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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Annual carbon dioxide flux over seasonal sea ice in the Canadian Arctic

Continuous measurements of carbon dioxide (CO 2 ) flux were collected from a 10 m eddy covariance tower in a coastal-marine environment in the Canadian Arctic Archipelago over the course of a 17-month period. The extended length of data collection resulted in a unique dataset that includes measurements from two spring melt and summer seasons and one autumn freeze-up. These field observations were used to verify findings from previous theoretical and laboratory experiments investigating air-sea gas exchange in connection with sea ice. The results corroborated previous findings showing that thick ice cover under winter conditions acts as a barrier to gas exchange. In the spring, CO 2 fluxes were downward (uptake) in both the presence of melt ponds and during ice break-up. However, diurnal cycles were present throughout the early spring melt period, corresponding to the opposing influences of freezing and melting at the ice surface. Fluxes measured during melt periods confirmed previous laboratory tank measurements that showed a gas transfer coefficient of melting ice of 0.4 mol m −2 d −1 atm −1 . Open water CO 2 fluxes showed outgassing in early summer and uptake in mid-to-late summer, tied closely to trends in surface water temperature and its effect on the partial pressure of CO 2 in the water. The autumn period of the field campaign represents the first eddy covariance CO 2 fluxes measured over naturally forming sea ice. Our measurements showed mean upward fluxes (outgassing) of 1.1±1.5 mmol m −2 d −1 associated with the freezing of ice – the same order of magnitude found by previous laboratory tank experiments. However, peak flux periods during ice formation had measured fluxes that were a factor of 3 higher than the tank experiments, suggesting the importance of natural conditions (e.g., wind) on air-ice gas exchange. Conducting an Arctic-wide extrapolation we estimate CO 2 outgassing from the freezing period to be a counterbalance equivalent to 5 to 15 % of the magnitude of the estimated Arctic CO 2 sink. Overall, there was no evidence of dramatically enhanced gas exchange in marginal ice conditions as proposed by previous studies. Although the different seasons showed active CO 2 exchange, there was a balance between upward and downward fluxes at this specific location, resulting in a small net CO 2 uptake over the annual cycle of −0.3 g C m −2 .

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Linked Open Data in the Global Change Information System (GCIS)

The U.S. Global Change Research Program (http://globalchange.gov) coordinates and integrates federal research on changes in the global environment and their implications for society. The USGCRP is developing a Global Change Information System (GCIS) that will centralize access to data and information related to global change across the U.S. federal government. The first implementation will focus on the 2013 National Climate Assessment (NCA) . (http://assessment.globalchange.gov) The NCA integrates, evaluates, and interprets the findings of the USGCRP; analyzes the effects of global change on the natural environment, agriculture, energy production and use, land and water resources, transportation, human health and welfare, human social systems, and biological diversity; and analyzes current trends in global change, both human-induced and natural, and projects major trends for the subsequent 25 to 100 years. The NCA has received over 500 distinct technical inputs to the process, many of which are reports distilling and synthesizing even more information, coming from thousands of individuals around the federal, state and local governments, academic institutions and non-governmental organizations. The GCIS will present a web-based version of the NCA including annotations linking the findings and content of the NCA with the scientific research, datasets, models, observations, etc. that led to its conclusions. It will use semantic tagging and a linked data approach, assigning globally unique, persistent, resolvable identifiers to all of the related entities and capturing and presenting the relationships between them, both internally and referencing out to other linked data sources and back to agency data centers. The developing W3C PROV Data Model and ontology will be used to capture the provenance trail and present it in both human readable web pages and machine readable formats such as RDF and SPARQL. This will improve visibility into the assessment process, increase understanding and reproducibility, and ultimately increase credibility and trust of the resulting report. Building on the foundation of the NCA, longer term plans for the GCIS include extending these capabilities throughout the U.S. Global Change Research Program, centralizing access to global change data and information across the thirteen agencies that comprise the program.

