Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Randomly sampled sites”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

HfNb_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys hafnium-niobium (Hf-Nb). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Hf and Nb. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect BCC lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,029 randomized atomic structures over 31 chemical compositions. Further methodological and structural information is contained in the dataset README.txt file.

36 MATERIALS SCIENCE↗
DOE OSTI2024

VZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys vanadium-zirconium (V-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements V and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling neutral defects in III-V ternary alloys with a special quasirandom structure: Analysis of As- and III-site point defects in InGaAs

While first-principles density functional theory modeling has become a vital tool to investigate defect properties in semiconductors, the lack of crystalline periodicity in pseudobinary random composition alloys, such as In 1−𝑥 ⁢Ga 𝑥 ⁢As, complicates such analyses. We present a simulation strategy to systematically take into account the variability in the local defect environment in order to predict statistical properties of neutral intrinsic defects in In 1−𝑥⁢ Ga 𝑥 ⁢As. We use a comprehensive sampling from a modest-sized 64-atom special quasirandom structure (SQS) to define a statistically representative set of defects, and use a 512-atom hypercell, a 2 × 2 × 2 supercell of SQS supercells, to achieve cell-size convergence. We articulate an equivalent site principle and describe how it constrains atomic chemical reference energies in computation of defect formation energies in pseudobinary alloys. A simple protocol for estimating reference energies for the Ga and In atoms sharing the III site succeeds in obtaining the equivalence of defects at Ga-sites and In sites in the SQS supercell, (<30 meV differences in average formation energies). For III-site defects, such as the As antisite As III , the statistical variability in formation energies is modest, ≈ 0.1–0.2 eV. The variability in formation energy at As-site defects, such as the As vacancy 𝑣 As , can be much larger, >1 eV. The As antisite is shown to be a low-energy defect and the most likely to be present in as-grown materials, just as in GaAs. All other defects are higher-energy defects unlikely to be important in native material, but potentially important in radiation-damaged material. With a strong variability in defect energies, especially on the As-site, explicit consideration of statistical variability due to compositional randomness will be imperative for meaningful and quantitative comparisons to experiment.

Density functional theory↗
DOE OSTI2022

Estimating epistemic uncertainty in soil parameters for nonlinear site response analyses: Introducing the Latin Hypercube Sampling technique

This study quantifies the effects of epistemic uncertainty in soil parameters on nonlinear (NL) site response analysis (SRA) results, validated against the data recorded at a well-instrumented geotechnical downhole array located in Japan. To this end, a one-dimensional soil column model of the Service Hall Array (SHA) near the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) is developed using the finite element (FE) program LS-DYNA. The dynamic stress–strain relationship is characterized by a modified two-stage hyperbolic (MTH) NL backbone curve formulation capable of capturing soil behavior at both small- and large-shear strains. The model is then validated against the ground motion recordings to capture the model bias. The uncertainties associated with the shear-wave velocity profile (a small-strain soil property) and soil shear strength (a large-strain soil property) are incorporated in NL SRA to quantify their separate and joint randomization effects on the results. This study proposes using the Latin Hypercube Sampling (LHS) method as an efficient alternative to commonly used methods, such as Standard Monte Carlo (SMC), to account for uncertainty propagation in such reliability analysis. Both low-intensity and design-level records from the recordings at the SHA are applied to study the contribution of the small- and large-strain NL dynamic soil properties. Results from 46,200 NL FE analyses (23,100 per input motion) are presented. Measured and predicted site response, using recorded ground motions at this downhole array, is compared to assess the significance of soil parameter uncertainty on the observed ground motion dispersions. It is demonstrated that increasing the number of soft realizations and implementing higher level earthquake intensity lead to higher ground motion dispersion. Unlike past studies in randomization of Vs profiles with the SMC method, the LHS method is shown to have no significant effect on the predicted median surface response spectra and amplification factors (AFs) for this case study.

