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

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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Variation of Ionizing Continuum: The Main Driver of Broad Absorption Line Variability

We present a statistical analysis of the variability of broad absorption lines (BALs) in quasars using the large multi-epoch spectroscopic data set of the Sloan Digital Sky Survey Data Release 12 (SDSS DR12). We divide the sample into two groups according to the pattern of the variation of C iv BAL with respect to that of a continuum: the equivalent widths (EW) of the BAL decreases (increases) when the continuum brightens (dims) as group T1; and the variation of the EW and the continuum in the opposite relation of group T2. We find that T2 has significantly (P{sub T}<10{sup −6}, Students T Test) higher EW ratios (R) of Si iv to C iv BAL than T1. Our result agrees with the prediction of photoionization models that C{sup +3} column density increases (decreases) if there is a (or no) C{sup +3} ionization front, while R decreases with the incident continuum. We show that BAL variabilities in at least 80% of quasars are driven by the variation of an ionizing continuum, while other models that predict uncorrelated BAL and continuum variability contribute less than 20%. Considering large uncertainty in the continuum flux calibration, the latter fraction may be much smaller. When the sample is binned into different time intervals between the two observations, we find significant difference in the distribution of R between T1 and T2 in all time-bins down to ΔT<6 days, suggesting that the BAL outflow in a fraction of quasars has a recombination timescale of only a few days.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

Field Exploration and Life Detection Sampling Through Planetary Analogue Sampling (FELDSPAR).

Exploration missions to Mars rely on rovers to perform analyses over small sampling areas; however, landing sites for these missions are selected based on large-scale, low-resolution remote data. The use of Earth analogue environments to estimate the multi-scale spatial distributions of key signatures of habitability can help ensure mission science goals are met. A main goal of FELDSPAR is to conduct field operations analogous to Mars sample return in its science, operations, and technology from landing site selection, to in-field sampling location selection, remote or stand-off analysis, in situ analysis, and home laboratory analysis. Lava fields and volcanic regions are relevant analogues to Martian landscapes due to desiccation, low nutrient availability, and temperature extremes. Operationally, many Icelandic lava fields are remote enough to require that field expeditions address several sampling constraints that are experienced in robotic exploration, including in situ and sample return missions. The Fimmvruhls lava field was formed by a basaltic effusive eruption associated with the 2010 Eyjafjallajkull eruption. Mlifellssandur is a recently deglaciated plain to the north of the Myrdalsjkull glacier. Holuhraun was formed by a 2014 fissure eruptions just north of the large Vatnajkull glacier. Dyngjusandur is an alluvial plain apparently kept barren by repeated mechanical weathering. Informed by our 2013 expedition, we collected samples in nested triangular grids every decade from the 10 cm scale to the 1 km scale (as permitted by the size of the site). Satellite imagery is available for older sites, and for Mlifellssandur, Holuhraun, and Dyngjusandur we obtained overhead imagery at 1 m to 200 m elevation. PanCam-style photographs were taken in the field by sampling personnel. In-field reflectance spectroscopy was also obtained with an ASD spectrometer in Dyngjusandur. All sites chosen were 'homogeneous' in apparent color, morphology, moisture, grain size, and reflectance spectra at all scales greater than 10 cm. Field lab assays were conducted to monitor microbial habitation, including ATP quantification, qPCR for fungal, bacterial, and archaeal DNA, and direct cell imaging using fluorescence microscopy. Home laboratory analyses include Raman spectroscopy and community sequencing. ATP appeared to be significantly more sensitive to small changes in sampling location than qPCR or fluorescence microscopy. Bacterial and archaeal DNA content were more consistent at the smaller scales, but similarly variable across more distant sites. Conversely, cell counts and fungal DNA content have significant local variation but appear relatively homogeneous over scales of 1 km. ATP, bacterial DNA, and archaeal DNA content were relatively well correlated at many spatial scales. While we have observed spatial variation at various scales and are beginning to observe how that variation fluctuates over time as biodiversity recovers after an eruption, we do not yet fully understand what parameters lead to the observed spatial variation. Home laboratory analyses will help us further understand the elemental and structural composition of the basaltic matrices, but further field analyses are vital for the understanding how temperature, moisture, incident radiation, and so forth influence the habitability of a microclimate.