Tilmes, Curt A.↗
NASA NTRS2013

Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data

Web-based geospatial client applications such as Google Earth and NASA World Wind must listen to data requests, access appropriate stored data, and compile a data response to the requesting client application. This process occurs repeatedly to support multiple client requests and application instances. Newer Web-based geospatial clients also provide user-interactive functionality that is dependent on fast and efficient server responses. With massively large datasets, server-client interaction can become severely impeded because the server must determine the best way to assemble data to meet the client applications request. In client applications such as Google Earth, the user interactively wanders through the data using visually guided panning and zooming actions. With these actions, the client application is continually issuing data requests to the server without knowledge of the server s data structure or extraction/assembly paradigm. A method for efficiently controlling the networked access of a Web-based geospatial browser to server-based datasets in particular, massively sized datasets has been developed. The method specifically uses the Keyhole Markup Language (KML), an Open Geospatial Consortium (OGS) standard used by Google Earth and other KML-compliant geospatial client applications. The innovation is based on establishing a dynamic cascading KML strategy that is initiated by a KML launch file provided by a data server host to a Google Earth or similar KMLcompliant geospatial client application user. Upon execution, the launch KML code issues a request for image data covering an initial geographic region. The server responds with the requested data along with subsequent dynamically generated KML code that directs the client application to make follow-on requests for higher level of detail (LOD) imagery to replace the initial imagery as the user navigates into the dataset. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics. The method yields significant improvements in userinteractive geospatial client and data server interaction and associated network bandwidth requirements. The innovation uses a C- or PHP-code-like grammar that provides a high degree of processing flexibility. A set of language lexer and parser elements is provided that offers a complete language grammar for writing and executing language directives. A script is wrapped and passed to the geospatial data server by a client application as a component of a standard KML-compliant statement. The approach provides an efficient means for a geospatial client application to request server preprocessing of data prior to client delivery. Data is structured in a quadtree format. As the user zooms into the dataset, geographic regions are subdivided into four child regions. Conversely, as the user zooms out, four child regions collapse into a single, lower-LOD region. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics.

Baxes, Gregory↗
NASA NTRS2004

Secure, Mobile, Wireless Network Technology Designed, Developed, and Demonstrated

The inability to seamlessly disseminate data securely over a high-integrity, wireless broadband network has been identified as a primary technical barrier to providing an order-of-magnitude increase in aviation capacity and safety. Secure, autonomous communications to and from aircraft will enable advanced, automated, data-intensive air traffic management concepts, increase National Air Space (NAS) capacity, and potentially reduce the overall cost of air travel operations. For the first time ever, secure, mobile, network technology was designed, developed, and demonstrated with state-ofthe- art protocols and applications by a diverse, cooperative Government-industry team led by the NASA Glenn Research Center. This revolutionary technology solution will make fundamentally new airplane system capabilities possible by enabling secure, seamless network connections from platforms in motion (e.g., cars, ships, aircraft, and satellites) to existing terrestrial systems without the need for manual reconfiguration. Called Mobile Router, the new technology autonomously connects and configures networks as they traverse from one operating theater to another. The Mobile Router demonstration aboard the Neah Bay, a U.S. Coast Guard vessel stationed in Cleveland, Ohio, accomplished secure, seamless interoperability of mobile network systems across multiple domains without manual system reconfiguration. The Neah Bay was chosen because of its low cost and communications mission similarity to low-Earth-orbiting satellite platforms. This technology was successfully advanced from technology readiness level (TRL) 2 (concept and/or application formation) to TRL 6 (system model or prototype demonstration in a relevant environment). The secure, seamless interoperability offered by the Mobile Router and encryption device will enable several new, vehicle-specific and systemwide technologies to perform such things as remote, autonomous aircraft performance monitoring and early detection and mitigation of potential equipment malfunctions. As an additional benefit, team advancements were incorporated into open standards, ensuring technology transfer. Low-cost, commercial products incorporating the new technology are already available. Furthermore, these products are fully interoperable with legacy network technology equipment currently being used throughout the world.

Ivancic, William D.↗
NASA NTRS1995

Gas near the center of 30 Doradus as revealed by Hubble Space Telescope images

We present images of a 40 pc region of the 30 Doradus nebula centered about 1 arcminute north of the luminous star cluster R136 in the Large Magellanic Cloud. The region was imaged with the Hubble Space Telescope (HST) Wide Field Camera through H alpha, (S II), and stellar continuum filters. These data allow us to examine this region of star formation and the breakup of the cloud around R136 on a scale of 0.027 pc per pixel. We also present a complementary ground-based echelle spectrum of the H alpha and (N II) emission lines in this region. In the images one sees an extensive filamentary structure surrounding regions that have been hollowed out by R136 and other massive stars in the area. The (S II) image shows a sharper, more filamentary appearance than the H alpha image, and the filaments are offset in (S II) generally away from R136. These characteristics are indicative of ionization fronts that are outlining the neutral material and dust features. We also find fingers of enhanced (S II) emission located about 90 sec to the northwest of R136. The (S II) fingers appear to be readiating generally from a common region, and we suggest that they are composed of material ablated from the high density gas of the ionization fronts and entrained with the flow of the stellar winds from R136. We find that a small knot of emission resolves into two shells of about 0.5 pc diameter, each of which encircles one or two stars. One of the stars has been identified as an early main-sequence O star by Walborn & Blades (1987), and the shell could be a young wind-blown bubble. We also find a parabolic-shaped arc at the head of a long cone that opens up away from R136. The arc is located near a luminous candidate protostar identified by Hyland et al. (1992).