Engineering↗
NASA NTRS1985

A spring window for geobotanical anomaly detection

The observation of senescence of deciduous vegetation to detect soil heavy metal mineralization is discussed. A gridded sampling of two sites of Quercus alba L. in south-central Virginia in 1982 is studied. The data reveal that smaller leaf blade lengths are observed in the soil site with copper, lead, and zinc concentrations. A random study in 1983 of red and white Q. rubra L., Q. prinus L., and Acer rubrum L., to confirm previous results is described. The observations of blade length and bud breaks show a 7-10 day lag in growth in the mineral site for the oak trees; however, the maple trees are not influenced by the minerals.

Bell, R.↗
DOE OSTI2023

Estimation of hydraulic conductivity in a watershed using sparse multi-source data via Gaussian process regression and Bayesian experimental design

Enhanced water management systems depend on accurate estimation of subsurface hydraulic properties. However, geologic formations can vary significantly, so information from a single source (e.g., widely spaced boreholes) is insufficient in characterizing subsurface aquifer properties. Therefore, multiple sources of information are needed to complement the hydrogeology understanding of a region. Here, this study presents a numerical framework in which information from different measurement sources is combined to characterize the 3D random field in a multi-fidelity prediction model. Coupled with the model, a Bayesian experimental design was used to determine the best future sampling locations. The Upper Sangamon watershed in east-central Illinois was selected as the case study site, where the multi-fidelity Gaussian process model was used to estimate the hydraulic conductivity in the region of interest. Multi-source observation data were obtained from electrical resistivity and borehole pumping tests. The accuracy of the model prediction is dependent on the locations and the distribution of both high- and low-fidelity data. Furthermore, the multi-fidelity model was compared with the single-fidelity model. The uncertainties and confidence in the measurements and parameter estimates were quantified and used to design future cycles of data collection to further improve the confidence intervals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2020

Site-wide occupancy assessment using camera traps for seven mammalian species at Los Alamos National Laboratory

Los Alamos National Laboratory (LANL or Laboratory) is committed to solving national security challenges through scientific excellence and has been serving the nation and northern New Mexico for over 70 years. Being located on the Pajarito Plateau in the eastern flanks of the Jemez Mountains, the Laboratory is surrounded by a rich diversity of plants and animals. It is common to see many different species of wildlife on Laboratory property; however, sometimes interactions with wildlife can be negative. Vehicle accidents with wildlife have become a common occurrence. With the current and ongoing expansion of the Laboratory on the Pajarito Plateau, it has the potential to further impact wildlife movement including large game species. Local agencies and tribal Pueblos rely on large game species and do not want these species to be restricted from moving across property boundaries. Temporal and spatial aspects of where wildlife occur on the site is a phenomena that is either not well understood in uncommon species or needs periodic reevaluation for common species. Estimating the distribution of multiple species across the landscape provides wildlife biologists with crucial information for monitoring and conserving animal populations in a particular area. Utilizing motion activated wildlife cameras, also known as camera traps, to monitor wildlife populations has become an essential tool for biologists. Camera traps are non-invasive and cost-effective and can document multiple elusive or uncommon wildlife species, such as carnivores, simultaneously. Occupancy modeling provides a flexible framework for the analysis of the distribution for multiple wildlife species. It explicitly recognizes whether a species is spatially common or rare (occupancy = ψ) and if that species is easy or hard to detect (detection probability = p ). Multispecies and multi-season occupancy models can detect trends in species occupancy because individual species may vary in seasonal movements, detection probability, and transition rates between habitats. In this study, we assessed the site as a whole to ascertain when and where medium and large mammal species are present. Understanding wildlife patterns at the Laboratory will better inform future management decisions regarding land use and development strategies. We placed motion activated wildlife cameras in a random systematic sampling design and used these data to create occupancy models. We tested for differences in single-species occupancy and detection probability by season of mammal species captured on 20 camera traps placed across the Laboratory in a 40 mi² (103 km²) area. We focus the interpretation of our findings on seven mammal species found during this study. They are Rocky Mountain elk ( Cervus canadensis nelsoni ; hereafter “elk”), mule deer ( Odocoileus hemionus ; hereafter “deer”), mountain lion ( Puma concolor ; hereafter “lion”), American black bear ( Ursus americanus ; hereafter “bear”), coyote ( Canis latrans ), bobcat ( Lynx rufus ), and gray fox ( Urocyon cinereoargenteus ; hereafter “fox”).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1988

Static magnetic ordering of CeCu2.1Si2 found by muon spin relaxation

Zero- and longitudinal-field muon spin relaxation measurements on a polycrystal sample of a heavy fermion superconductor CeCu2.1 Si2 (T(c) = 0.7 K) have revealed an onset of static magnetic ordering below T approximately 0.8 K. The line shapes of the observed spectra in zero field indicate a wide distribution of static random local fields at muon sites, suggesting that the ordering is either spin glass or incommensurate spin-density-wave state. The observed width of the random local field at T = 0.05 K corresponds to a small averaged static moment of the order of 0.1 micro-B per formula unit.

Uemura, Y. J.↗
DOE OSTI2024

Elemental profiling and genomewide association studies reveal genomic variants modulating ionomic composition in Populus trichocarpa leaves

Samples were collected from a population of 1,089 black cottonwood genotypes (P. trichocarpa) assembled from native stands to encompass the central portion of the natural range of the species, stretching from 38.8° to 54.3° N Q13 latitude from California, USA, to British Columbia, Canada. Establishment of the common garden, growth conditions, and site maintenance have been described by Muchero et al (2015). In this study, leaf samples for ionomic profiling were collected from 4-year-old trees, during the growing season, in July 2012, from a field located in Clatskanie, Oregon, USA (46°6′11″N 123°12′13″W). The field site was located in a protected alluvial floodplain containing a uniform Wauna-Locoda silt loam soil area characterized by an acidic pH, in Columbia County, Oregon. A subset of 584 out of the 1,089 P. trichocarpa genotypes were represented in this sampling. These genotypes were randomly selected to represent the geographical distribution of the population. A single fully mature (LPI 7-9) leaf on the south side of the tree exposed to full sunlight conditions was removed from the tree within a 6-hour window centering on solar noon and immediately frozen under dry ice before processing. Leaf samples of 584 P. trichocarpa genotypes were finely ground to 40 mm particle size using a mortar and pestle, and ionomic composition was analyzed using ICP-MS. In total, 20 elements were profiled, including aluminum (Al27), arsenic (As75), boron (B11), cadmium (Cd111), calcium (Ca43), cobalt (Co), copper (Cu), iron (Fe57), magnesium (Mg25), manganese (Mn55), molybdenum (Mo), nickel (Ni60), phosphorus (P31), potassium (K39), rubidium (Rb85), selenium (Se82), sodium (Na23), strontium (Sr88), sulfur (S34), and zinc (Zn66), following a protocol established by Ziegler et al. (2013). For each sample, 75mg of powder was digested overnight in 2.5 mL HNO3 containing 20 parts per billion (ppb) indium as an internal standard, following the protocol described in Ziegler et al. (2013). Following a dilution, concentration of the 20 elements was measured using an Elan 6000 DRC-e mass spectrometer (Perkin-Elmer SCIEX) connected to a PFA microflow nebulizer (Elemental Scientific) and Apex HF desolvator (Elemental Scientific). One measurement per sample per genotype was done. For subsequent analyses, the quantifications were converted to total element concentration.

CBI ionomics, GWAS, plasma-mass spectrometry, neut↗
NASA NTRS1999

Lunar Meteorites and Implications for Compositional Remote Sensing of the Lunar Surface

