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NASA NTRSDate not supplied

Enabling Open and Interoperable Science: Multi-Omics Data Processing Platform with NASA GeneLab Standardized Bioinformatics Workflows for Space and Earth Research

Multi-omics biological data continues to be generated at an astounding pace. Genomics, transcriptomics, metabolomics, and proteomics, or collectively known as multi-omics data, are used to assess biological functions, and provide invaluable insights into human, animal, plant, and environmental health both on Earth and in Space. Despite the abundance of these valuable data, the need for bioinformatics expertise, particularly as it relates to the niche filed of space biology, and a lack of accessible resources for processing these data limit their usefulness in deriving biological insights. The NASA Open Science Data Repository (OSDR) provides access to omics data from various spaceflight and analog studies. To enhance the accessibility and reusability of these data, GeneLab (part of OSDR) designs and implements standardized, community-driven, open-source bioinformatics workflows to transform raw omics data into standardized processed data. Currently, GeneLab-processed data from hundreds of space studies have been reused for meta-analyses. This has led to new insights and scientific publications that extend beyond the initial research, thereby enriching our understanding of molecular-scale biological responses to the space environment. To make these bioinformatics workflows open and accessible, GeneLab teamed up with DOE-funded initiatives, including the National Microbiome Data Collaborative (NMDC), to create the NASA EDGE [Empowering the Development of Genomics Expertise] Bioinformatics web-based platform. NASA EDGE utilizes shared compute resources to run the GeneLab standardized bioinformatics workflows, which eliminates the need for researchers to have their own high performance computing cluster. The web-based platform makes complicated biological analyses incredibly easy to perform, thus expanding the reach of these analyses to bioinformatics novices, students, and even citizen scientists enabling them to contribute to scientific discoveries and progress. The authors will demonstrate how the NASA EDGE platform can be used to process microbial omics data hosted on OSDR as well as user-generated omics datasets using GeneLab’s standard workflows.

Amanda M. Saravia-Butler↗
NASA NTRS2014

Long Term Displacement Data of Woven Fabric Webbings Under Constant Load for Inflatable Structures

Inflatable modules for space applications offer weight and launch volume savings relative to current metallic modules. Limited data exist on the creep behavior of the restraint layer of inflatable modules. Long-term displacement and strain data of two high strength woven fabric webbings, Kevlar and Vectran, under constant load is presented. The creep behavior of webbings is required by designers to help determine service life parameters of inflatable modules. Four groups of different webbings with different loads were defined for this study. Group 1 consisted of 4K Kevlar webbings loaded to 33% ultimate tensile strength and 6K Vectran webbings loaded to 27% ultimate tensile strength, group 2 consisted of 6K Kevlar webbings loaded to 40% and 43% ultimate tensile strength, and 6K Vectran webbings loaded to 50% ultimate tensile strength, group 3 consisted of 6K Kevlar webbings loaded to 52% ultimate tensile strength and 6K Vectran webbings loaded to 60% ultimate tensile strength, and group 4 consisted of 12.5K Kevlar webbings loaded to 22% ultimate tensile strength, and 12.5K Vectran webbings loaded to 22% ultimate tensile strength. The uniquely designed test facility, hardware, displacement measuring devices, and test data are presented. Test data indicate that immediately after loading all webbings stretch an inch or more, however as time increases displacement values significantly decrease to fall within a range of several hundredth of an inch over the remainder of test period. Webbings in group 1 exhibit near constant displacements and strains over a 17-month period. Data acquisition was suspended after the 17th month, however webbings continue to sustain load without any local webbing damage as of the 21st month of testing. Webbings in group 2 exhibit a combination of initial constant displacement and subsequent increases in displacement rates over a 16-month period. Webbings in group 3 exhibit steady increases in displacement rates leading to webbing failure over a 3-month period. Five of six webbings experienced local damage and subsequent failure in group 3. Data from group 4 indicates increasing webbing displacements over a 7-month period. All webbings in groups 1, 2, and 4 remain suspended without any local damage as of the writing of this paper. Variations in facility temperatures over test period seem to have had limited effect on long-term webbing displacement data.