Hunter, Deidre A.↗
DOE OSTI2021

Unveiling the star formation history of the Upper Scorpius association through its kinematics

ABSTRACT Stellar associations can be discerned as overdensities of sources not only in the physical space but also in the velocity space. The common motion of their members, gradually eroded by the galactic tidal field, is partially reminiscent of the initial kinematic structure. Using recent data from Gaia EDR3, combined with radial velocities from GALAH and APOGEE, we traced back the present positions of stars belonging to Upper Scorpius (USCO), a subgroup of Scorpius–Centaurus, the nearest OB association. About one half of the subgroup (the ‘clustered’ population) appears composed of many smaller entities, which were in a more compact configuration in the past. The presence of a kinematic duality is reflected into an age spread between this younger clustered population and an older diffuse population, in turn confirmed by a different fraction fD of disc-bearing stars (fD = 0.24 ± 0.02 versus fD = 0.10 ± 0.01). Star formation in USCO appears to have lasted more than 10 Myr and proceeded in small groups that, after a few Myr, dissolve in the field of the older population but retain for some time memory of their initial structure. The difference of ages inferred through isochrones and kinematics, in this regard, could provide a powerful tool to quantify the time-scale of gas removal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Comparative analysis of nutrient concentrations in generalist and specialist tree species and soils, Manaus, Brazil

This dataset was collected near Manaus, Brazil, at ZF-2 site, inside the North-South transect plots from 20221011 to 20221020. Measurements were made on specialists and generalist tree species along topographic gradient (in upland high-clay content soils of plateaus and high sandy content and partially flooded soils of valleys). We selected nine species (with four replicates each, totaling 35 individuals) occurring in different topographic positions: three plateau specialists, three valley specialists, and three generalists, where leaf and trunk samples were collected from each individual, and soil samples for carbon and nutrient analysis and quantification. Three soil pits were opened around each sample tree, about one meter apart (total of 105 soil pits each 60-cm deep), where soil samples were collected at four depths: 0-5, 5-10, 10-30 and 30-50 cm. In each of the three pits around each tree, one single sample was taken at each depth and combined to obtain a composite sample per depth per individual tree (35 trees × 4 depths = 140 soil samples). The files “Plant_Nutrient_Concentrations_NS_Transect_Manaus.csv” and “Soil_Nutrient_Concentrations_NS_Transect_Manaus.csv” contain the nutrient concentration data from plant and soil material, respectively. Additionally, the file “Sample_Info.csv” contains details about each variable including units and data type. The file “Species_Info.csv” includes information about each sampled individual, such as species, family, diameter at the breast height (DBH), and more. The dataset is ready to be used in any programming language like python or R. This dataset was originally published on the NGEE Tropics Archive and is being mirrored on ESS-DIVE for long-term archival Acknowledgement: Funding for NGEE-Tropics data resources was provided by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗
NASA NTRS2017

A Case for Nebula Scale Mixing Between Non-Carbonaceous and Carbonaceous Chondrite Reservoirs: Testing the Grand Tack Model with Chromium Isotopic Composition of Almahata Sitta Stone 91A