Lunar meteorites (LMs) are rocks found on Earth that were ejected from the Moon by impact of an asteroidal meteoroid. Three factors make the LMs important to remote-sensing studies: (1) Most are breccias composed of regolith or fragmental material; (2) all are rocks that resided (or breccias composed of material that resided) in the upper few meters of the Moon prior to launch and (3) most apparently come from areas distant from the Apollo sites. How Many Lunar Locations? At this writing (June 1999), there are 18 known lunar meteorite specimens. When unambiguous cases of terrestrial pairing are considered, the number of actual LMs reduces to 13. (Terrestrial pairing is when a single piece of lunar rock entered Earth's atmosphere, but multiple fragments were produced because the meteoroid broke apart on entry, upon hitting the ground or ice, or while being transported through the ice.) We have no reason to believe that LMs preferentially derive from any specific region(s) of the Moon; i.e., we believe that they are samples from random locations. However, we do not know how many different locations are represented by the LMs; mathematically, it could be as few as 1 or as many as 13. The actual maximum is < 13 because in some cases a single impact appears to have yielded more than one LM. Yamato 793169 and Asuka 881757 are considered "source-crater paired" or "launch paired" because they are compositionally and petrographically similar to each other and distinct from the others, and both have similar cosmic-ray exposure (CRE) histories. The same can be said of QUE 94281 and Y 793274. Thus the 13 meteorites probably represent a maximum of 11 locations on the Moon. The minimum number of likely source craters is debated and in flux as new data for different isotopic systems are obtained. Conservatively, considering CRE data only, a minimum of about 5 impacts is required. Compositional and petrographic data offer only probabilistic constraints. An extreme, but not unreasonable viewpoint, is that such data offer no constraint. For example, if one were to cut up the Apollo 17 landing site (which was selected for its diversity) into softball-sized pieces, some of those pieces (e.g., sample 70135) would be crystalline mare basalts like Y 793169 whereas others (e.g., sample 73131 would be feldspathic regolith breccias like MAC 88104/ 88105. However, nature is not so devious. Warren argues that LMs come from craters of only a few kilometers in diameter. If so, even though CRE data allow, for example, that ALHA 81005 and Y 791197) were launched simultaneously from the same crater, the probability is nevertheless low because the two meteorites are compositionally and mineralogically distinct. Thus, within the allowed range (5-11) for the number of locations represented by the LMs, values at the high end of the range are probably more likely. Mare Meteorites: Three LMs consist almost entirely of mare basalt. Two, Y 793169 and Asuka 881757, are unbrecciated, low-Ti, crystalline rocks that are compositionally and mineralogically similar (but not identical) to each other; they probably derive from a single lunar-mare location. The third, EET 87521/96008, is a fragmental breccia consisting predominantly of VLT mare basalt. Thus, these LMs probably represent only two lunar mare locations. The basaltic LMs have mineral and bulk compositions distinct from Apollo mare basalts. The petrography of Calcalong Creek has not been described in detail, but compositionally it is unique in that it corresponds to a mixture (breccia) of about one-half feldspathic material (i.e., the mean composition of the feldspathic lunar meteorites, below), one-fourth KREEP norite, one-fourth VLT mare basalt (like EET 87521), and 1% CI chondrite. With 4 micro g/g Th and correspondingly high concentrations of other incompatible elements, it is the only lunar meteorite that is likely to have come from within the Procellarum KREEP Terrane (PKT). Yamato 793274 and QUE 94281 are together distinct in being fragmental breccias containing subequal parts of feldspathic highland material and VLT mare basalt. Jolliff et al. estimate a mare to highland ratio of 54:46 for QUE 94281 and 62:38 for Y 793274; this difference is well within the range observed for soils collected only centimeters apart (in cores) at interface site like Apollo 15 and 17 [11]. Although the two meteorites were found on opposite sides of Antarctica, they are probably launch-paired. The strongest evidence is that the pyroclastic glass spherules that occur in both are of two compositional groups and the two groups are essentially the same in both meteorites. Yamato 791197 is nominally a feldspathic lunar meteorite (below), but among FLMs, it probably contains the highest abundance of clasts and glasses of mare derivation. As a consequence, its composition is at the high-Fe, low-Mg end of the range for FLMs and is not included in the FLM average of Table 1. Its composition is consistent with about 10% mare-derived material. Similarly, the two small (Y 82) pieces of Y 82192/82193186032 are more mafic than the large (Y 86) piece, probably as a result of about 7% mare-derived material. All Apollo missions went to areas in or near the PKT, and, consequently, all Apollo regolith samples are contaminated with Th-rich material from the PKT. At the nominally "typical" highland site, Apollo 16, about 30% of the regolith (<1-mm fines) is Th-rich ejecta from the Imbrium impact and about 6% is mare material probably derived from mare basins. Thus Apollo 16 regolith is not typical of the highlands. Among Apollo rocks, the compositions of the FLMs correspond most closely to the feldspathic granulitic breccias of Apollo 16 and 17. (Additional information is contained in original)

Korotev, R. L.↗
DOE OSTI2026

Data and scripts associated with “Non-random processes impacting organic matter chemistry are maximized in mid-order streams”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Pulling Marbles from a Bag: Deducing the Regional Impact History of the SPA Basin from Impact Melt Rocks

The South Pole-Aitken (SPA) basin is an important target for absolute age-dating. Vertical and lateral impact mixing ensures that regolith within SPA will contain rock fragments from SPA itself, local impact craters, and faraway giant basins. About 20% of the regolith at any given site is foreign [1, 2], but much of this material will be cold ejecta, not impact melt. We calculated the fraction of contributed impact melt using scaling laws to estimate the amount and provenance of impact melt, demonstrating that SPA melt is the dominant impact melt rock (>70%) likely to be present. We also constructed a statistical model to illustrate how many randomly-selected impact-melt fragments would need to be dated, and with what accuracy, to confidently reproduce the impact history of a site. A detailed impact history becomes recognizable after a few hundred to a thousand randomly-selected marbles, however, it will be useful to have more information (e.g. compositional, mineralogical, remote sensing) to group fragments. These exercises show that SPA melt has a high probability of being present in a scoop sample and that dating of a few hundred to a thousand impact-melt fragments will yield the impact history of the SPA basin.

Cohen, Barbara A.↗
NASA NTRS2020

Forest Potential Productivity Mapping by Linking Remote-Sensing-Derived Metrics to Site Variables

A fine-resolution region-wide map of forest site productivity is an essential need for effective large-scale forestry planning and management. In this study, we incorporated Sentinel-2 satellite data into an increment-based measure of forest productivity (biomass growth index (BGI)) derived from climate, lithology, soils, and topographic metrics to map improved BGI (iBGI) in parts of North American Acadian regions. Initially, several Sentinel-2 variables including nine single spectral bands and 12 spectral vegetation indices (SVIs) were used in combination with forest management variables to predict tree volume/ha and height using Random Forest. The results showed a 10–12 % increase in out of bag (OOB) r2when Sentinel-2 variables were included in the prediction of both volume and height together with BGI. Later, selected Sentinel-2 variables were used for biomass growth prediction in Maine, USA and New Brunswick, Canada using data from 7738 provincial permanent sample plots. The Sentinel-2 red-edge position (S2REP) index was identified as the most important variable over others to have known influence on site productivity. While a slight improvement in the iBGI accuracy occurred compared to the base BGI model (~2%), substantial changes to coefficients of other variables were evident and some site variables became less important when S2REP was included.

site productivity↗
DOE OSTI2021

Magnetism in Mixed Valence, Defect, Cubic Perovskites: BaIn 1– x Fe x O 2.5+δ , x = 0.25, 0.50, and 0.75. Local and Average Structures

The series BaIn 1–x Fe x O 2.5+δ , x = 0.25, 0.50, and 0.75, has been prepared under air-fired and argon-fired conditions and studied using X-ray diffraction, d.c. and a.c. susceptibility, Mössbauer spectroscopy, neutron diffraction, X-ray near edge absorption spectroscopy (XANES), and X-ray pair distribution (PDF) methods. While Ba 2 In 2 O 5 (BaInO 2.5 ) crystallizes in an ordered brownmillerite structure, Ibm2, and Ba 2 Fe 2 O 5 (BaFeO 2.5 ) crystallizes in a complex monoclinic structure, P2 1 /c, showing seven Fe 3+ sites with tetrahedral, square planar, and octahedral environments, all phases studied here crystallize in the cubic perovskite structure, Pm$\bar{}3}$m, with long-range disorder on the small cation and oxygen sites. 57 Fe Mössbauer studies indicate a mixed valency, Fe 4+ /Fe 3+ , for both the air-fired and argon-fired samples. The increased Fe 3+ content for the argon-fired samples is reflected in increased cubic cell constants and in the increased Mössbauer fraction. It appears that the Pm$\bar{}3}$m phases are only metastable when fired in argon. From a slightly modified percolation theory for a primitive cubic lattice (taking into account the presence of random O atom vacancies), long-range spin order is permitted for the x = 0.50 and 0.75 phases. Instead, the d.c. susceptibility shows only zero-field-cooled (ZFC) and field-cooled (FC) divergences at ~6 K [5 K] for x = 0.50 and at ~22 K [21 K] for x = 0.75, with values for the argon-fired samples in [ ]. Neutron diffraction data for the air-fired samples confirm the absence of long-range magnetic order at any studied temperature. For the air-fired x = 0.50, a.c. susceptibility data show a frequency-dependent χ'(max) and spin glass behavior, while for x = 0.75, χ'(max) is invariant with frequency, ruling out either a spin glass or a superparamagnetic ground state. These behaviors are discussed in terms of competing Fe 3+ –Fe 3+ antiferromagnetic exchange and ferromagnetic Fe 3+ –Fe 4+ exchange. The PDF and 57 Fe Mössbauer data indicate a local structure at short interatomic distances, which deviates strongly from the average Pm$\bar{}3}$m model. Fe Mössbauer, PDF, and XANES data show a systematic dependence on x and indicate that the Fe 3+ sites are largely fourfold-coordinated and Fe 4+ sites are fivefold- or sixfold-coordinated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Chromosome Aberrations in Human Epithelial Cells Exposed Los Alamos High-Energy Secondary Neutrons: M-BAND Analysis

High-energy secondary neutrons, produced by the interaction of galactic cosmic rays (GCR) with the atmosphere, spacecraft structure and planetary surfaces, contribute a significant fraction to the dose equivalent radiation measurement in crew members and passengers of commercial aviation travel as well as astronauts in space missions. The Los Alamos Nuclear Science Center (LANSCE) neutron facility's 30L beam line (4FP30L-A/ICE House) is known to generate neutrons that simulate the secondary neutron spectrum of the Earth's atmosphere at high altitude. The neutron spectrum is also similar to that measured onboard spacecrafts like the MIR and the International Space Station (ISS). To evaluate the biological damage, we exposed human epithelial cells in vitro to the LANSCE neutron beams with an entrance dose rate of 2.5 cGy/hr, and studied the induction of chromosome aberrations that were identified with multicolor-banding in situ hybridization (mBAND) technique. With this technique, individually painted chromosomal bands on one chromosome allowed the identification of inter-chromosomal aberrations (translocation to unpainted chromosomes) and intra-chromosomal aberrations (inversions and deletions within a single painted chromosome). Compared to our previous results with gamma-rays and 600 MeV/nucleon Fe ions of high dose rate at NSRL (NASA Space Radiation Laboratory at Brookhaven National Laboratory), the neutron data from the LANSCE experiments showed significantly higher frequency of chromosome aberrations. However, detailed analysis of the inversion type revealed that all of the three radiation types in the study induced a low incidence of simple inversions. Most of the inversions in gamma-ray irradiated samples were accompanied by other types of intrachromosomal aberrations but few inversions were accompanied by interchromosomal aberrations. In contrast, neutrons and Fe ions induced a significant fraction of inversions that involved complex rearrangements of both inter- and intrachromosome exchanges. The distribution of damage sites on chromosome 3 was also compared for different radiation types. The breakpoints were randomly localized on chromosome 3 with neutrons and Fe ions exposure, whereas non-random distribution with clustering breakpoints was observed with gamma-rays exposure. The specific fingerprint of neutron radiations on chromosomal aberrations will be discussed.

Hada, M.↗
NASA NTRS2022

Desert Locust Cropland Damage Differentiated from Drought, with Multi-Source Remote Sensing in Ethiopia

In 2020, Ethiopia had the worst desert locust outbreak in 25 years, leading to food insecurity. Locust research has typically focused on predicting the paths and breeding grounds based on ground surveys and remote sensing of outbreak factors. In this study, we hypothesized that it is possible to detect desert locust cropland damage through the analysis of fine-scale (5–10 m) resolution satellite remote sensing datasets. We performed our analysis on 121 swarm point locations on croplands derived from the Food and Agriculture Organization (FAO) of the United Nations, and 94 ‘non-affected’ random cropland sample points generated for this study that are distributed within 20–25 km from the ‘center’ of swarm affected sample locations. Integrated Drought Condition Indices (IDCIs) and Vegetation Health Indices (VHIs) calculated for the affected sample locations for 2000–2020 were strongly correlated (R(exp 2) > 0.90) with that of the corresponding non-affected group of sample sites. Drought indices were strongly correlated with the evaluation Standardized Precipitation Evapotranspiration Indices (SPEIs) and showed that 2020 was the wettest year since 2000. In 2020, the NDVI and backscatter coefficient of cropland phenologies from the affected versus non-affected cropland sample sites showed a slightly wider, but significant gap in March (short growing season) and August-October (long growing season). Thus, slightly wider gaps in cropland phenologies between the affected and non-affected sites were likely induced from the locust damage, not drought, with fine scale data representing a larger gap.

Desert locust↗
DOE OSTI2022

Correcting for filter-based aerosol light absorption biases at the Atmospheric Radiation Measurement program's Southern Great Plains site using photoacoustic measurements and machine learning

Abstract. Measurement of light absorption of solar radiation by aerosols is vital for assessing direct aerosol radiative forcing, which affects local and global climate. Low-cost and easy-to-operate filter-based instruments, such as the Particle Soot Absorption Photometer (PSAP), that collect aerosols on a filter and measure light attenuation through the filter are widely used to infer aerosol light absorption. However, filter-based absorption measurements are subject to artifacts that are difficult to quantify. These artifacts are associated with the presence of the filter medium and the complex interactions between the filter fibers and accumulated aerosols. Various correction algorithms have been introduced to correct for the filter-based absorption coefficient measurements toward predicting the particle-phase absorption coefficient (Babs). However, the inability of these algorithms to incorporate into their formulations the complex matrix of influencing parameters such as particle asymmetry parameter, particle size, and particle penetration depth results in prediction of particle-phase absorption coefficients with relatively low accuracy. The analytical forms of corrections also suffer from a lack of universal applicability: different corrections are required for rural and urban sites across the world. In this study, we analyzed and compared 3 months of high-time-resolution ambient aerosol absorption data collected synchronously using a three-wavelength photoacoustic absorption spectrometer (PASS) and PSAP. Both instruments were operated on the same sampling inlet at the Department of Energy's Atmospheric Radiation Measurement program's Southern Great Plains (SGP) user facility in Oklahoma. We implemented the two most commonly used analytical correction algorithms, namely, Virkkula (2010) and the average of Virkkula (2010) and Ogren (2010)–Bond et al. (1999) as well as a random forest regression (RFR) machine learning algorithm to predict Babs values from the PSAP's filter-based measurements. The predicted Babs was compared against the reference Babs measured by the PASS. The RFR algorithm performed the best by yielding the lowest root mean square error of prediction. The algorithm was trained using input datasets from the PSAP (transmission and uncorrected absorption coefficient), a co-located nephelometer (scattering coefficients), and the Aerosol Chemical Speciation Monitor (mass concentration of non-refractory aerosol particles). A revised form of the Virkkula (2010) algorithm suitable for the SGP site has been proposed; however, its performance yields approximately 2-fold errors when compared to the RFR algorithm. To generalize the accuracy and applicability of our proposed RFR algorithm, we trained and tested it on a dataset of laboratory measurements of combustion aerosols. Input variables to the algorithm included the aerosol number size distribution from the Scanning Mobility Particle Sizer, absorption coefficients from the filter-based Tricolor Absorption Photometer, and scattering coefficients from a multiwavelength nephelometer. The RFR algorithm predicted Babs values within 5 % of the reference Babs measured by the multiwavelength PASS during the laboratory experiments. Thus, we show that machine learning approaches offer a promising path to correct for biases in long-term filter-based absorption datasets and accurately quantify their variability and trends needed for robust radiative forcing determination.

54 ENVIRONMENTAL SCIENCES↗