combustion Aerosols in MERRA-2, FLEXPART and CALIPSO and Implications for Deposition Freezing Over Wintertime Siberia

Aerosol distributions have a potentially large influence on climate-relevant cloud properties but can be difficult to observe over the Arctic given pervasive cloudiness, long polar nights, data paucity over remote regions, and periodic diamond dust events that satellites can misclassify as aerosol. We compared Arctic 2008–2015 mineral dust and combustion aerosol distributions from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis products, and the FLEXible PARTicle (FLEXPART) dispersion model. Based on coincident, seasonal Atmospheric Infrared Sounder (AIRS) Arctic satellite meteorological data, diamond dust may occur up to 60 % of the time in winter, but it hardly ever occurs in summer. In its absence, MERRA-2 and FLEXPART each predict the vertical and horizontal distribution of large-scale patterns in combustion aerosols with relatively high confidence (Kendall tau rank correlation > 0.6), although a sizable amount of variability is still unaccounted for. They do the same for dust, except in conditions conducive to diamond dust formation where CALIPSO is likely misclassifying diamond dust as mineral dust and near the surface (< ∼ 2 km) where FLEXPART may be overpredicting local dust emissions. Comparisons to ground data suggest that MERRA-2 Arctic dust concentrations can be improved by the addition of local dust sources. All three products predicted that wintertime dust and combustion aerosols occur most frequently over the same Siberian regions where diamond dust is most common in the winter. This suggests that dust aerosol impacts on ice phase processes may be particularly high over Siberia, although further wintertime model validation with non-CALIPSO observations is needed. This assessment paves the way for applying the model-based aerosol simulations to a range of regional-scale Arctic aerosol–cloud interaction studies with greater confidence.

MERRA-2↗
NASA NTRS2022

Remote Sensing of Aerosol Water Fraction, Dry Size Distribution and Soluble Fraction Using Multi-Angle, Multi-Spectral Polarimetry

A framework to infer volume water fraction, soluble fraction and dry size distributions of fine mode aerosol from multi-angle, multi-spectral polarimetry retrievals of column-averaged ambient aerosol properties is presented. The method is applied to observations of the Research Scanning Polarimeter (RSP) obtained during two NASA aircraft campaigns, namely the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) and the Cloud, Aerosol, and Monsoon Processes-Philippines Experiment (CAMP2Ex). All aerosol retrievals are statistically evaluated using in situ data. Volume water fraction is inferred from the retrieved ambient real part of the refractive index, assuming a dry refractive index of 1.54 and by applying a volume mixing rule to obtain the effective ambient refractive index. The uncertainties in inferred volume water fraction resulting from this simplified model are discussed and estimated to be lower than 0.2 and decreasing with increasing volume water fraction. The daily mean retrieved volume water fractions correlate well with the in situ values with a mean absolute difference of 0.09. Polarimeter-retrieved ambient effective radius for daily data is shown to increase as a function of volume water fraction as expected. Furthermore, the effective variance of the size distributions also increases with increasing effective radius, which we show is consistent with an external mixture of soluble and insoluble aerosol. The relative variations of effective radius and variance over an observation period are then used to estimate the soluble fraction of the aerosol. Daily results of soluble fraction correlate well with in situ observed sulfate mass fraction with a correlation coefficient of 0.79. Subsequently, inferred water and soluble fractions are used to derive dry fine-mode size distributions from their ambient counterparts. While dry effective radii obtained in situ and from RSP show similar ranges, in situ values are generally substantially smaller during the ACTIVATE deployments, which may be due to biases in RSP retrievals or in the in situ observations, or both. Both RSP and in situ observations indicate the dominance of aerosol with low hygroscopicity during the ACTIVATE and CAMP2Ex campaigns. Furthermore, RSP indicates a high degree of external mixing of particles with low and high hygroscopicity. These retrievals of fine mode water volume fraction and soluble fraction may be used for the evaluation of water uptake in atmospheric models. Furthermore, the framework allows to estimate the variation in the concentration of fine-mode aerosol larger than a specific dry radius limit, which can be used as a proxy for the variation in cloud condensation nucleus concentrations. This framework may be applied to multi-angle, multi-spectral satellite data expected to be available in the near future.