There is an increasing number of Cr-O-Ti isotope studies that show solar system materials are divided into two main populations, one carbonaceous chondrite (CC)-like and the other is non-carbonaceous (NC)-like, with minimal mixing attributed to a gap opened in the protoplanetary disk due to Jupiter's formation. The Grand Tack model suggests there should be large-scale mixing between S- and C-type asteroids, an idea supported by our recent work on chondrule (Delta)17O-ε54Cr isotope systematics. The Almahata Sitta (AhS) meteorite provides a unique opportunity to test the Grand Tack model. The meteorite fell to Earth in October 2008 and has been linked to the asteroid 2008 TC3 which was discovered just prior to the fall of the AhS stones. The AhS meteorite is composed of up to 700 individual pieces with approx.140 of those pieces having some geochemical and/or petrologic studies. Almahata Sitta is an anomalous polymict ureilite with other meteorite components, including enstatite, ordinary, and carbonaceous chondrites with an approximate abundance of 70% ureilites and 30% chondrites. This observation has lead to the suggestion that TC3 2008 was a loosely aggregated rubble pile-like asteroid with the non-ureilite sample clasts within the rubble-pile. Due to the loosely-aggregated nature of AhS, the object disintegrated during atmospheric entry resulting in the weakly held clasts falling predominantly as individual stones in the AhS collection area. However, recent work has identified one sample of AhS, sample 91A, which may represent two different lithologies coexisting within a single stone. The predominate lithology type in 91A appears to be that of a C2 chondrite based on mineralogy but also contains olivine, pyroxene, and albite that have ureilite-like compositions. Previous Cr isotope investigations into AhS stones are sparse and what data is available show nearly uniform isotopic composition similar to that of typical ureilites with negative ε54Cr values.

Sanborn, M. E.↗
DOE OSTI2024

First principles density functional theory study of tritium species adsorption on Ni(111) surface and diffusion in nickel-sublayer for tritium storage

The nickel-plated zircaloy-4 is used as a tritium ( 3 H) getter in the tritium-producing burnable absorber rods (TPBARs) to capture 3 H produced in the 6 Li-riched annular γ-LiAlO 2 pellet under neutron irradiation. The experimental data and our previous theoretical results showed that the 3 H species produced from the γ-LiAlO 2 pellet were mainly 3 H 2 and 3 H 2 O. These 3 H species diffuse from the surface of the LiAlO 2 pellet across vacuum to the nickel-plated zircaloy-4 getter and then further diffuse into the getter to chemically form metal hydrides. While a number of studies show that oxygen binds strongly as compared to 3 H on the nickel (Ni) layer, the detailed mechanism of 3 H species absorption and diffusion across the Ni plate and Ni/Zr interface are still unclear. By employing density functional theory calculations, here we explored the 3 H 2 and 3 H 2 O species adsorption and dissociation on the Ni(111) surface and diffusion into the Ni sublayer. Our results indicated that the 3 H 2 and 3 H 2 O dissociate on the Ni(111) surface. The NiO x and Ni(O 3 H) x could be formed in the Ni layer due to the higher oxygen (O) diffusion energy barrier and formation of Ni vacancy defects. The oxygen was found to be retained in the Ni layer from diffusing across the Ni–Zr interface. This was revealed by comparing the diffusion barriers for 3 H with O. 3 H was found to have nearly three times smaller diffusion barrier than for O, making 3 H comparatively easier to diffuse through the Ni layer. In conclusion, the obtained results provide guidelines for experimental measurements on 3 H retention behavior in TPBARs and may open further avenues to explore the impurity effects on 3 H diffusion and storage at the Ni/zircaloy interfaces.

Tafen, De Nyago [National Energy Technology Lab. (↗
DOE OSTI2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tuscaloosa Marine Shale Laboratory