Kenner, Winfred S.↗
NASA NTRS2012

The Strengths and Limitations of Satellite Data for Evaluating Tropospheric Processes in Chemistry-Climate Models

There is now a wealth of satellite data products available with which to evaluate a model fs simulation of tropospheric composition and other model processes. All of these data products have their strengths and limitations that need to be considered for this purpose. For example, uncertainties are introduced into a data product when 1) converting a slant column to a vertical column and 2) estimating the amount of a total column of a trace gas (e.g., ozone, nitrogen dioxide) that resides in the troposphere. Oftentimes, these uncertainties are not well quantified and the satellite data products are not well evaluated against in situ observations. However, these limitations do not preclude us from using these data products to evaluate our model processes if we understand these strengths and limitations when developing diagnostics. I will show several examples of how satellite data products are being used to evaluate particular model processes with a focus on the strengths and limitations of these data products. In addition, I will introduce the goals of a newly formed team to address issues on the topic of "satellite data for improved model evaluation and process studies" that is established in support of the IGAC/SPARC Global Chemistry ]Climate Modeling and Evaluation Workshop.

Duncan, Bryan↗
NASA NTRS1974

Procedures and results related to the direct determination of gravity anomalies from satellite and terrestrial gravity data

The equations needed for the incorporation of gravity anomalies as unknown parameters in an orbit determination program are described. These equations were implemented in the Geodyn computer program which was used to process optical satellite observations. The arc dependent parameter unknowns, 184 unknown 15 deg and coordinates of 7 tracking stations were considered. Up to 39 arcs (5 to 7 days) involving 10 different satellites, were processed. An anomaly solution from the satellite data and a combination solution with 15 deg terrestrial anomalies were made. The limited data samples indicate that the method works. The 15 deg anomalies from various solutions and the potential coefficients implied by the different solutions are reported.

Rapp, R. H.↗
NASA NTRS2018

Comparisons of Two Spatial Implementations of a Crop Model Using Remotely Sensed Observations over Southeastern United States

Global food security is one of the most pressing issues of the current century, particularly for developing nations. Agricultural simulation models can be a key component in testing new technologies, seeds and cultivars etc. However, inaccurate input information, model related errors and the mode of implementation can also add to model uncertainties. In this study, the crop model is implemented in two separate fashions: a)gridded (GriDSSAT model) and b) using random spatial ensembles (RHEAS model). This is done in the Southeastern US to evaluate and understand the modelperformance over a region data availabilities. Once the model performance is assessed, multiple satellite based earth observation parameters such as soil moisture, vegetation index etc. can be assimilated into crop models to reduce input and model related uncertainties particularly in data limited regions. In this study, the National Agricultural Statistical Services (NASS) reported yield data at county levels are used for comparison andvalidation purposes. The GriDSSAT model estimation of corn yields in comparison with the reported NASS yields showed an overall RMSD of nearly 3720 (kg/ha) whereas RMSD for the RHEAS model implementation was 3550 (kg/ha). Overall the GriDSSAT model had negative bias of nearly 2400 kg/ha (except for 2013) while RHEAS had a slight positive bias of 400 kg/ha (approx.).

SERVIR↗
NASA NTRS1999

Autonomous Science Analyses of Digital Images for Mars Sample Return and Beyond

To adequately explore high priority landing sites, scientists require rovers with greater mobility. Therefore, future Mars missions will involve rovers capable of traversing tens of kilometers (vs. tens of meters traversed by Mars Pathfinder's Sojourner). However, the current process by which scientists interact with a rover does not scale to such distances. A single science objective is achieved through many iterations of a basic command cycle: (1) all data must be transmitted to Earth and analyzed; (2) from this data, new targets are selected and the necessary information from the appropriate instruments are requested; (3) new commands are then uplinked and executed by the spacecraft and (4) the resulting data are returned to Earth, starting the process again. Experience with rover tests on Earth shows that this time intensive process cannot be substantially shortened given the limited data downlink bandwidth and command cycle opportunities of real missions. Sending complete multicolor panoramas at several waypoints, for example, is out of the question for a single downlink opportunity. As a result, long traverses requiring many science command cycles would likely require many weeks, months or even years, perhaps exceeding rover design life or other constraints. Autonomous onboard science analyses can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands, for example acquiring and returning spectra of "interesting" rocks along with the images in which they were detected. Such approaches, coupled with appropriate navigational software, address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing algorithms to enable such intelligent decision making by autonomous spacecraft. Reflecting the ultimate level of ability we aim for, this program has been dubbed the "Grad Student on Mars Project". We envision, for example, an appropriately intelligent Athena-like rover at the Pathfinder landing site might be able to traverse over the ridge towards "Twin Peaks" to obtain better information on the stratigraphy of these "streamlined islands" or of the size, composition and morphology of boulders located on them. Along the traverse, the intelligent rover would collect and analyze images and obtain spectra of geologically interesting features or regions. The intelligent rover might also traverse further up Arcs Vallis, and find additional paleoflood stage indicators such as slackwater deposits. Recognizing additional regions where boulders are imbricated, noting changes in their size, distribution, morphology, composition and the associated changes in channel geometry would yield important information on the outflow channel's paleoflood history, Representative images and associated supporting data from these locations could be downlinked to Earth along with the data requested by scientists from the previous uplink opportunity. Our initial work has focused on recognizing geologically interesting portions of images. Here we summarize some of the algorithms to date.

