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At least 721 records · Page 40

High-resolution Infrared Spectroscopy of Hot Molecular Gas in AFGL 2591 and AFGL 2136: Accretion in the Inner Regions of Disks around Massive Young Stellar Objects

We have performed a high-resolution 4–13 μm spectral survey of the hot molecular gas associated with the massive protostars AFGL 2591 and AFGL 2136, utilizing the Echelon Cross Echelle Spectrograph (EXES) on board the Stratospheric Observatory for Infrared Astronomy, and the iSHELL instrument and Texas EchelonCross Echelle Spectrograph (TEXES) on the NASA Infrared Telescope Facility (IRTF). Here we present the results of this survey with analysis of CO, HCN, C2H2, NH3, and CS, deriving the physical conditions for each species. Also from the IRTF, iSHELL data at 3 μm for AFGL 2591are presented that show HCN and C2H2 in emission. In the EXES and TEXES data, all species are detected in absorption, and temperatures and abundances are found to be high (600 K and 10−6, respectively). Differences of up to an order of magnitude in the abundances of transitions that trace the same ground-state level are measured for HCN and C2H2. The mid-infrared continuum is known to originate in a disk, hence we attribute the infrared absorption to arise in the photosphere of the disk. As absorption lines require an outwardly decreasing temperature gradient, we conclude that the disk is heated in the midplane by viscous heating due to accretion. We attribute the near-IR emission lines to scattering by molecules in the upper layers of the disk photosphere. The absorption lines trace the disk properties at 50 au where high-temperature gasphase chemistry is taking place. Abundances are consistent with chemical models of the inner disk of Herbig disks.

Andrew Barr↗

Robust Metal Additive Manufacturing Process Selection and Development for Aerospace Components

Metal additive manufacturing (AM) is a generic term that captures a variety of fabrication techniques. Each of these manufacturing process has unique advantages, applications for use, and challenges. The most common AM processes in use include Powder Bed Fusion (PBF) and Directed Energy Deposition (DED) as well as many solid state processes. While detailed research has been conducted among many of the processes including parameters and material properties, navigating which processes are best to select is difficult as it is based on component requirements. The focus of this presentation is to provide an overview of considerations for each of metal AM process selection for aerospace components based on various attributes. These attributes include geometric considerations, metallurgical characteristics, cost basis, post-processing and maturity of the processes. The data for these trade selections are based on studies that NASA as performed internally and with academic and industry partners. These studies include multiple AM build experiments to evaluate (1) geometric variations and constraints within the processes, (2) alloy characterization and mechanical testing, (3) pathfinder component development and hotfire evaluations, and (4) certification approaches. This presentation summarizes these results and meant to introduce various considerations when designing a metal AM component.

Additive Manufacturing↗

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods. REFERENCES [1] Open science in space. Nature Medicine, 2021. 27(9): p. 1485-1485. [2] Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. [3] Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5. [4] Whetzel, P.L., et al., BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res, 2011. 39(Web Server issue): p. W541-5.

informatics↗

Limitations in Representation of Physical Processes Prevents Successful Simulation of PM2.5 During KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by -64% but overestimates nitrate by +36%. The largest underestimate in sulfate occurs during the pollution event, where models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 25% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

Katherine R. Travis↗

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗

Evaluating CERES TOA Fluxes using ARISE aircraft observations

Uncertainty in observations of top-of-atmosphere (TOA) radiation fluxes are larger in the Arctic than in other regions. The magnitude of these uncertainties limit our understanding of the Arctic surface energy budget and its variability. The significant uncertainties are due to the low sun angles and wide range of highly reflecting, anisotropic, and highly heterogeneous surface conditions. Therefore, quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with measurements from the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) flow in September 2014. A key objective of ARISE was to evaluate and attribute uncertainty in CERES footprint and gridded TOA radiative fluxes. In this study, we first compare the CERES TOA flux with those obtained from the broadband radiometer measurements from the aircraft using instantaneously matched footprint with the flight track and as the hourly gridded fluxes. This comparison indicates an agreement within uncertainty in the longwave (2 Wm-2 ) for all five grid boxes and agreement in the shortwave (10 Wm-2) for four-out-of-five grid boxes. While not a statistically significant results given the small sample size, the hourly, gridded and the instantaneously matched footprint comparison suggest a -10 Wm-2 bias for CERES in the shortwave. To explore whether this is a robust feature or a statistical artifact, we quantify the individual sources of uncertainty in the differences (temporal and spatial sampling differences, scene evolution, accuracy, angular distribution models, and scene id) to see if any of these differences account for the shortwave bias.