The Tuscaloosa Marine Shale (TMS) in Louisiana and Mississippi is an Upper Cretaceous source rock formation sandwiched between the sands of the upper and lower Tuscaloosa sections. The TMS is believed to be the source rock for underlying prolific Tuscaloosa sand formation. The TMS has an unproven estimate of 7,000,000,000 bbls of recoverable oil while its current total average production is about 3,000 bbls of oil per day in 2017. In 2013 and 2014, more than 80 wells were drilled horizontally into the TMS that were fractured using multi-stage fracturing technology. The results from this have been mixed, but recent production for several wells show an appealing initial oil production rate of more than 1000 bbl/day. The preliminary core analysis by industry partners and a few literature studies shows that the TMS is one of the most clay-rich and sensitive shales to water. Due to these and other technical problems, there is high risk for the economic development of TMS compared to other shale plays. The experiences of major industrial players in the TMS show the necessity of open and collaborative efforts to better understand the critical gaps in the development of this challenging and potentially highly economic shale play to enable more cost-efficient and environmentally-sound recovery from this unconventional liquid-rich shale play. The overall objective of this project is to form a consortium of science and industry partners to address the following six major objectives using scientific and technical approaches: 1. To improve wellbore integrity by better understanding the sources of the wellbore instability issues, proposing innovative mud and cement design for the TMS. 2. To improve formation evaluation using laboratory techniques for the evaluation of mineralogical composition, organic content, and produced-water chemistry as well as well log and geophysical analysis. 3. To determine the role of geologic discontinuities on fracture growth and shale creep behavior using digital image correlation technique. 4. To investigate the application of stable CO 2 foam and super-hydrophobic proppants for improved reservoir stimulation. 5. To better understand the nature of water/hydrocarbon/CO 2 flow in clay and organic-rich formation and the role of water/fluid interaction on recovery. 6. To prepare better socio-economic environment for TMS development by community engagement. Subsequently, the TMS virtual laboratory conducted testing and analysis of various properties of rock and formation fluids from the TMS, including but not limited to the following: Analyzing reports and logs to better understand the source of wellbore instability in TMS wells; Experiments to design a customized cement based on TMS requirements; Experiments to obtain the mineralogical and geochemical composition of TMS samples; Seismic analysis of TMS geophysical data to better predict total organic carbon (TOC) content and brittleness in TMS; Well log analysis to better estimate the TOC and geo-mechanical properties of TMS; Experiments on formation water to understand the chemistry of produced water; Experiments to determine the role of lamination and natural fractures on fracture propagation or rock deformation using digital image correlation technique in in-direct tensile tests, semi-circular bend test and creep tests Experiments to determine the stability and rheological properties of nanoparticle-stabilized CO 2 foam in TMS rock samples; Experiments to determine fluid dynamics in un-propped TMS fractures and the role of nano-coating of proppants on fluid dynamics in fractures with proppants; Micro-fluidics experiments to enhance the understanding of fluid dynamics in tight liquidrich pores with high clay content; Socio-economic studies to better engage communities in TMS development.

58 GEOSCIENCES↗
NASA NTRS2019

WWAO-WSWC Workshop Report 2019 Final

EXECUTIVE SUMMARY The Western States Water Council (WSWC) and the NASA Western Water Applications Office (WWAO) hosted a joint workshop on technology transfer for water management in the Western U.S. The goals of the workshop were to understand how different agencies approach the technology transfer and research to operations (R2O) process, identify best practices, and discuss existing barriers to successful technology infusion into operational water resource management systems at the state and federal level. The workshop took place August 7-9, 2019 in Irvine, CA. Key outcomes of the meeting include the following:• U.S. Rep. Grace Napolitano provided opening remarks for the workshop, where she highlighted the critical value of water data and the importance of collaboration between state and federal agencies in working to advance the use of water data in water management, planning and policy. • A total of 33 participants (including remote participants) were part of the workshop. They included principal investigators and project teams supported by NASA (Cyanobacteria Assessment Network, Evapotranspiration for Western States, Evaporative Stress Index, the Airborne Snow Observatory, Satellite-based Snow Water Equivalent in the Sierra Nevadas, and Fallowed Area Mapping) as well as representatives from federal (USGS, NOAA, USBR, EPA) and state (CA, WY, OR, NE) agency partners. • One main outcome of the meeting was the consensus that successful transitions of new applications and new technologies into operations require careful planning, effective communication within and across institutions, resources and considerable time investments. In addition, there was broad agreement that significant lead time is often required to allow for identification of financial and technical resources to sustain operational use of new data, information and tools.• The meeting included remarks from U.S. Rep. Napolitano and discussions during presentations and breakout groups about key opportunities to develop best practices and streamline the technology transfer process. • For example, one key set of best practices that emerged revolved around the the importance of building trust and establishing clear lines of communication between the research and operational institutions. The conversations led to defining two key components of trust-building. The first aspect is purely technical. It requires effectively demonstrating that the proposed application meets the end user’s needs in terms of accuracy, format, resolution, latency, metadata and documentation. The second aspect of building trust involves developing sustained, productive and mutually-beneficial relationships with the partner operational agency. The best practices presented here span both the technical as well as the relational aspects of cultivating trust. • This workshop served as a first step in developing a broader community discussion around R2O in western water management. Many of the best practices and lessons learned described in this report represent starting places for action within the WWAO, WSWC and our colleagues’ institutions. • Effective implementation of the best practices that emerged from this workshop will require sustained investments of time, resources and transition planning. In recognition of this, the WSWC and the WWAO proposed continuation of discussions begun at the workshop through a series of semi-annual or annual workshops.

