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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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NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We investigate two related approaches to prediction of GS cloud properties from SGS variability: the critical saturation ratio method, and the critical relative humidity method. We find significant correlation between GS cloud water and SGS supersaturation when the critical saturation ratio is set at 100%, as well as a notable relationship between GS cloud water and the width of the SGS total water distribution. Critical relative humidity also compares well with GS cloud water. However, we also find that the assumptions of a static critical saturation ratio of 100% to be unrealistic, as well as a fixed SGS distribution width. Empirical calculations from the ARISE data show a large sensitivity of these SGS variables to GS relative humidity, and so a SGS parameterization allowing them to vary according to GS thermodynamic properties may result in more realistic GS cloud water values.

J. Brant Dodson↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We examine the influence of three assumed SGS parameters on the estimation of GS cloud water: the width of the SGS PDF of total water (ΔQT), the shape of the SGS PDF, and the critical saturation ratio (Scrit), which partitions the SGS PDF into water that is available or not for conversion to cloud water. Both Scrit and ΔQT influence predicted GS cloud water strongly. ARISE and FIRE-ACE disagree somewhat in the details, but both campaigns support the possibility that more realistic representations of these two parameters may lead to more realistic GS cloud water. In particular, both parameters are sensitive to GS relative humidity, and so we examine the effects of allowing these quantities to vary as an empirically-derived linear function of GS relative humidity. In contrast, the shape of the PDF has little effect on the predicted cloud water – a surprising result that merits additional investigation.

J Brant Dodson↗
NASA NTRS1986

Error propagation in a digital avionic processor: A simulation-based study

An experimental analysis to study error propagation from the gate to the chip level is described. The target system is the CPU in the Bendix BDX-930, an avionic miniprocessor. Error activity data for the study was collected via a gate-level simulation. A family of distributions to characterize the error propagation, both within the chip and at the pins, was then generated. Based on these distributions, measures of error propagation and severity were defined. The analysis quantifies the dependency of the measured error propagation on the location of the fault and the type of instruction/microinstruction executed.

Lomelino, D.↗
NASA NTRS1995

Aircrew Discourse: Exploring Strategies of Information and Action Management

This paper explores methodology issues encountered in the analysis of flightcrew communications in aviation simulation research. Examples are provided by two recent studies which are compared on three issues: level of analysis, data definition, and interpretation of the results. The data discussed were collected in a study comparing two levels of aircraft automation. The first example is an investigation of how pilots' information transfer strategies differed as a function of automation during low and high-workload flight phases. The second study focuses on how crews managed actions in the two aircraft during a ten minute, high-workload flight segment. Results indicated that crews in the two aircraft differed in their strategies of information and action management. The differences are discussed in terms of their operational and research significance.

Irwin, Cheryl M.↗
NASA NTRS2012

Toward Lower Organic Environments in Astromaterial Sample Curation for Diverse Collections

Great interest was taken during the frenzied pace of the Apollo lunar sample return to achieve and monitor organic cleanliness. Yet, the first mission resulted in higher organic contamination to samples than desired. But improvements were accomplished by Apollo 12 [1]. Quarantine complicated the goal of achieving organic cleanliness by requiring negative pressure glovebox containment environments, proximity of animal, plant and microbial organic sources, and use of organic sterilants in protocols. A special low organic laboratory was set up at University of California Berkeley (UCB) to cleanly subdivide a subset of samples [2, 3, 4]. Nevertheless, the basic approach of handling rocks and regolith inside of a positive pressure stainless steel glovebox and restrict-ing the tool and container materials allowed in the gloveboxes was established by the last Apollo sample re-turn. In the last 40 years, the collections have grown to encompass Antarctic meteorites, Cosmic Dust, Genesis solar wind, Stardust comet grains and Hayabusa asteroid grains. Each of these collections have unique curation requirements for organic contamination monitor-ing and control. Here is described some changes allowed by improved technology or driven by changes in environmental regulations and economy, concluding with comments on organic witness wafers. Future sample return missions (OSIRIS-Rex; Mars; comets) will require extremely low levels of organic contamination in spacecraft collection and thus similarly low levels in curation. JSC Curation is undertaking a program to document organic baseline levels in current operations and devise ways to reduce those levels.

Allton, J. H.↗
NASA NTRS2000

BOREAS RSS-14 Level-1a GOES-8 Visible, IR and Water Vapor Images

The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. The level-1a GOES-8 images were created by BORIS personnel from the level-1 images delivered by FSU personnel. The data cover 14-Jul-1995 to 21-Sep-1995 and 12-Feb-1996 to 03-Oct-1996. The data start out as three bands with 8-bit pixel values and end up as five bands with 10-bit pixel values. No major problems with the data have been identified. The differences between the level-1 and level-1a GOES-8 data are the formatting and packaging of the data. The images missing from the temporal series of level-1 GOES-8 images were zero-filled by BORIS staff to create files consistent in size and format. In addition, BORIS staff packaged all the images of a given type from a given day into a single file, removed the header information from the individual level-1 files, and placed it into a single descriptive ASCII header file. The data are contained in binary image format files. Due to the large size of the images, the level-1a GOES-8 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1a GOES-8 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS1987

Status report on a natural laminar-flow nacelle flight experiment

The natural laminar flow (NLF) nacelle experiment is part of a drag reduction production program, and has the dual objectives of studying the extent of NLF on full scale nacelles in a flight environment and the effect of acoustic disturbance on the location of transition on the nacelle surface. The experiment is being conducted in two phases: (1) an NLF fairing was flown on a full scale Citation nacelle to develop the experiment technique and establish feasibility; (2) full scale, flow through, NLF nacelles located below the right wing of an experimental NASA OV-1 aircraft are evaluated. The measurements of most interest are the static pressure distribution and transition location on the nacelle surface, and the fluctuating pressure levels associated with the noise sources. Data are collected in combinations of acoustic frequencies and sound pressure levels. The results of phase 2 tests to date indicate that on shape GE2, natural laminar flow was maintained as far aft as the afterbody joint at 50 percent of the nacelle length. An aft facing step at this joint caused premature transition at this station. No change was observed in the transition pattern when the noise sources were operated.

Hastings, Earl C., Jr.↗
NASA NTRS2022

Ozone Monitoring Instrument (OMI) collection 4: establishing a 17-year-long series of detrended level-1b data

The Ozone Monitoring Instrument (OMI) was launched on 15 July 2004, with an expected mission lifetime of 5 years. After more than 17 years in orbit the instrument is still functioning satisfactorily and in principle can continue doing so until the expected decommissioning of its platform Aura in 2025. In order to continue the datasets acquired by OMI and the Microwave Limb Sounder, the mission was extended up to at least 2023. Actions have been taken to ensure the proper functioning of the OMI operations, the data processing, and the calibration monitoring system until the eventual end of the mission. For the data processing a new level-0 (L0) to level-1b (L1b) data processor was built based on the recent developments for the TROPOspheric Monitoring Instrument (TROPOMI). With corrections for the degradation of the instrument now included, it is feasible to generate a new data collection to supersede the current collection-3 data products and reprocess the data of the entire mission up to now. This paper describes the differences between the collection-3 and collection-4 data. It will be shown that the collection-4 L1b data comprise a clear improvement with respect to the previous collections. By correcting for the gentle optical and electronic aging that has occurred over the past 17 years, OMI’s ability to make trend-quality ozone measurements has further improved.

UV↗
NASA NTRS2000

BOREAS RSS-14 Level-1 GOES-8 Visible, IR and Water Vapor Images

The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. The level-1 BOREAS GOES-8 images are raw data values collected by RSS-14 personnel at FSU and delivered to BORIS. The data cover 14-Jul-1995 to 21-Sep-1995 and 01-Jan-1996 to 03-Oct-1996. The data start out containing three 8-bit spectral bands and end up containing five 10-bit spectral bands. No major problems with the data have been identified. The data are contained in binary image format files. Due to the large size of the images, the level-1 GOES-8 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1 GOES-8 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS2021

Tonlé Sap Food Security and Agriculture: Evaluating the Effects of Land Use and Hydrological Change on Ecosystem Vitality using Remotely-Sensed Data in the Tonlé Sap Lake Basin

Tonlé Sap Lake, the largest lake in Southeast Asia, is a critical source of fish and freshwater resources for the region. The health of this freshwater system is under pressure from accelerating dam construction, intensifying agriculture, deforestation, and changing climate patterns, forcing tradeoffs between immediate food security and the long-term vitality and productivity of the ecosystem. Efficient freshwater system monitoring is crucial to navigating these challenges. In collaboration with Conservation International, the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority, we developed and tested remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI), which is typically calculated using in situ datasets. We used landcover datasets derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), PROBA-V Vegetation sensor (VGT), Sentinel-2 Multispectral Imager (MSI), Advanced Very High Resolution Radiometer (AVHRR), and Envisat Medium Resolution Imaging Spectrometer (MERIS) as inputs to calculate land cover naturalness and bank modification. Additionally, we created a lake-level time series using a collection of altimetry data sources to estimate deviation from natural flow. We observed a decrease in landcover naturalness and a breakdown in the volume and regularity of annual lake levels from 2000-2020, reflecting increased pressure on water supply and agricultural productivity. At least 8% of forested areas in the basin were lost and rice harvest intensity increased over the course of the study period. These results will help our partners make informed decisions regarding freshwater management. Furthermore, our remotely-sensed FHI analysis can be replicated in other regions, providing decision makers with a snapshot of freshwater health in data-scarce environments.

Marco Vallejos↗
NASA NTRS2004

A Survey of Collectives

Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a well-defined set of system-level performance criteria, are called collectives. The fundamental problem in analyzing/designing such systems is in determining how the combined actions of self-interested agents leads to 'coordinated' behavior on a iarge scale. Examples of artificial systems which exhibit such behavior include packet routing across a data network, control of an array of communication satellites, coordination of multiple deployables, and dynamic job scheduling across a distributed computer grid. Examples of natural systems include ecosystems, economies, and the organelles within a living cell. No current scientific discipline provides a thorough understanding of the relation between the structure of collectives and how well they meet their overall performance criteria. Although still very young, research on collectives has resulted in successes both in understanding and designing such systems. It is eqected that as it matures and draws upon other disciplines related to collectives, this field will greatly expand the range of computationally addressable tasks. Moreover, in addition to drawing on them, such a fully developed field of collective intelligence may provide insight into already established scientific fields, such as mechanism design, economics, game theory, and population biology. This chapter provides a survey to the emerging science of collectives.

Tumer, Kagan↗
NASA NTRS2013

Cryogenic Liquid Sample Acquisition System for Remote Space Applications

There is a need to acquire autonomously cryogenic hydrocarbon liquid sample from remote planetary locations such as the lakes of Titan for instruments such as mass spectrometers. There are several problems that had to be solved relative to collecting the right amount of cryogenic liquid sample into a warmer spacecraft, such as not allowing the sample to boil off or fractionate too early; controlling the intermediate and final pressures within carefully designed volumes; designing for various particulates and viscosities; designing to thermal, mass, and power-limited spacecraft interfaces; and reducing risk. Prior art inlets for similar instruments in spaceflight were designed primarily for atmospheric gas sampling and are not useful for this front-end application. These cryogenic liquid sample acquisition system designs for remote space applications allow for remote, autonomous, controlled sample collections of a range of challenging cryogenic sample types. The design can control the size of the sample, prevent fractionation, control pressures at various stages, and allow for various liquid sample levels. It is capable of collecting repeated samples autonomously in difficult lowtemperature conditions often found in planetary missions. It is capable of collecting samples for use by instruments from difficult sample types such as cryogenic hydrocarbon (methane, ethane, and propane) mixtures with solid particulates such as found on Titan. The design with a warm actuated valve is compatible with various spacecraft thermal and structural interfaces. The design uses controlled volumes, heaters, inlet and vent tubes, a cryogenic valve seat, inlet screens, temperature and cryogenic liquid sensors, seals, and vents to accomplish its task.

Mahaffy, Paul↗
NASA NTRS1986

Euler solutions using an implicit multigrid technique

A coarse-grid correction algorithm has been implemented into an implicit upwind Euler solver and tested for transonic airfoil problems. The Euler solver uses split-flux formulation and penta-diagonal scalar equations, respectively, for the explicit and implicit operators. The multigrid sequence starts at the fine grid level, then steps down to each coarse grid level to smooth error components using implicit operators. Estimate of residuals can be obtained by two approaches, which differ in the level where the residuals are collected. Both approaches will lead to a work reduction factor of 12 for a Mach 0.75 flow at 2 degrees incidence on a 65x26 grid. The work reduction factor is found to increase proportional to the number of grid levels.

Li, Chien-Peng↗
NASA NTRS2004

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

Oreopoulos, Lazaros↗
NASA NTRS2000

BOREAS RSS-14 Level-1 GOES-7 Visible, IR and Water Vapor Images

The BOREAS RSS-14 team collected and processed GOES-7 and -8 images of the BOREAS region as part of its effort to characterize the incoming, reflected, and emitted radiation at regional scales. The level-1 BOREAS GOES-7 image data were collected by RSS-14 personnel at FSU and delivered to BORIS. The data cover the period of 01-Jan-1994 through 08-Jul-1995, with partial to complete coverage on the majority of the days. The data include three bands with eight-bit pixel values. No major problems with the data have been identified. Due to the large size of the images, the level-1 GOES-7 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1 GOES-7 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS2000

BOREAS RSS-14 Level 1a GOES-7 Visible, IR, and Water Vapor Images

The BOREAS RSS-14 team collected and processed GOES-7 and -8 images of the BOREAS region as part of its effort to characterize the incoming, reflected, and emitted radiation at regional scales. The level-1a BOREAS GOES-7 image data were collected by RSS-14 personnel at FSU and processed to level-1a products by BORIS personnel. The data cover the period of 01-Jan-1994 through 08-Jul-1995 with partial to complete coverage on the majority of the days. The data include three bands with eightbit pixel values. No major problems with the data have been identified. Due to the large size of the images, the level-1a GOES-7 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1a GOES-7 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS2016

A Quantum Annealing Computer Team Addresses Climate Change Predictability

The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be converted to a BM algorithm implementation on the QAC. The first integer adder has been implemented on the D-Wave 2X by A. Shehab that will perform HAAR wavelets for image compression of MODIS scenes. Finally, based on the next generations of QACs, we are preparing a 5-year performance road map on the scalability of the current QAC algorithms.

Science Data Processing↗