Bastiaan Van Diedenhoven↗
NASA NTRS2021

The Effect of Transfer Line Length and Heat Rejection Temperature Distribution on the Thales Linear Pulse Tube (LPT) Cryocoolers

Four Thales LPT9310 and four Thales LPT9510 commercial off-the-shelf (COTS) cryocoolers were parametrically performance tested. The LPT9310 coolers had transfer lines of various lengths while the LPT9510 coolers all had the same transfer line geometry. The LPT9510 test results revealed unit-tounit thermodynamic performance variation, quantified the effect of compressor temperature on thermodynamic performance and quantified the heat flow distribution between the compressor and expander as a function of their temperature distribution. The LPT9310 test results revealed the optimal drive frequency as a function of transfer line length, quantified the effect of heat rejection temperature distribution on thermodynamic performance and enabled the development and verification of a thermodynamic performance prediction tool that accounted for cold tip temperature, heat lift, heat rejection temperature and transfer line length.

Rodriguez, J.I.↗
NASA NTRS2021

The spatial distribution of ionospheric threats to WAAS integrity, 2000 – 2019: a systematic analysis

The United States’ Wide Area Augmentation System (WAAS) broadcasts data to facilitate aircraft navigation. This paper examines the spatial dependence of ionospheric disturbances that have threatened the accuracy and reliability of position estimates derived from these data over the period 2000 – 2019. We address two distinct aspects of this spatial dependence: (1) the geographic distribution of these threats, in particular, in relation to geomagnetic latitude, and (2) the geometric dependence of threats relative to the locations of the receiver sites that comprise the WAAS network. We analyze threat distributions in terms of the various means that WAAS employs to mitigate these threats, including the Extreme Storm Detector, the Moderate Storm Detector, local irregularity detectors, and the ionospheric threat model. Distinct distributions are presented for threats occurring in Solar Cycle 23 and those of Solar Cycle 24. To study the geometric dependence of threats on receiver locations, we use as a metric the distance separating a threat from the centroid of the nearest Ncentroid receivers. Large values of this metric identify threats at or beyond the edge of coverage. We conclude by discussing the implications of our results for WAAS operations.

Altshuler, Eric↗
NASA NTRS2021

Distributed Aperture Radar Tomographic Sensors (darts) to Map Surface Topography and Vegetation Structure

Distributed Aperture Radar Tomographic Sensors (DARTS)is a mission concept being studied at the NASA Jet PropulsionLaboratory in collaboration with the California Institute ofTechnology to enable global and repeated imaging of surfacetopography and three-dimensional vegetation structure usingsingle-pass tomographic SAR technique. The observing systemconsists of a distributed formation of multiple small syntheticaperture radar platforms deployed in space with variabledistances to achieve look angle diversity and sensitivityto the vertical distribution of vegetation components. Ourgoal is to identify the optimal system configuration startingfrom documented community needs and mature the criticaltechnologies that lead to a viable implementation of DARTS.Here, we provide an overview of DARTS and describe ourapproach for designing and demonstrating single-pass SARtomographic systems as part of an on-going funded NASA Instrument Incubator Program effort.

Chung, Soon-Jo↗
NASA NTRS2023

Distributed Sensing and Reasoning for Advanced Air Mobility Health Management and Mission Assurance

As envisioned, Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) will introduce new vehicles and operations within the national airspace, moving people and cargo safely and efficiently at a much larger scale than today. Driven by transformative technology and revolutionary aircraft, this movement must still manage technical, regulatory, operational, and policy challenges. NASA’s work in support of AAM and UAM includes, but is not limited to tools, technologies, and architectures for distributed sensing of aircraft, data & reasoning services exchange, Human-Autonomy Teaming (HAT), contingency management, and vehicle health management. This paper builds upon these concepts and evaluates the use of distributed sensing and infrastructure assistance towards health management and mission assurance of UAM vehicles in specific operational scenarios. Through analysis of these example missions, aided by the data produced by the conceptual distributed sensing and reasoning infrastructure, we define opportunities for state estimation, diagnosis, and key decision points affecting the health state of the vehicle and the airspace volume. As a result, we define a number of measurable health state parameters providing relevant information to drive decision-making in contingency situations or feed automation tools in support of operators and managers.