Wilardson, Tony↗
DOE OSTI2022

The 3D Kinematics of the Orion Nebula Cluster: NIRSPEC-AO Radial Velocities of the Core Population

The kinematics and dynamics of stellar and substellar populations within young, still-forming clusters provide valuable information for constraining theories of formation mechanisms. Using Keck II NIRSPEC+AO data, we have measured radial velocities for 56 low-mass sources within 4' of the core of the Orion Nebula Cluster (ONC). We also remeasure radial velocities for 172 sources observed with SDSS/APOGEE. These data are combined with proper motions measured using HST ACS/WFPC2/WFC3IR and Keck II NIRC2, creating a sample of 135 sources with all three velocity components. The velocities measured are consistent with a normal distribution in all three components. We measure intrinsic velocity dispersions of (${\sigma }_{{v}_{\alpha }}$, ${\sigma }_{{v}_{\delta }}$, ${\sigma }_{{v}_{r}}$) = (1.64 ± 0.12, 2.03 ± 0.13, ${2.56}_{-0.17}^{+0.16}$) km s –1 . Our computed intrinsic velocity dispersion profiles are consistent with the dynamical equilibrium models from Da Rio et al. (2014) in the tangential direction but not in the line-of-sight direction, possibly indicating that the core of the ONC is not yet virialized, and may require a nonspherical potential to explain the observed velocity dispersion profiles. We also observe a slight elongation along the north–south direction following the filament, which has been well studied in previous literature, and an elongation in the line-of-sight to tangential velocity direction. These 3D kinematics will help in the development of realistic models of the formation and early evolution of massive clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

From EXOSAT to the High Energy Astrophysics Science Archive (HEASARC): X-ray Astronomy Comes of Age

In May 1983 the European Space Agency launched EXOSAT, its first X-ray astronomy observatory. Even though it lasted only 3 short years, this mission brought not only new capabilities that resulted in unexpected discoveries, but also a pioneering approach to operations and archiving that changed X-ray astronomy from observations led by small instrument teams, to an observatory approach open to the entire community through a guest observer program. The community use of the observatory was supported by a small dedicated team of scientists, the precursor to the data center activities created to support e.g. Chandra and XMM-Newton. The new science capabilities of EX OS AT included a 90 hr highly eccentric high earth orbit that allow unprecedented continuous coverage of sources as well as direct communication with the satellite that allowed real time decisions to respond to unexpected events through targets of opportunity. The advantages of this orbit demonstrated by EXOSAT resulted in Chandra and XMM-Newton selecting similar orbits. The three instruments on board the EXOSAT observatory were complementary, designed to give complete coverage over a wide energy band pass of 0.05-50 keY. An onboard processor could be programmed to give multiple data modes that could be optimized in response to science discoveries: These new capabilities resulted in many new discoveries including the first comprehensive study of AGN variability, new orbital periods in X-ray binaries and cataclysmic variables, new black holes, quasi-periodic oscillations from neutron stars and black holes and broad band X-ray spectroscopy. The EXOSAT team generated a well-organized database accessible worldwide over the nascent internet, allowing remote selection of data products, making samples and undertaking surveys from the data. The HEASARC was established by NASA at Goddard Space Flight Center in 1990 as the repository of NASA X-ray and Gamma-ray data. The proven EXOSAT database system became the core of the HEASARC infrastructure. The HEASARC pioneered many concepts now taken for granted including standardized formats using FITS files, restoring data from earlier missions, multi-mission analysis tools and a searchable archive over the world wide web.

White, Nicholas E.↗
DOE OSTI2023

Optimized thermodynamic properties of REE aqueous species (REE 3+ and REEOH 2+ ) and experimental database for modeling the solubility of REE phosphate minerals (monazite, xenotime, and rhabdophane) from 25 to 300 °C

Rare earth elements (REE) are critical elements found in monazite, xenotime, and hydrated REE phosphates which typically form in hydrothermal mineral deposits. Accurate predictions of the solubility of these REE phosphates and the speciation of REE in aqueous fluids are both key to understanding the controls on the transport, fractionation, and deposition of REE in natural systems. Previous monazite and xenotime solubility experiments indicate the presence of large discrepancies between experimentally derived solubility constants versus calculated solubilities by combining different data sources for the thermodynamic properties of minerals and aqueous species at hydrothermal conditions. In this study, these discrepancies were resolved by using the program GEMSFITS to optimize the standard partial molal Gibbs energy of formation (Δ f G° 298 ) of REE aqueous species (REE 3+ and REE hydroxyl complexes) at 298.15 K and 1 bar while keeping the thermodynamic properties fixed for the REE phosphates. A comprehensive experimental database was compiled using solubility data available between 25 and 300 °C. The latter permits conducting thermodynamic parameter optimization of Δ f G° 298 for REE aqueous species. