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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Evaluation of Extreme Soil Moisture Patterns over the Sahel during the 2020 Growing Season

The African Sahel is an ecologically and climatically sensitive region, and thus is a valuable test case for examination of climate extremes. Above-average rainfall during the 2020 growing season (June-October) led to flooding in the West, Central and East Sahel, with implications for infrastructure, agriculture and disease outbreaks. In this study, we evaluate soil moisture patterns in the region during 2020 to assess and quantify the extremeness of the event. The primary tool is the NASA Soil Moisture Active Passive (SMAP) Level 4 surface soil moisture data. Daily, monthly, and seasonal anomalies are computed relative to SMAP’s long-term mean (2015-2021). Additional comparisons are made with longer-time-series data sets, including surface soil moisture from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2(MERRA-2; 1981-present) and precipitation from the African Rainfall Climatology, Version 2 (ARC2; 1983-present).Possible drivers of the extreme wet event are examined, including potential links to the concurrent 2020-21 La Niña event. Finally, we explore the connections between the extreme soil moisture and vector-borne disease outbreaks in the region in2020, namely, Rift Valley Fever in Mauritania and Chikungunya in Chad.

Soil Moisture↗
NASA NTRS2021

The connection between forest degradation and urban energy demand in sub-Saharan Africa: a characterization based on high-resolution remote sensing data

Charcoal is a key energy source for urban households in sub-Saharan Africa and charcoal production is the main cause of forest degradation across the region. We used multitemporal high-resolution remote sensing optical imagery to quantify the extent and intensity of forest degradation associated with charcoal production and its impact on forest carbon stocks for the main supplying area of an African capital. This analysis documents the advance of forest degradation and quantifies its aboveground biomass removals over a seven-year period, registering that, between 2013 and 2016, the average annual area under charcoal production was 103 sq.km and the annual aboveground biomass removals reached 1081 000 (SD = 2461) Mg. Kiln densities in the study area rose to 2 kilns-ha, with an average of 90.7 Mg ha^(−1) of extracted aboveground biomass. Charcoal production was responsible for the degradation of 55.5% of the mopane woodlands in the study area between 2013 and 2019. We estimated post-disturbance recovery times using an ecosystem model calibrated for the study area. The simulations showed that recovery times could require up to 150 years for current aboveground biomass extraction rates. The results of the remote sensing analysis and the simulations of the ecosystem model corroborate the unsustainability of the present patterns of charcoal production. The detailed characterization of the spatial and temporal patterns of charcoal production was combined with household survey information to quantify the impact of the urban energy demand of the Maputo urban area on forest carbon stocks. The analysis shows that Maputo charcoal demand was responsible for the annual degradation of up to 175.3 sq.km and that the contribution of the study area to this demand fluctuated between 75% and 33% over the study period. The extent, advance pace and distance from urban centers documented in this study support the idea that forest degradation from charcoal production cannot merely be considered a peri-urban process. The intensity of the aboveground biomass (AGB) removals and its contribution to forest carbon stocks changes is significant at the national and regional levels.

F Sedano↗
NASA NTRS2021

A lingering local exopshere created by a gas plume of a lunar lander

We model the expected local exosphere created by outgassing from a lunar lander plume water deposit located adjacent to a lunar lander. We assume the landing is near dawn within Lacus Mortis at 45oN. We consider a set of water desorption scenarios especially focusing on the water-surface desorption activation energy that can possess a distribution of energy states. Our initial simulation starts with a deposition surface having 1020 water molecules per square meter in a 2 km × 2 km region where 90% of the water is retained by weak water-water sorption interactions and 10% are bound by water-regolith sorption interactions. We find that the loosely bound water molecules in water-water interactions quickly desorb within hours after landing. However, water molecules bound to surface sites having a desorption activation greater than 0.7 eV were found to be retained until the source region rotated to later local times (i.e., surface temperature becomes relatively high). We found such time-delayed desorption leads to a tenuous but lingering exosphere emitted from the lander plume deposit region for many 10's of hours after landing. We also adjusted the initial condition by considering different landing local times and considered a case where 100% of the water is bound by water-regolith interactions (mimicking a porous regolith).

W.M. Farrell↗
NASA NTRS2021

The Dark Energy Survey Supernova Programme: Modelling Selection Efficiency and Observed Core-collapse Supernova Contamination

The analysis of current and future cosmological surveys of Type Ia supernovae (SNe Ia) at high redshift depends on the accuratephotometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes anessential step for training and testing photometric classification algorithms, and for correcting biases introduced by selectioneffects and contamination arising from core-collapse SNe in the photometric SN Ia samples. We use published SN time-seriesspectrophotometric templates, rates, luminosity functions, and empirical relationships between SNe and their host galaxies toconstruct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark EnergySurvey (DES) 5-yr photometric SN sample, comparing our simulations of DES with the observed DES transient populations.We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data.We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and beforephotometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation,we find that the predicted contamination varies from 7.2 to 11.7 per cent, with an average of 8.8 per cent and an r.m.s. of 1.1 percent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveyswithout fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmologyanalysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associatedsystematic uncertainty.

M Vincenzi↗
NASA NTRS2021

Simultaneous Multiwavelength Flare Observations of EV Lacertae

We present the first results of our ongoing project conducting simultaneous multiwavelength observations of flares on nearby active M dwarfs. We acquired data of the nearby dM3.5e star EV Lac using five different observatories: NASA's Transiting Exoplanet Survey Satellite (TESS), NASA's Neil Gehrels Swift Observatory (Swift), NASA's Neutron Interior Composition Explorer (NICER), the University of Hawaii 2.2-meter telescope (UH88), and the Las Cumbres Observatory Global Telescope (LCOGT) Network. During the ∼25 days of TESS observations, we acquired three simultaneous UV/X-ray observations using Swift that total ∼18 ks, 21 simultaneous epochs totaling ∼98 ks of X-ray data using NICER, one observation (∼3 hr) with UH88, and one observation (∼3 hr) with LCOGT. We identified 56 flares in the TESS light curve with estimated energies in the range log E(T) (erg) = (30.5–33.2), nine flares in the Swift UVM2 light curve with estimated energies in the range log E(UV) (erg) = (29.3–31.1), 14 flares in the NICER light curve with estimated minimum energies in the range log E(N) (erg) = (30.5–32.3), and 1 flare in the LCOGT light curve with log E(L) (erg) = 31.6. We find that the flare frequency distributions (FFDs) of TESS and NICER flares have comparable slopes, β(T) = −0.67 ± 0.09 and β(N) = − 0.65 ± 0.19, and the FFD of UVOT flares has a shallower slope (β(U) = −0.38 ± 0.13). Furthermore, we do not find conclusive evidence for either the first ionization potential (FIP) or the inverse FIP effect during coronal flares on EV Lac.

Rishi R. Paudel↗
NASA NTRS2022

Solar Wind Ion Sputtering of Sodium from Silicates Using Molecular Dynamics Calculations of Surface Binding Energies

For nearly 40 yr, studies of exosphere formation on airless bodies have been hindered by uncertainties in our understanding of the underlying ion collisional sputtering by the solar wind (SW). These ion impacts on airless bodies play an important role in altering their surface properties and surrounding environment. Much of the collisional sputtering data needed for exosphere studies come from binary collision approximation (BCA) sputtering models. These depend on the surface binding energy (SBE) for the atoms sputtered from the impacted material. However, the SBE is not reliably known for many materials important for planetary science, such as plagioclase feldspars and sodium pyroxenes. BCA models typically approximate the SBE using the cohesive energy for a monoelemental solid. We use molecular dynamics (MD) to provide the first accurate SBE data we are aware of for Na sputtered from the above silicate minerals, which are expected to be important for exospheric formation at Mercury and the Moon. The MD SBE values are ∼8 times larger than the Na monoelemental cohesive energy. This has a significant effect on the predicted SW ion sputtering yield and energy distribution of Na and the formation of the corresponding Na exosphere. We also find that the SBE is correlated with the coordination number of the Na atoms within the substrate and with the cohesive energy of the Na-bearing silicate. Our MD SBE results will enable more accurate BCA predictions for the SW ion sputtering contribution to the Na exosphere of Mercury and the Moon.

Lunar surface↗
NASA NTRS2021

Sputtering of Surfaces by Ion Irradiation: A Comparison of Molecular Dynamics and Binary Collision Approximation Models to Laboratory Measurements

We compare various sputtering simulation methods to experimental results in both the low energy (<1 keV) and high energy (≥1 keV) impact regimes for argon ions impacting a pure copper substrate at normal incidence. Our results indicate that for high energy impacts, both binary collision approximation (BCA) and molecular dynamics methods can be used to generate reasonable predictions for the yield and energy distribution of the sputtered atoms. We also find reasonable agreement between the theoretical and experimental results down to impact energies of 600 eV. However, at 200 eV impact energies, significant discrepancies appear between the experimental and theoretical ejecta energy distributions in the peak position, the width of the energy distribution, and the magnitude of the high energy tail. These discrepancies appear to arise from the experimental results being only for atoms sputtered normal to the substrate surface, whereas the theoretical results are integrated over all 2π solid angles above the surface. Using the BCA code SDTrimSP and limiting the results to only atoms emitted within ±15° of the surface normal brings theory and experiment into reasonable agreement. These results suggest that for low energy impacts, the energy distribution of sputtered atoms is highly dependent on the emission angle of the ejecta.

Solar wind↗
NASA NTRS2021

Volatiles and Refractories in Surface-Bounded Exospheres in the Inner Solar System

Volatiles and refractories represent the two end-members in the volatility range of species in any surface-bounded exosphere. Volatiles include elements that do not interact strongly with the surface, such as neon (detected on the Moon) and helium (detected both on the Moon and at Mercury), but also argon, a noble gas (detected on the Moon) that surprisingly adsorbs at the cold lunar nighttime surface. Refractories include species such as calcium, magnesium, iron, and aluminum, all of which have very strong bonds with the lunar surface and thus need energetic processes to be ejected into the exosphere. Here we focus on the properties of species that have been detected in the exospheres of inner Solar System bodies, specifically the Moon and Mercury, and how they provide important information to understand source and loss processes of these exospheres, as well as their dependence on variations in external drivers.

Moon↗
NASA NTRS2022

Simulating the Diffusion of Hydrogen in Amorphous Silicates: A ‘Jumping’ Migration Process and its Implications for Solar Wind Implanted Lunar Volatiles

We use molecular dynamics (MD) simulations to better explain the movement of atomic hydrogen in amorphous silica and quantify the planetary science implications of these findings. Previous MD simulations had a large range of predicted values and did not agree well with experiment. Our simulations sample atomic motion for a longer duration and consider a wider range of temperatures than previous simulations. In contrast to constant atomic motion, the hydrogen atoms were shown to undergo random intermittent jumps from one oxygen atom to another, the number of which increase with temperature. Predicted diffusion coefficients had a better agreement to experimental values than previous MD simulations, suggesting the importance of longer simulation durations for better statistics. The low activation energy and jumps observed at lunar temperatures do not support the theory of diurnal variations in OH content for an undamaged amorphous silica surface. Instead, we conclude that energetic solar wind impacts can induce two competing atomic hydrogen motion processes in the exposed surface: A prompt effect that induces jumps in the temperature spike volume, but also a long term effect of damage in the structure that traps atomic hydrogen. We then use SDTrimSP to quantify the damage created during exposure and MD to demonstrate the H retention and trapping near these defects. Damage was shown to be dependent on impact energy, with defects easily retaining implanted hydrogen. MD results like those presented herein on unweathered surfaces are therefore most relevant to magnetic anomalies. As a result, we demonstrate the importance of lunar volatile models to account for the damage state of the substrate when modelling hydrogen diffusion, retention, and subsequent OH/water production.

Liam S. Morrissey↗
NASA NTRSDate not supplied

Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning

The microstructure of metals is key to their mechanical properties. The types, density, composition and morphology of crystal defects all have pronounced impact on the properties. Changes to the microstructure occurring during processing and use can be very striking. The emerging technology additive manufacturing (AM) has the potential to improve performance by allowing optimized designs, but the process and environments can lead to unusual microscale features whose properties must be understood and characterized to enable higher technological readiness levels and application. Experimentally, an extensive evaluation of mechanical properties of 3D printed metals is a challenge, and anomalous effects related to the AM process add complexity. We present a new machine learning (ML) model predicting mechanical response based on dislocation mediated plasticity simulations. A large set of 3D discrete dislocation dynamics simulations with wide ranges of loading conditions is transformed to preprocessed data ready for training with the ML model. The trained model can predict the mechanical response of Mo30W for a given microstructure evolution, providing key information essential for optimization of AM processing.