CERES↗

Crucial Role of Thermal Gradients in MMS Fluxgate In-Flight Calibration

To meet the science goals of the Magnetospheric Multiscale (MMS) mission, the Fluxgate Magnetometer (FGM) must measure the ambient magnetic field with an accuracy of 0.1 nT. On a typical MMS orbit, the offsets (or zero levels) of the 3-axis FGM can vary by ~0.5 nT (exclusive of periods in Earth shadow). Previous studies have shown that these variations can be characterized as functions of sensor temperature, TS, and can thus be corrected to within 0.2 nT in the spin plane using in-flight calibration techniques (Bromund, et al., 2016, https://ntrs.nasa.gov/citations/20160014711). In that presentation, we noted two significant observations: A distinct function of TS must be used to characterize offsets during shadow: offsets at a given TScan differ by as much as 2 nT in shadow vs sunlight. Offsets change after maneuvers, without a commensurate change in TS . These changes can be as large as 2 nT. We now note a third, related observation: Offsets increase with proximity to the earth even when TS is constant, resulting in variations of ~0.2 nT at 4-5 Earth radii (RE) These effects are evidence that offsets are a multivariate function of TS and another factor, namely: thermal gradients. Due to the spacecraft spin, the Earth and the Sun each provide a relatively constant thermal input onto one instrument face while the opposite face remains in shadow, thus giving rise to thermal gradients. The thermal gradient depend on the orientation of the spin axis relative to the Earth or Sun. We observe that offsets vary by as much as 0.17 nT/degree as a function of the tilt of the spin axis towards the Sun. Thermal input from the Earth is dominated by Outgoing Longwave Radiation (OLR). Due to the proximity to Earth, the inverse proportion of the distance squared is a significant factor in the thermal gradient attributed to Earth OLR. We find that offsets can be corrected to <0.05 nT accuracy near perigee when accounting for these factors using empirically determined constants of proportionality that account for differences in emissivity of the top and bottom faces of the sensor to OLR (as well as other thermal effects). The changes in offset associated with thermal gradient are of the same order of magnitude as effects that were formerly attributed to sensor temperature alone, and thus both parameters are necessary to characterize the FGM offsets.

Kenneth R Bromund↗

Investigating Stable Oxygen and Carbon Isotopic Variability in Speleothem Records Over the Last Millennium Using Multiple Isotope-Enabled Climate Models

The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISS-E2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

isotope-enabled simulations↗

Mass Balance of the Antarctic Ice Sheet 1992–2016: Reconciling Results from GRACE Gravimetry With ICESat, ERS1/2 and Envisat Altimetry

GRACE and ICESat Antarctic mass-balance differences are resolved utilizing their dependencies on corrections for changes in mass and volume of the same underlying mantle material forced by ice-loading changes. Modeled gravimetry corrections are 5.22 times altimetry corrections over East Antarctica (EA) and 4.51 times over West Antarctica (WA), with inferred mantle densities 4.75 and 4.11 g/cu. cm. Derived sensitivities (Sg, Sa) to bedrock motion enable calculation of motion (δB0) needed to equalize GRACE and ICESat mass changes during 2003–08. For EA, δB0 is −2.2 mm/a subsidence with mass matching at 150 Gt/a, inland WA is −3.5 mm/a at 66 Gt/a, and coastal WA is only −0.35 mm/a at −95 Gt/a. WA subsidence is attributed to low mantle viscosity with faster responses to post-LGM deglaciation and to ice growth during Holocene grounding-line readvance. EA subsidence is attributed to Holocene dynamic thickening. With Antarctic Peninsula loss of −26 Gt/a, the Antarctic total gain is 95 ± 25 Gt/a during 2003–08, compared to 144 ± 61 Gt/a from ERS1/2 during 1992–2001. Beginning in 2009, large increases in coastal WA dynamic losses overcame long-term EA and inland WA gains bringing Antarctica close to balance at −12 ± 64 Gt/a by 2012–16.

Antarctic glaciology↗

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.

domain adaptation↗

Analysis of PICA-NuSil at the Hypersonic Materials Environmental Test System (HyMETS)

Phenolic Impregnated Carbon Ablator (PICA) gained heritage during the stardust mission and is the baseline material for missions to Mars. The phenolic phase of PICA is friable, and therefore the surface is treated with a siloxane resin (NuSil) to mitigate the shedding of particulate matter. Historically, material response models have not accounted for the presence of this coating. Therefore, a test campaign was executed at the Hypersonic Materials Environmental Test System (HyMETS) to investigate the performance of NuSil under multiple heating rates and gas composition. Sphere-cone models were instrumented with thermocouples to measure the in-depth temperature response, and surface temperatures were monitored with a pyrometer. Furthermore, emission spectrometers were used to collect spectra from species emitting at the surface of the test article and the post-shock stagnation region. Post-test analysis suggests that the coating decomposes according to multiple stages. Inspection of silicon emission data reveals a rapid rise and decline in intensity within the first couple of seconds of testing, which is attributed to pyrolysis of NuSil. Pyrolysis is followed by a stagnation in silicon emission and surface temperature which are attributed to the formation of a thin layer of oxidation-resistant silicon oxycarbide. Moreover, the presence of the silicon oxycarbide layer significantly reduces the in-depth thermal response when compared to the baseline material. Eventually, the silicon oxycarbide layer decomposes via high-temperature reactions, which expose the underlying char layer to a highly reactive flow.

PICA-NuSil↗

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods.

knowledge↗

First-results from the Perseverance SHERLOC Investigation: Aqueous Alteration Processes and Implications for Organic Geochemistry in Jezero Crater, Mars

The Perseverance rover landed in Jezero crater, a site selected to fulfill the Mars-2020 mission goals of characterizing the geology of habitable environments and searching for signs of life while collecting samples for return to Earth [1]. Jezero hosted an open-basin lake during the late Noachian/early Hesperian (~3.7 Ga) [1-2], has units associated with the largest carbonate deposit identified on Mars [3-4], and has a well-preserved delta with clay and carbonate-bearing sediments, well-suited to preservation of organics [1,3-4]. Investigating the nature of organics and aqueous environments within their geologic con-text allows us to understand important aqueous processes and determine habitability within Jezero crater. Previous in situ landed measurements of organics could not resolve their spatial and mineralogical con-text [5-6]. Although Martian meteorites lack geological context, the spatial distribution of organic compounds in Martian meteorites have allowed recognition of an association between aqueous processes and organics [7-8]. Here, we show for the first time in-situ associations between carbonate-forming ultramafic alteration process, later stage aqueous sulfate and perchlorate formation, and organics on the Martian surface. Methodology and geological context: We use the Perseverance rover’s SHERLOC instrument (Scanning Habitable Environments with Raman and Lumines-ence of Organics and Chemicals), a deep-ultraviolet fluorescence and Raman scattering spectrometer capable of mapping the organic and mineral composition with a spatial resolution of 100 μm resolution to report the presence of organics and aqueously formed minerals at Jezero crater [9]. These spectral detections were compared with co-located images obtained with the autofocus context imager (ACI) and the WATSON camera for textural analysis [9]. As of writing, the Per-severance rover has abraded five targets that were measured with the SHERLOC instrument. The five targets are located in two different orbitally-identified geological units within the floor of Jezero crater; the Crater Floor Fractured Rough unit (CF-Fr) and the Séítah region within the Crater Floor Fractured 1 unit (CF-F1) [10]. In orbital infrared spectroscopic data, the CF-Fr unit is associated with pyroxene spectral signatures and minor alteration, while the Séítah region is associated with olivine and minor Mg-rich carbonates and clays [3-4,10]. Carbonation of ultramafic protolith recorded within Jezero crater: All scans of abraded targets within the Séítah region reveal strong peaks at 1080–1090 cm−1 consistent with carbonate and peak singlets or doublets at 820–840 cm−1 attributed to olivine (Fig. 1), consistent with orbital infrared observations. Our detailed micron-scale petrographic and spectroscopic evidence shows that these carbonates formed through carbonation of an ultramafic protolith. The supporting observations include: (1) Carbonate cation compositions match those of olivine, suggesting mixed Fe- and Mg-olivine gave rise to mixed Fe- and Mg-carbonates, similar to observations of ultramafic systems on Earth and within Martian meteorites [3-4,7-8]. (2) The ob-served carbonates co-occur with hydrated materials, gypsum, and potentially aqueously-formed phases, amorphous silicates and phosphate. (3) The spectral and textural variation of olivine and carbonate dominated zones and olivine-carbonate mixtures within both primary grains and interstitial zones are expected for carbonated ultramafic protoliths. (4) These mineral associations and textures closely resemble those observed within the ALH84001 and Nakhlite meteorites attributed to olivine carbonation on Mars [6-7]. Taken together, micron-scale SHERLOC documentation of these phenomena bridge previous orbital and meteorite observations and demonstrate in-situ regionally extensive (~106 km2) ultramafic alteration resulting in geo-logical deposition of carbonates. Furthermore, we observe that olivine carbonation was involved in preserving and possibly synthesizing organics, which makes this environment potentially habitable, as previously suggested in [1,3-4] (Fig. 1). Late-stage aqueous perchlorate and sulfate in Jezero crater: An abrasion target within the CF-Fr unit contains combinations of high intensity 950-955 cm−1 peaks and minor 1090-1095 cm−1 and 1150-1155 cm−1 peaks that are spectral fits to anhydrous perchlorate (Fig. 1). Some spectra show a combination of 950-955 cm−1 peaks with equally strong 1010-1020 cm−1 peaks, low intensity broad features at 1120 cm−1, and occasional broad 3450 cm−1 hydration (-OH) features, indicating a mixture of Ca-sulfate and perchlorate that is minimally hydrated (Fig. 1). The detections of per-chlorates within Jezero crater differ from previous measurements (e.g. Phoenix lander, Curiosity rover, Tissint meteorite [7,11]) because they are observed to be intimately related to aqueous processes including sulfate formation, they present as a secondary white void-fill occurring within the interior of the rock, and they are found to likely be Na-perchlorate. implications for their formation: Three different types of organics embedded within three different lithologies were observed within the abraded targets. Organics associated with low intensity ~340 nm fluorescence were widespread within targets with no apparent association to particular minerals (Fig. 1). Organics associated with ~305 nm and ~275 nm fluorescence correlated with sulfates within the Bellegarde target in the CF-Fr unit, while organics associated with high intensity ~340 nm fluorescence correlated with carbonate, phosphate, and amorphous silicate mixtures within the Garde target in the Séítah region (Fig. 1). Although assignment of fluorescence signatures to specific organic compounds is not conclusive, ~340 nm fluorescence is generally more consistent with 2-ring aromatic organics, ~275 nm fluorescence is more consistent with 1-ring aromatic organics, and ~305 nm fluorescence can be created by either 2- or 1-ring aromatics [12]. These observations indicate that the strongest fluorescence signatures interpreted as organics were found in materials associated with aqueous processes, i.e. sulfate- and carbonate-bearing materials, suggesting both brines and ultramafic carbonation aqueous environments were capable of preserving organics on ancient Mars. In Martian meteorites, simple aromatic organics proposed to have been synthesized through aqueous processes can be found within minerals associated with olivine carbonation and in spatial association with perchlorate and sulfate materials [7-8], similar to SHERLOC observations. Hence, we advance an abiotic aqueous synthesis origin for the organics although we cannot rule out the presence of organics from meteoritic in-fall or putative organic biosignatures. Detailed analyses will be required upon return of these materials to Earth.

E L Scheller↗

Metal Additive Manufacturing Process Selection and Development for Propulsion Components

Metal additive manufacturing (AM) is a generic term that captures a variety of fabrication processes. Each of these manufacturing process has unique advantages and challenges for use in aerospace propulsion applications. The most commonly used AM processes include Powder Bed Fusion (PBF), Directed Energy Deposition (DED), and solid-state processes as in Cold Spray, Ultrasonic Additive Manufacturing, and Additive Friction Stir Deposition. While detailed research has been conducted among many of the AM processes to mature processing parameters and material properties, navigating which processes are best to select is difficult as it is based on specific component requirements. The focus of this presentation is to provide an overview of considerations for each of metal AM process selection for aerospace components based on various key attributes. These key attributes include geometric considerations, metallurgical characteristics, cost basis, post-processing and maturity of the processes. The data for these trade selections are based on studies that NASA as performed internally and with academic and industry partners. These studies include multiple AM build experiments to evaluate (1) geometric variations and constraints within the processes, (2) alloy characterization and mechanical testing, (3) pathfinder component development and hot-fire evaluations, and (4) certification approaches. This presentation summarizes these results and is meant to introduce specific examples which show what to consider when designing a metal AM component for aerospace propulsion applications.