Gulick, V. C.↗
NASA NTRS1995

Correlation of electron and proton irradiation-induced damage in InP solar cells

When determining the best solar cell technology for a particular space flight mission, accurate prediction of solar cell performance in a space radiation environment is essential. The current methodology used to make such predictions requires extensive experimental data measured under both electron and proton irradiation. Due to the rising cost of accelerators and irradiation facilities, such extensive data sets are expensive to obtain. Moreover, with the rapid development of novel cell designs, the necessary data are often not available. Therefore, a method for predicting cell degradation based on limited data is needed. Such a method has been developed at the Naval Research Laboratory based on damage correlation using 'displacement damage dose' which is the product of the non-ionizing energy loss (NIEL) and the particle fluence. Displacement damage dose is a direct analog of the ionization dose used to correlate the effects of ionizing radiations. In this method, the performance of a solar cell in a complex radiation environment can be predicted from data on a single proton energy and two electron energies, or one proton energy, one electron energy, and Co(exp 60) gammas. This method has been used to accurately predict the extensive data set measured by Anspaugh on GaAs/Ge solar cells under a wide range of electron and proton energies. In this paper, the method is applied to InP solar cells using data measured under 1 MeV electron and 3 MeV proton irradiations, and the calculations are shown to agree well with the measured data. In addition to providing accurate damage predictions, this method also provides a basis for quantitative comparisons of the performance of different cell technologies. The performance of the present InP cells is compared to that published for GaAs/Ge cells. The results show InP to be inherently more resistant to displacement energy deposition than GaAs/Ge.

Walters, Robert J.↗
NASA NTRS2021

SNOOPI: Demonstrating P-Band Reflectometry from Orbit

SigNals Of Opportunity: P-band Investigation (SNOOPI)will be the first on-orbit demonstration of remote sensing using Signals of Opportunity (SoOp) in P-band (240-380 MHz). P-band is needed to penetrate through dense vegetation and into the root zone. The longer wavelength of P-band also increases the unwrapping interval for phase observations. These observations hold the potential for spaceborne remote sensing of root-zone soil moisture (RZSM) and snow water equivalent(SWE), two variables identified as priorities in the 2017-2027 Decadal Survey for Earth Science and Applications from Space. SNOOPI will provide in-space validation of both the P-band SoOp technique and a science instrument prototype. SNOOPI technology validation goals will be met by targeting observations within 9 km of the SMAP calibration/validation sites in the continental United States. A secondary priority is collection of continuous phase data over snow-covered regions. These goals are evaluated under constraints of a limited data budget and mission lifetime, with a launch readiness in early2022. Updates on the development of measurement models and mission planning to support SNOOPI are provided. Aground-based station will be deployed to monitor the non-cooperative sources, in order to reduce risk due to uncertainty in knowledge of the broadcast power, spectrum shape, and orbital position.

J L Garrison↗
NASA NTRS2022

Instrument Science Experiments on the SNOOPI P-Band Reflectometry Mission

SigNals Of Opportunity: P-band Investigation (SNOOPI) will be the first in-space validation of P-band (240–380 MHz) SoOp techniques and a prototype science instrument. These techniques have the potential to enable remote sensing of root-zone soil moisture (RZSM) and snow water equivalent (SWE). SNOOPI technology validation goals will be met by targeting observations within 9 km of the SMAP calibration/validation sites in the continental United States. A second priority is collection of continuous phase data over snow-covered regions. These goals are evaluated under constraints of a limited data budget and mission lifetime, with a launch readiness in August 2022. This presentation will review the instrument science plans aimed at achieving the validation objectives defined for the mission. Mission planning and data processing approaches are described.