Field↗
NASA NTRS1973

Magnetic studies on Apollo 15 and 16 lunar samples

The magnetic properties of lunar samples are almost exclusively due to rather pure metallic iron. The mare basalt contains about 0.06 wt.% Fe, the soils 0.5-0.6 wt.%, and the breccias 0.3-1.0 wt.%. Most of the additional iron in the soils and breccias is believed to be the result of reduction processes operating on the lunar surface. Whereas the total metallic iron content of the soils from all landing sites is rather constant, the Fe(0)/Fe(++) ratio and the average iron grain size increase with the age of the landing site, reflecting increasing maturity. The crystalline rocks studied from Apollo 16 have highly variable, but generally, very high metallic Fe content (up to 1.7 wt.% Fe). It is suggested that these rocks are either breccias or igneous samples which have been severely thermally metamorphosed in a highly reducing environment.

Pearce, G. W.↗
DOE OSTI2024

Deep drilling in the time domain with DECam – II: characterizing the light curves of candidates in the extragalactic fields

ABSTRACT In this second paper on the DECam deep-drilling field (DDF) program, we release 2020 optical $gri$-band light curves for transients and variables in the extragalactic COSMOS and ELAIS fields based on time series observations with a 3-d cadence from semester 2021A through 2023A. In order to demonstrate the wide variety of time domain events detected by the program and encourage others to use the data set, we characterize the sample by presenting a brief analysis of the light-curve parameters such as time span, amplitude, and peak brightness. We also present preliminary light-curve categorizations, and identify potential stellar variables, active galactic nuclei, tidal disruption events, supernovae (SNe) (such as Type Ia, Type IIP, superluminous, and gravitationally lensed SNe), and fast transients. Where relevant, the number of identified transients is compared to the predictions of the original proposal. We also discuss the challenges of analyzing DDF data in the context of the upcoming Vera C. Rubin Observatory and its Legacy Survey of Space and Time, which will include DDFs. Images from the Dark Energy Camera DDF program are available without proprietary period and the light curves presented in this work are publicly available for analysis.

Graham, Melissa L. (ORCID:0000000291543136)↗
DOE OSTI2019

Cloud Atlas: Hubble Space Telescope Near-infrared Spectral Library of Brown Dwarfs, Planetary-mass Companions, and Hot Jupiters

Bayesian atmospheric retrieval tools can place constraints on the properties of brown dwarfs' and hot Jupiters' atmospheres. To fully exploit these methods, high signal-to-noise spectral libraries with well-understood uncertainties are essential. We present a high signal-to-noise spectral library (1.10–1.69 μm) of the thermal emission of 76 brown dwarfs and hot Jupiters. All our spectra have been acquired with the Hubble Space Telescope’s Wide Field Camera 3 instrument and its G141 grism. The near-infrared spectral types of these objects range from L4 to Y1. Eight of our targets have estimated masses below the deuterium-burning limit. We analyze the database to identify peculiar objects and/or multiple systems, concluding that this sample includes two very-low-surface-gravity objects and five intermediate-surface-gravity objects. In addition, spectral indices designed to search for composite-atmosphere brown dwarfs indicate that eight objects in our sample are strong candidates to have such atmospheres. None of these objects are overluminous, so their composite atmospheres are unlikely to be companion-induced artifacts. Five of the eight confirmed candidates have been reported as photometrically variable, suggesting that composite atmospheric indices are useful in identifying brown dwarfs with strongly heterogeneous cloud covers. We compare hot Jupiters and brown dwarfs in a near-infrared color–magnitude diagram. We confirm that the coldest hot Jupiters in our sample have spectra similar to mid-L dwarfs, and the hottest hot Jupiters have spectra similar to those of M-dwarfs. Our sample provides a uniform data set of a broad range of ultracool atmospheres, allowing large-scale comparative studies and providing an HST legacy spectral library.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗
NASA NTRS1972