Jaehyun Cho↗
NASA NTRS2022

The Influence of surface binding energy on sputtering in models of the sodium exosphere of Mercury

We have simulated the sodium (Na) exosphere of Mercury to show how the exosphere is affected by the assumed surface binding energy (SBE) of Na in the sputtered component. We constrained ion precipitation onto the surface using distributions for the cusp regions that are consistent with measurements by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging Fast Imaging Plasma Spectrometer instrument. We have simulated sputtering with SBEs of 0.27, 2.6, 4.4, and 7.9 eV, with the lowest value commonly used in exosphere models and the highest from recent molecular dynamics calculations for the Na-bearing feldspar end-member, albite. A gradual change in the exosphere is seen as the yield decreases and the ejecta energy increases with increasing SBE. We describe the corresponding exosphere source functions for ion sputtering (IS), as well as for the previously studied processes of micrometeoroid impact vaporization and photon-stimulated desorption (PSD), along with their release energy distributions and spatial distributions. We have summed the contributions of the various source processes to explain how and when the different sources can be distinguished by observations. The modeled exosphere scale heights range from 72 km for PSD to over 1000 km for IS using a SBE of 7.9 eV. We find that the processes responsible for generating Mercury's Na exosphere are separable by measuring line-of-sight column densities tangent to the planet at various altitudes and positions around the planet. Our initial results are consistent with the Na being sputtered from a high-SBE material such as feldspar, which has been predicted to be abundant on the Mercury's surface.

Rosemary M. Killen↗
NASA NTRSDate not supplied

Refractory Carbides for Hydrogen Erosion Resistance in Carbon Tubes for Nuclear Thermal Propulsion

As crewed travel becomes more common to the Moon and beyond, space nuclear propulsion-based craft offer reduced travel times and double the specific impulse compared to conventional chemical rockets. The nuclear core and its integral hydrogen propellant channels will require advanced refractory carbide coatings over a carbon/carbon substrate for hydrogen resistance. Using ab initio and other computational techniques, we studied select (Zr/Ta/Nb)C mixed carbide systems for erosion resistance and hydrogen diffusion using realistic levels of carbon vacancies and experimentally obtainable stoichiometries. Various contributions to the formation and hydrogen erosion free energies were calculated, including configurational, electronic, and vibrational terms. Our calculations indicate that ZrC is less likely to lose carbon than NbC or TaC, providing an explanation for heritage NERVA data on ZrC and NbC mass loss performance. Additionally, binary mixtures show compositions that are more stable than their end-member counterparts. Hydrogen diffusion in stoichiometric ZrC was found to be slightly higher than previously theorized, with the caveat that hydrogen saturation of carbon vacancies will hinder further hydrogen diffusion through the bulk, while hydrogen diffusion in ZrNbC is slightly enhanced over ZrC. And finally, we show that as carbon is depleted, the deformation mechanism of ZrC changes from brittle to ductile. Though many questions still remain as to the bulk performance of these materials, these trends and results are important in terms of materials selection efforts for hydrogen-resistant coatings on carbon/carbon substrates.

William C Tucker↗
NASA NTRSDate not supplied

Characterization of NU-LHT-4M Lunar Regolith Simulant Using Different Raman Configurations

As much as possible, structures to help sustain a long-term human presence on the moon will be constructed via in-situ resource utilization (ISRU) from lunar regolith. Various processes have been proposed to make lunar regolith-based construction materials, but one complication is that the lunar regolith is relatively complex in terms of composition and can vary quite significantly from one site to another. Some of these methods to make lunar regolith-based construction materials are quite sensitive to the composition and so in-situ methods for evaluating the composition of the lunar regolith could be critical. Various analytical instrumentation has been proposed for in-situ characterization of the composition of regolith on planetary bodies. Raman spectroscopy has been suggested and has some advantages over other in-situ techniques, such as potential for relatively high spatial resolution, direct determination of the mineralogy (while other methods may only infer the mineralogy), nondestructive analysis, relatively simple instrument configurations, and minimal sample preparation/handling. For example, Raman instrumentation has already been deployed in rover-based missions to Mars. Previously, we developed the Standoff Ultracompact Micro-Raman Sensor (SUCR), which is a portable Raman spectroscopy instrument capable to be integrated into a rover or onto a lander. Here, we present work on Raman spectroscopy measurements of NU-LHT-4M lunar simulant using three different Raman instruments with different configurations for collecting Raman data with the goal to explore the effect of these different configurations on the results, especially for use in a lunar environment.

Raman Spectroscopy↗
NASA NTRS2022

Mineral-Catalysed Formation of Marine NO and N 2 O on the Anoxic Early Earth

Microbial denitrification converts fixed nitrogen species into gases in extant oceans. However, it is unclear how such transformations occurred within the early nitrogen cycle of the Archean. Here 5we present experimental anoxic surface-catalyzed reduction of nitrite and nitrate via green rust and magnetite combined with diffusion and photochemical modeling. We find that in a Fe 2+ -rich marine environment, Fe minerals could have catalyzed abiotic denitrification reactions leading to the formation of nitric oxide (NO) and nitrous oxide (N 2 O). Nitrate did not exhibit reactivity in the presence of either mineral or aqueous Fe2+, however, both minerals induced rapid nitrite reduction 10to NO and N 2 O. While N 2 O escaped into the atmosphere (63% of nitrite-nitrogen, with green rust as catalyst), NO remained associated with precipitates (7%) serving as a potential shuttle to the benthic ocean.The modeling suggests that marine N 2 O emissions would have sustained 0.8-6 ppb of atmospheric N 2 O without a protective ozone layer. Our findings add detail to the as yet incompletely documented Archean nitrogen cycle, implying a globally distributed process driven 15by chemical kinetics similar to those of modern enzymatically mediated conversions.

Steffen Buessecker↗
NASA NTRSDate not supplied

Using Coordinated, Multi-Agent Platforms for Dynamic Ocean Worlds Science

Planetary science missions have the opportunity to enhance science return through deployment of autonomous capabilities designed to dynamically respond to new information. Future outer solar system missions to ocean worlds in particular would benefit from this technology - intelligent science payloads (ISP) - because it would allow for a coordinated, near real-time response to ephemeral ‘events’ such as plumes, tectonism, surface implantation, volatile releases, thermal and magnetic anomalies, or radiation, as well as increasing the cadence and coverage of data collection. Prioritization and decision-making frameworks from ISP could be deployed at various scales - from analysis onboard a spacecraft with multiple instruments – to coordinated analyses among separate spacecraft in an e.g., distributed systems mission (DSM) composed of multiple SmallSats. Goddard’s Intelligent Science Payload team is developing an agile autonomous architecture for an icy ocean worlds DSM concept. Our goals are to coordinate data collection and onboard data analysis, and to make autonomous decisions for new data collection and analysis based on science priorities between multiple spacecraft with variable instrumentation and orbits. We use a range of data analysis tools to coordinate the DSM response, spanning from observations of data over a specified threshold to more computationally intensive machine learning algorithms (ML). ML algorithms here currently focus on determining the composition of an ocean world using mass spectrometry, and specifically methods for understanding ‘novelties’ and potential biosignatures. These algorithms could be used to quickly process and analyze onboard data that would be significantly delayed in downlink due to long communication delays for outer solar system missions in order to make dynamic science observations. Our ocean worlds case study ISP architecture is intended as an ‘agile’ and modular framework that could be used as a whole or as particular modules based on mission needs.

Distributed Systems↗
NASA NTRS2023

Ad Hawk Aerial Connectivity Network

Wildfires in the United States have been increasing significantly in both frequency and size in recent decades, requiring maximal efficiency on the part of wildfire management organizations. However, while the methodology and technology to combat wildfires has improved, theconnectivityinfrastructure in more ruralregionsof the country is either incompatible with newertechnology or altogether non-existent. Due to this, many modern communication methods are rendered uselessin areas where connection is needed most, complicating the overall fire management procedure. To improve communication and logistics between responders on the front lines and headquarters, a team of NASA researchassociateshas developed the schematic for a rapidly deployable mobile ad-hoc internet-enabled Wi-Fi network that can bring stable internet accessto any desired area.

Wi-Fi↗