Soil Moisture↗
NASA NTRS2015

NASA Propulsion Concept Studies and Risk Reduction Activities for Resource Prospector Lander

The trade study has led to the selection of propulsion concept with the lowest cost and net lowest risk -Government-owned, flight qualified components -Meet mission requirements although the configuration is not optimized. Risk reduction activities have provided an opportunity -Implement design improvements while development with the early-test approach. -Gain knowledge on the operation and identify operation limit -Data to anchor analytical models for future flight designs; The propulsion system cold flow tests series have provided valuable data for future design. -The pressure surge from the system priming and waterhammer within component operation limits. -Enable to optimize the ullage volume to reduce the propellant tank mass; RS-34 hot fire tests have successfully demonstrated of using the engines for the RP mission -No degradation of performance due to extended storage life of the hardware. -Enable to operate the engine for RP flight mission scenarios, outside of the qualification regime. -Provide extended data for the thermal and GNC designs. Significant progress has been made on NASA propulsion concept design and risk reductions for Resource Prospector lander.

Trinh, Huu P.↗
NASA NTRS1978

The light curve at 10 microns of Algol near secondary minimum

Observations of Algol (Beta Persei) at 10 microns are presented which are of relevance to the system's behavior around the time of its secondary minimum. No evidence is found for a significant excess at 10 microns. The data show a smooth decline by 0.3 mag which starts at about phase 0.42, while the limited data obtained at phases greater than 0.50 are consistent with a symmetrical curve about phase 0.50.

Nadeau, D.↗
NASA NTRS1981

A comparative statistical study of long-term agroclimatic conditions affecting the growth of US winter wheat: Distributions of regional monthly average precipitation on the Great Plains and the state of Maryland and the effect of agroclimatic conditions on yield in the state of Kansas

A histogram analysis of average monthly precipitation over 30 and 84 year periods for both Maryland and Kansas was made and the results compared. A second analysis, a statistical assessment of the effect of average monthly precipitation on Kansas winter wheat yield was made. The data sets covered the three periods of 1941-1970, 1887-1970, and 1887-1921. Analyses of the limited data sets used (only the average monthly precipitation and temperature were correlated against yield) indicated that fall precipitation values, especially those of September and October, were more important to winter wheat yield than were spring values, particularly for the period 1941-1970.

Welker, J.↗
NASA NTRS2016

Global Carbon Budget 2016

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere the global carbon budget is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1(sigma), reflecting the current capacity to characterize the annual estimates of each component of the global carbon budget. For the last decade available (2006-2015), EFF was 9.3+/-0.5 GtC/yr, ELUC 1.0+/-0.5 GtC/yr,GATM 4.5+/-0.1 GtC/yr, SOCEAN 2.6+/-0.5 GtC/yr, and SLAND 3.1+/-0.9 GtC/yr. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9+/-0.5 GtC/yr, showing a slowdown in growth of these emissions compared to the average growth of 1.8/yr that took place during 2006-2015.Also, for 2015, ELUC was 1.3+/-0.5 GtC/yr, GATM was 6.3+/-0.2 GtC/yr, SOCEAN was 3.0+/-0.5 GtC/yr, and SLAND was 1.9+/-0.9 GtC/yr. GATM was higher in 2015 compared to the past decade (2006-2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4+/-0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2% (range of -1.0 to +1.8% ) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Nino conditions of 2015-2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565+/-55 GtC (2075+/-205 GtCO2) for 1870-2016, about 75% from EFF and 25% from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set.