Some analyses of the variability of atmospheric parameters at low altitudes significant for aircraft propagation

The results are discussed in terms of the meteorological data acquisition procedures necessary to monitor changes in atmospheric parameters to support aircraft flyover noise measurements and aircraft noise certification programs. The data consisted primarily of sequential radiosonde ascents to approximately 5000 ft spaced some half-hour to an hour apart. The weather covered by the data sample was predominantly that of clear skies and calm-to-light surface winds associated with well established high-pressure systems. Under these restrictive weather conditions, the study shows that the largest variabilities in temperature and humidity occur during the early morning hours resulting from the effects of direct solar heating of the surface. These rapid changes apparently do not penetrate above approximately 1000 ft. In the late morning hours, the atmosphere appears to become stabilized so that net changes in temperatures and relative humidities at all levels are insignificant even in time periods exceeding three hours. By noon, however, turbulent fluctuations in surface wind and the wind speed itself increase to levels which would make the microphone recording of acoustic signals in the field difficult.

Chang, D. T.↗
DOE OSTI2015

Quantifying Interannual Variability for Photovoltaic Systems in PVWatts

The National Renewable Energy Laboratory's (NREL's) PVWatts is a relatively simple tool used by industry and individuals alike to easily estimate the amount of energy a photovoltaic (PV) system will produce throughout the course of a typical year. PVWatts Version 5 has previously been shown to be able to reasonably represent an operating system's output when provided with concurrent weather data, however this type of data is not available when estimating system output during future time frames. For this purpose PVWatts uses weather data from typical meteorological year (TMY) datasets which are available on the NREL website. The TMY files represent a statistically 'typical' year which by definition excludes anomalous weather patterns and as a result may not provide sufficient quantification of project risk to the financial community. It was therefore desired to quantify the interannual variability associated with TMY files in order to improve the understanding of risk associated with these projects. To begin to understand the interannual variability of a PV project, we simulated two archetypal PV system designs, which are common in the PV industry, in PVWatts using the NSRDB's 1961-1990 historical dataset. This dataset contains measured hourly weather data and spans the thirty years from 1961-1990 for 239 locations in the United States. To note, this historical dataset was used to compose the TMY2 dataset. Using the results of these simulations we computed several statistical metrics which may be of interest to the financial community and normalized the results with respect to the TMY energy prediction at each location, so that these results could be easily translated to similar systems. This report briefly describes the simulation process used and the statistical methodology employed for this project, but otherwise focuses mainly on a sample of our results. A short discussion of these results is also provided. It is our hope that this quantification of the interannual variability of PV systems will provide a starting point for variability considerations in future PV system designs and investigations. however this type of data is not available when estimating system output during future time frames.

14 SOLAR ENERGY↗
NASA NTRS2000

Oscillatory patterns in sympathetic neural discharge and cardiovascular variables during orthostatic stimulus

BACKGROUND: We tested the hypothesis that a common oscillatory pattern might characterize the rhythmic discharge of muscle sympathetic nerve activity (MSNA) and the spontaneous variability of heart rate and systolic arterial pressure (SAP) during a physiological increase of sympathetic activity induced by the head-up tilt maneuver. METHODS AND RESULTS: Ten healthy subjects underwent continuous recordings of ECG, intra-arterial pressure, respiratory activity, central venous pressure, and MSNA, both in the recumbent position and during 75 degrees head-up tilt. Venous samplings for catecholamine assessment were obtained at rest and during the fifth minute of tilt. Spectrum and cross-spectrum analyses of R-R interval, SAP, and MSNA variabilities and of respiratory activity provided the low (LF, 0.1 Hz) and high frequency (HF, 0.27 Hz) rhythmic components of each signal and assessed their linear relationships. Compared with the recumbent position, tilt reduced central venous pressure, but blood pressure was unchanged. Heart rate, MSNA, and plasma epinephrine and norepinephrine levels increased, suggesting a marked enhancement of overall sympathetic activity. During tilt, LF(MSNA) increased compared with the level in the supine position; this mirrored similar changes observed in the LF components of R-R interval and SAP variabilities. The increase of LF(MSNA) was proportional to the amount of the sympathetic discharge. The coupling between LF components of MSNA and R-R interval and SAP variabilities was enhanced during tilt compared with rest. CONCLUSIONS: During the sympathetic activation induced by tilt, a similar oscillatory pattern based on an increased LF rhythmicity characterized the spontaneous variability of neural sympathetic discharge, R-R interval, and arterial pressure.

NASA Program Biomedical Research and Countermeasur↗
DOE OSTI2023

Carbon-Assisted, Continuous Syngas Production in a Chemical Looping Scheme

In the current energy and environment scenario, it is imperative to develop energy efficient routes for chemical manufacturing that also pave the way for mitigation of greenhouse gas emissions. This work presents an efficient pathway for continuous syngas production via a chemical looping conversion of the two most potent greenhouse gases—CH 4 , and CO 2 . The well-known dry-reforming process of converting CH 4 , and CO 2 to syngas is energy-intensive and suffers from catalyst deactivation. The chemical looping approach, on the other hand, provides avenues for mitigating catalyst deactivation and enabling improved energy efficiency. The key to such process enhancements lies in the intricate structure–function relationships of the catalyst and its correlation to the process variables. We present the reduction and oxidation characteristics of 5 wt.% Ni/Ce 1-x Zr x O 2 -based catalysts (x = 0, 0.4, and 0.625). We demonstrate low temperature CH4 activation over Ni-promoted samples as opposed to pure Ce 1-x Zr x O 2 . Moreover, our results depict an optimum regeneration of these catalysts when oxidized by CO 2 , and H 2 O, which allows for chemical looping operation of steam reforming of methane as well. Process variables were tuned to optimize the CH 4 conversion (over 80%), and H 2 /CO ratio at 650 °C. The critical surface reactions—carbon accumulation and gasification, and thermocatalytic CO 2 splitting were investigated to elucidate the dynamic nature of the catalyst surface. In conclusion, the impact of this work lies in showcasing the opportunities to design chemical looping reactors for energy efficient syngas production from waste greenhouse gases.

25 ENERGY STORAGE↗
NASA NTRS1985

Optical and radio properties of X-ray selected BL Lacertae objects

The eight BL Lac objects from the HEAO 1 A-2 all-sky survey and from the Einstein medium-sensitivity survey (MSS) form a flux-limited complete X-ray selected sample. The optical and radio properties of the MSS BL Lac objects are presented and compared with those of the HEAO 1 A-2 sample and with those of radio-selected BL Lac objects. The X-ray selected BL Lac objects possess smaller polarized fractions and less violent optical variability than radio-selected BL Lac objects. These properties are consistent with the substantial starlight fraction seen in the optical spectra of a majority of these objects. This starlight allows a determination of definite redshifts for two of four MSS BL Lac objects and a probable redshift for a third. These redshifts are 0.2, 0.3, and 0.6. Despite the differences in characteristics between the X-ray selected and radio-selected samples, it is concluded that these eight objects possess most of the basic qualities of BL Lac objects and should be considered members of that class. Moreover, as a class, these X-ray selected objects have the largest ratio of X-ray to optical flux of any active galactic nuclei yet discovered.

Stocke, J. T.↗
DOE OSTI2015

SUN-LIKE MAGNETIC CYCLES IN THE RAPIDLY ROTATING YOUNG SOLAR ANALOG HD 30495

A growing body of evidence suggests that multiple dynamo mechanisms can drive magnetic variability on different timescales, not only in the Sun but also in other stars. Many solar activity proxies exhibit a quasi-biennial (∼2 year) variation, which is superimposed upon the dominant 11 year cycle. A well-characterized stellar sample suggests at least two different relationships between rotation period and cycle period, with some stars exhibiting long and short cycles simultaneously. Within this sample, the solar cycle periods are typical of a more rapidly rotating star, implying that the Sun might be in a transitional state or that it has an unusual evolutionary history. In this work, we present new and archival observations of dual magnetic cycles in the young solar analog HD 30495, a ∼1 Gyr old G1.5 V star with a rotation period near 11 days. This star falls squarely on the relationships established by the broader stellar sample, with short-period variations at ∼1.7 years and a long cycle of ∼12 years. We measure three individual long-period cycles and find durations ranging from 9.6 to 15.5 years. We find the short-term variability to be intermittent, but present throughout the majority of the time series, though its occurrence and amplitude are uncorrelated with the longer cycle. These essentially solar-like variations occur in a Sun-like star with more rapid rotation, though surface differential rotation measurements leave open the possibility of a solar equivalence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Synthesis and Observation of Emergent Phenomena in Epitaxial Heusler Compound Heterostructures