Additive Manufacturing↗

Premature Deaths in Africa Due to Particulate Matter Under High and Low Warming Scenarios

Sustainable development and climate change mitigation can provide enormous public health benefits via improved air quality, especially in polluted areas. We use the latest state-of-the-art composition-climate model simulations to contrast human exposure to fine particulate matter in Africa under a “baseline” scenario with high material consumption, population growth, and warming to that projected under a sustainability scenario with lower consumption, population growth, and warming. Evaluating the mortality impacts of these exposures, we find that under the low warming scenario annual premature deaths due to PM2.5 are reduced by roughly 515,000 by 2050 relative to the high warming scenario (100,000, 175,000, 55,000, 140,000, and 45,000 in Northern, West, Central, East, and Southern Africa, respectively). This reduction rises to ∼800,000 by the 2090s, though by that time much of the difference is attributable to the projected differences in population. By contrast, during the first half of the century benefits are driven predominantly by emissions changes. Depending on the region, we find large intermodel spreads of ∼25%–50% in projected future exposures owing to different physics across the ensemble of 6 global models. The spread of projected deaths attributable to exposure to fine particulate matter, including uncertainty in the exposure-response function, are reduced in every region to ∼20%–35% by the non-linear exposure-response function. Differences between the scenarios have an even narrower spread of ∼5%–25% and are highly statistically significant in all regions for all models. These results provide valuable information for policy-makers to consider when working toward climate change mitigation and sustainable development goals.

PM2.5↗

Metal Additive Manufacturing Process Selection and Development Lifecycle for Propulsion Components

Metal additive manufacturing (AM) is a generic term that captures a variety of fabrication processes. Each of these manufacturing process has unique advantages and challenges for use in aerospace propulsion applications. The most commonly used AM processes include Powder Bed Fusion (PBF), Directed Energy Deposition (DED), and solid-state processes as in Cold Spray, Ultrasonic Additive Manufacturing, and Additive Friction Stir Deposition. While detailed research has been conducted among many of the AM processes to mature processing parameters and material properties, navigating which processes are best to select is difficult as it is based on specific component requirements. The focus of this presentation is to provide an overview of considerations for each of metal AM process selection for aerospace components based on various key attributes. These key attributes include geometric considerations, metallurgical characteristics, cost basis, post-processing and maturity of the processes. The data for these trade selections are based on studies that NASA as performed internally and with academic and industry partners. These studies include multiple AM build experiments to evaluate (1) geometric variations and constraints within the processes, (2) alloy characterization and mechanical testing, (3) pathfinder component development and hot-fire evaluations, and (4) certification approaches. This presentation summarizes these results and is meant to introduce specific examples which show what to consider when designing a metal AM component for aerospace propulsion applications.

Paul Gradl↗

Silicon Carbide Sensors and Electronics Technology for Extreme Environments: Opportunities for Nuclear Power Applications

Over the past five decades, NASA Glenn Research Center had been advancing the development of single crystal silicon carbide growth, sensors and electronics device technologies, culminating in the recent demonstration of Micro-Electro-Mechanical Systems scale batch fabricated pressure sensors operating at 800 °C and integrated circuit electronics with demonstrated durability of over 1000 hours at 500 °C. As a result of the progress made in demonstrating the high temperature capability of the technology, insertion into actual operational environments, such as in jet engines and planet Venus, are in progress. The high temperature, near inert surface chemistry, and radiation hardness attributes of SiC, coupled with the relative maturation of the device batch microfabrication, contact metallization, and packaging technologies, make the material a prime candidate for use as part of future advanced nuclear reactor instrumentation and control strategy. Hence the current research efforts at NASA Glenn are aimed toward harnessing these attributes in developing SiC sensors and electronics for nuclear reactor applications, potentially for future Lunar/Martian nuclear power and the emerging terrestrial micro nuclear power plants.

silicon carbide↗

Additional Metadata Guidelines to Improve the Structure and Usability of HDF and NetCDF Files

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global attributes or variables and are popular with the modeling community. HDF and NetCDF files are largely used with remote sensing data and have been used to support measurements from numerous campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. This metadata might be present in another file in the dataset containing the same data using the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) format. Recently, the Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a set of requirements for the HDF and NetCDF files for field studies, aiming to make the data products more interoperable and usable. Particularly, these requirements seek to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. These requirements would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. To be presented are the details of the MACIE requirements as well as examples of the implementation of these requirements for merge files and lidar observation data files.

Sean Leavor↗