Quéré, Corinne Le↗
NASA NTRS2019

Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data

Applications in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on spatial and temporal resolutions of satellite observations. However, there are typically trade-offs between spatial and temporal resolutions in dataset selection. For instance, geostationary weather tracking satellites are designed to take snapshots many times throughout the day but sensor hardware limits data collection. In this work we tackle this limitation, developing a method for temporal upsampling of multi-spectral satellite imagery using optical flow video interpolation deep convolutional neural networks. The presented model, extends Super SloMo (SSM) from single optical flow estimates to multichannel where flows are computed per band. We apply this technique on 8 multi-spectral bands of NOAA/NASA's GOES-16 mesoscale dataset to temporally enhance full disk hemispheric snapshots from 15 minutes to 1 minute. Through extensive experimentation, we show SSM vastly outperforms the linear interpolation baseline and that multichannel optical flows improves performance on GOES-16. A visual analysis of optical flow vectors clearly identifies hurricanes and large-scale atmospheric dynamics. Furthermore, we discuss challenges and open questions related to optical flow and temporal interpolation of multispectral geostationary satellite imagery.

Optical Flow↗
NASA NTRS1992

Tank Pressure Control Experiment/thermal Phenomena (TPCE/TP)

The 'Tank Pressure Control Experiment/Thermal Phenomena (TPCE/TP)' is a reflight of the tank pressure control experiment (TPCE), flown on STS-43 in a standard Get-Away Special (GAS) container in August 1991. The TPCE obtained extensive video and digital data of the jet induced mixing process in a partially filled tank in low gravity environments. It also provided limited data on the thermal processes involved. The primary objective of the reflight of TPCE is to investigate experimentally the phenomena of liquid superheating and pool nucleate boiling at very low heat fluxes in a long duration low gravity environment. The findings of this experiment will be of direct relevance to space based subcritical cryogenic fluid system design and operation. Experiment hardware and results from the first TPCE are described in outline and graphic form.

Hasan, M. M.↗
NASA NTRS1965

Operational Experiences of General Aviation Aircraft

An investigation is currently under way to determine the operational practices and load experiences of general aviation aircraft performing five basic types of operations: twin-engine executive, single-engine executive, personal, instructional, and commercial survey. Limited data obtained to date from aircraft engaged in these operations indicate that aircraft are generally being operated within the limits to which they were designed.

Jewel, Joseph W., Jr.↗
NASA NTRS2017

Data Production on Past and Future NASA Missions

Data return is a metric that is commonly publicized for all space science missions. In the early days of the Space Program, this figure was small, and could be described in bits or maybe even megabits. But now, missions are capable of returning data volumes two or three orders of magnitude larger. For example, Voyager 1 and 2 combined produced a little over 5 Terabits of data in 39 years of operation. In contrast, the Cassini mission, launched two decades after Voyager, produced about one and a half times those data volumes in half the time. NISAR, an Earth Science Mission currently in implementation, plans to produce over 28 Petabits of raw data in just 3 years. This means that NISAR will produce about as many data in 30 days as the combined data production of nearly all planetary missions to date. These increases in capability are a result of technology enhancements in two main areas: telecommunications architecture (both space and ground segments) and data storage technology. This paper describes the progression of these two technologies over the course of more than three decades of space missions and provides additional insight into the design of the end-to-end NISAR Data System Architecture. Trends in the data are briefly explored and compared to Moore’s Law which provides only a qualitative model for memory growth but not for data production. In summary, early missions are found to be driven by unrefined processes while later missions, having utilized earlier lessons learned, focus more on improvements to flight and ground capabilities. Data return seems to fall into three categories. First, deep space missions are driven by the large distances that limit data return to the Earth. Next, the orbiter infrastructure around Mars helps these missions generate more data than other deep space spacecraft. Finally, near-Earth missions have the greatest capabilities for the studied metrics due to their close proximity to Earth and the ground network availability.

Xaypraseuth, Peter↗
NASA NTRS1972

Jupiter radiation belt engineering model

On the basis of earth observations of the HF and UHF radio emission generated near Jupiter, the presence of energetic charged particles trapped in the planet's dipole magnetic field has been inferred. For electrons, energies of the order of 10 MeV and peak fluxes of the order of 10 to the 7th power per square centimeter per second can be derived from the data for equatorial regions about two planetary radii from the dipole. Energetic protons and lower-energy electrons and protons are also expected, but the limited data require that their fluxes be based on theory or earth analogy. Because descriptions available in the literature suggest large associated uncertainties, both nominal and limiting models for the charged-particle populations of Jupiter's belts are derived. These new engineering models describe electron and proton fluxes and their distributions in energy and position in forms suitable as space vehicle design criteria.

Divine, N.↗