The proposal was on the synthesis and observation of emergent phenomena in epitaxial Heusler compound heterostructures. The large range of properties and number of Heusler compounds opens up a wide number of potential compounds that will exhibit emergent phenomena. The similarity, large range of relatively inexpensive, large area, high crystal quality, III-V bulk substrates, lattice parameters and the ability to tune the lattice parameters through ternary or quaternary III-V compound semiconductor epitaxial growth, makes III-V semiconductors an ideal choice for substrates for epitaxial growth of Heusler compounds. A number of half Heusler compounds have been predicted to exhibit band inversion, making them topological and are therefore expected to exhibit spin-momentum locked topological surface states with linear dispersion. Others are predicted to be semimetals with Weyl points and others semiconducting and magnetic. During the course of this grant, emphasis has been on investigating Heusler compounds with emergent phenomena and demonstrating the ability to tune their properties through alloying and strain. We have grown toplogical semimetal (PtLuSb, PtMnBi), Weyl (Co 2 MnAl, Co 2 TiGe), half metal (PtMnSb, Co 2 MnSi, Co 2 MnAl x Si 1-x , Co2FeAl), and semiconducting (CoTiSb, NiTiSn) and tuned their properties through alloying and epitaxial strain. We also investigated the closely related materials of rare-earth monopnictide, some of which have also been predicted to be topological. During the attempts to grow the PtMnBi, it was discovered that Bi, another predicted topological material when ultrathin, could be grown epitaxially on InSb, results for which are also reported here. The main focus for this effort has been on using variable photon energy and spin-dependent angle resolved photoemission (ARPES) to determine bulk band structure and surface states of pristine epitaxial films grown on III-V semiconductor and MgO substrates and correlate results with theory and transport measurements. Theory has been critical to interpretation of experimental results and has been essential in guiding experiments. The research benefited from several strong collaborations between the PIs and the beamline scientists at the Advanced Light Source at Lawrence Berkeley Laboratory, the Stanford Linear Accelerator Center (SLAC) at Stanford and at the Max Lab at Lund University in Sweden. The strong experiment - theory collaboration between the PI’s groups, the Palmstrøm group at UCSB and the Janotti group at the University of Delaware, has been critical for interpreting the experimental ARPES and magnetotransport measurements results and making predictions to guide experiments. Weekly interactive Zoom meetings made this work well. A collaboration between the Palmstrøm group and Dr. Alexei Fedorov at the Advanced Light Source (ALS) resulted in significant modifications to his end chamber to accommodate the vacuum suitcase that was designed and constructed in the Palmstrøm group at UCSB. In collaboration with beamline scientists, Drs. Makoto Hashimoto and Donghui Lu at SLAC, Palmstrøm made modifications to the vacuum suitcase and developed special sample holders that allowed samples to be grown in the Palmstrøm MBE systems at UCSB and transported in the UHV vacuum suitcase to SLAC for ARPES measurements. The development of the vacuum suitcase was essential for this grant as it has allowed variable photon energies to be used to identify surface versus bulk states on samples that could not be capped and decapped using As- or Sb-capping layers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Integrating photovoltaics (PV) into electricity grids is challenged by potentially large fluctuations in power generation. In recent years, sky image-based PV output prediction using convolutional neural networks (CNNs) has emerged as a promising approach to forecasting fluctuations. A key challenge is imbalanced sky image datasets: because of the geography of solar PV system installations, sky image datasets are often rich in sunny condition data but deficient in cloudy condition data. This imbalance contrasts with the fact that model errors are dominated by cloudy condition performance. In this study, we attempt to remedy this by exploring the enrichment and augmentation of an imbalanced sky images dataset for two PV output prediction tasks: nowcasting (predicting concurrent PV output) and forecasting (predicting 15-minute-ahead future PV output). We empirically examine the efficacy of using different resampling and data augmentation approaches to create a rebalanced dataset for model development. A three-stage greedy search is used to determine the optimal resampling approach, data augmentation techniques and over-sampling rate. The results show that for the nowcast problem, resampling and data augmentation can effectively enhance the model performance, reducing overall root mean squared error (RMSE) by an average of 4%, or a 15 std. (standard deviation) of improvement compared to the variability of the baseline model. In contrast, the treatment RMSE for the forecast problem nearly always overlaps the baseline performance at the ± 2 std. level. The optimal resampling approach expands on the original dataset by over-sampling the minority cloudy data, with the best results from large over-sampling rate (e.g., 4 ~ 6 times over-sampling of cloudy images).