Safety↗
NASA NTRSDate not supplied

Deriving Representative Size Distributions From UW OPC Data for Sage II Extinction Measurements

For the purposes of studying the impacts of aerosols on the chemistry and climate of the atmosphere, size distribution information has been inferred from extinction measurements for decades. Using the measurements from the University of Wyoming balloon-borne optical particle counter experiment we have derived representative size distributions at SAGE II channel wavelengths. These are bimodal lognormal size distributions grouped into bins of 525 to 1020 nm extinction ratio. However there exists fundamental limitations to the information that can be derived from SAGE measurements. Future work will include expanding this analysis to SAGE III’s channels and considering the effect of a absorbing channel in the IR would have.

Aerosol↗
NASA NTRSDate not supplied

ASDC Distribution and Services of TEMPO Data

The Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument represents a groundbreaking advancement in remote sensing technology, providing real-time and high-resolution measurements of atmospheric pollutants and air quality monitoring. This presentation will highlight the significance of TEMPO and its data distribution by NASA’s Atmospheric Science Data Center (ASDC) to facilitate the analyses by the research and end user communities. TEMPO's geostationary orbit allows for continuous and high-resolution measurements of key atmospheric pollutants, including nitrogen dioxide (NO 2 ), ozone (O 3 ), and formaldehyde (HCHO). As a result, researchers can investigate the distribution patterns of these pollutants on an hourly basis, providing valuable information for understanding regional and temporal variations in air quality. Furthermore, this presentation will highlight the usability of TEMPO data in complementing ground-based air quality monitoring networks. ASDC distribution services and tools facilitate efficient data handling and analysis to support research and application uses of TEMPO data. As part of NASA’s Earthdata ecosystem, TEMPO will be available through Earthdata Search and Worldview, as well as have variable and spatial subsetting capabilities. This presentation will provide an overview of data access and services available for TEMPO data.

Hazem Mahmoud↗
NASA NTRSDate not supplied

Coarsening Up: Expanding the Particle Size Distributions of Lunar Simulants to Encompass A Comprehensive Range of Regolith Granularity

Due to a paucity of lunar regolith samples, simulated granular materials (simulants) have been developed and deployed for a variety of engineering and research purposes in an attempt to meet the requirements for lunar exploration. Broadly speaking, these manufactured materials aim to replicate the compositional (i.e., mineralogy and chemistry) and physical (e.g., particle size distribution, particle shape) profiles of lunar soil samples collected during the Apollo missions. While creating a “near-perfect” lunar simulant is prohibitive due to the unique formative processes (i.e., meteorite impacts, solar wind implantation) and conditions (anhydrous, reducing environment and exposure to radiation on the surface over billions of years) encountered on the moon, certain granular properties of the regolith can be recreated with a high level of fidelity by leveraging contemporary technologies. A fundamental physical property and descriptor, grain size can be correlated between samples and replicated through processing; however, a holistic understanding of the particle size distribution of lunar regolith must be considered when creating analog materials. This study produces particle size distributions for Apollo 16 returned samples, incorporating the sieved out >1 cm coarse-grained fraction, in order to provide a more comprehensive characterization of surficial lunar regolith grain sizes for the development of highlands-type granular analog testing materials.

R. N. Kovtun↗
NASA NTRS2017

Analysis of in Vitro Evolution Reveals the Underlying Distribution of Catalytic Activity Among Random Sequences

The emergence of catalytic RNA is believed to have been a key event during the origin of life. Understanding how catalytic activity is distributed across random sequences is fundamental to estimating the probability that catalytic sequences would emerge. Here, we analyze the in vitro evolution of triphosphorylating ribozymes and translate their fitnesses into absolute estimates of catalytic activity for hundreds of ribozyme families. The analysis efficiently identified highly active ribozymes and estimated catalytic activity with good accuracy. The evolutionary dynamics follow Fisher’s Fundamental Theorem of Natural Selection and a corollary, permitting retrospective inference of the distribution of fitness and activity in the random sequence pool for the first time. The frequency distribution of rate constants appears to be log-normal, with a surprisingly steep dropoff at higher activity, consistent with a mechanism for the emergence of activity as the product of many independent contributions.

Abe Pressman↗
NASA NTRSDate not supplied

Deriving Representative Size Distributions From UW OPC Data for Sage II Extinction Measurements

For the purposes of studying the impacts of aerosols on the chemistry and climate of the atmosphere, size distribution information has been inferred from extinction measurements for decades. Using the measurements from the University of Wyoming balloon-borne optical particle counter experiment we have derived representative size distributions at SAGE II channel wavelengths. These are bimodal lognormal size distributions grouped into bins of 525 to 1020 nm extinction ratio. However there exists fundamental limitations to the information that can be derived from SAGE measurements. Future work will include expanding this analysis to SAGE III’s channels and considering the effect of a absorbing channel in the IR would have.

Aerosol↗
NASA NTRS2023

Distributions of Mesoscale Periodic Structures in the Elemental and Ionic Composition of the Solar Wind

Multiple statistical and event studies based on in situ observations have shown that the solar wind contains mesoscale (∼ 100 – 10,000 Mm) periodic structures in the proton number density. Remote observations of such structures and event studies of concurrent variations in composition have demonstrated that they can form in the solar atmosphere and be preserved while advecting outwards through the heliosphere. Viall, Kepko, and Spence (J. Geophys. Res. (Space Phys.) 113, A07101, 2008; J. Geophys. Res. (Space Phys.) 114, A01201, 2009) and Kepko, Viall, and Wolfinger (J. Geophys. Res. (Space Phys.) 125(8), e28037, 2020) have reported that periodic proton density structures preferentially occur at specific radial length scales and have published their distributions from Wind measurements near L1. Here, we conduct a statistical study of 14 years (1998 – 2011) of 12-minute composition data measured by the Solar Wind Ion Composition Spectrometer instrument aboard the Advanced Composition Explorer spacecraft. We found that the elemental and ionic composition also contain statistically significant mesoscale periodic structures and, for the first time, present occurrence distributions for elemental abundance ratios with low, intermediate, and high first ionization potentials as well as for key solar wind charge states. These distributions set important constraints on solar wind formation in general and the formation of periodic mesoscale solar wind structures specifically, as the elemental and ionic composition are known to be determined at the Sun and to not evolve during advection.

Solar wind↗
NASA NTRS2024

Emplacement of Shergottites in the Martian Crust Inferred From 3D Petrofabric and Crystal Size Distribution Analyses

Shergottites are mafic to ultramafic igneous rocks that represent a majority of known martian meteorites. They are subdivided into gabbroic, poikilitic, basaltic, and olivine-phyric categories based on differences in mineralogy and textures. Their geologic contexts are unknown so analyses of crystal sizes and preferred orientations have commonly been used to infer where shergottites solidified. Such environments range from subsurface cumulates to shallow intrusives to extrusive lava flows, which all have contrasting implications for interactions with crustal material, cooling histories, and potential in situ exposure at the surface. In this study, we present a novel three-dimensional (3D) approach to better understand the solidification environments of these samples and improve our knowledge of shergottites’ geologic contexts. Shape preferred orientations of most phases and crystal size distributions of late-forming minerals were measured in 3D using X-ray computed tomography (CT) on eight shergottites representing the gabbroic, poikilitic, basaltic, and olivine-phyric categories. Our analyses show that highly anisotropic, rod-like pyroxene crystals are strongly foliated in the gabbroic samples but have a weaker foliation and a mild lineation in the basaltic sample, indicating a directional flow component in the latter. Star volume distribution analyses revealed that most phases (maskelynite, pyroxene, olivine, and oxides/sulfides) preserve a foliated texture with variable strengths, and that the phases within individual samples are strongly to moderately aligned with respect to one another. In combination with relative cooling rates during the final stages of crystallization determined from interstitial oxide/sulfide crystal size distribution analyses, these results indicate that the olivine-phyric samples were emplaced as shallow intrusives (e.g., dikes/sills) and that the gabbroic, poikilitic, and basaltic samples were emplaced in deeper subsurface environments.

Martian meteorites↗