14 SOLAR ENERGY↗
DOE OSTI2016

Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly

Self-assembly of proteins into amyloid aggregates is an important biological phenomenon associated with human diseases such as Alzheimer’s disease. Amyloid fibrils also have potential applications in nano-engineering of biomaterials. The kinetics of amyloid assembly show an exponential growth phase preceded by a lag phase, variable in duration as seen in bulk experiments and experiments that mimic the small volumes of cells. Here, to investigate the origins and the properties of the observed variability in the lag phase of amyloid assembly currently not accounted for by deterministic nucleation dependent mechanisms, we formulate a new stochastic minimal model that is capable of describing the characteristics of amyloid growth curves despite its simplicity. We then solve the stochastic differential equations of our model and give mathematical proof of a central limit theorem for the sample growth trajectories of the nucleated aggregation process. These results give an asymptotic description for our simple model, from which closed form analytical results capable of describing and predicting the variability of nucleated amyloid assembly were derived. We also demonstrate the application of our results to inform experiments in a conceptually friendly and clear fashion. Our model offers a new perspective and paves the way for a new and efficient approach on extracting vital information regarding the key initial events of amyloid formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2015

Ammonia and Methane Dairy Emission Plumes in the San Joaquin Valley of California from Individual Feedlot to Regional Scales

Agricultural ammonia (NH3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH3 and methane (CH4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH3 and CH4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH3:CH4 enhancement ratio derived from surface measurements is 0.15 +/- 0.03 ppmv ppmv−1. Individual dairy feedlots with spatially distinct NH3 and CH4 source pathways led to statistically significant correlations between NH3 and CH4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH3:CH4 enhancement ratio decreases 20-30%, suggesting the potential for NH3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surface mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH3 partitioning to submicron particles. Individual NH3 and CH4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. Our analyses have important implications for constraining NH3 sink and plume variability influences on regional NH3 emission estimates and for improving NH3 emission inventory spatial allocations.

Miller, David J.↗
DOE OSTI2016

Effects of the microstructure and porosity on properties of Ti-6Al-4V ELI alloy fabricated by electron beam melting (EBM)

Electron Beam Melting (EBM) is a metal powder bed-based Additive Manufacturing (AM) technology that makes possible the fabrication of three dimensional near-net-shaped parts directly from computer models. EBM technology has been in continuously updating, obtaining optimized properties of the processed alloys. Ti-6Al-4V titanium alloy is the most widely used and studied alloy for this technology and is the focus of this work. Several research works have been completed to study the mechanisms of microstructure formation as well as its influence on mechanical properties. However, the relationship is not completely understood, and more systematic research work is necessary in order to attain a better understanding of these features. In this work, samples fabricated at different locations, orientations, and distances from the build platform have been characterized, studying the relationship of these variables with the resulting material intrinsic characteristics and properties (surface topography, microstructure, porosity, micro-hardness and static mechanical properties). This study has revealed that porosity is the main factor controlling mechanical properties relative to the other studied variables. Therefore, in future process developments, decreasing of the porosity should be considered as the primary goal in order to improve mechanical properties.

36 MATERIALS SCIENCE↗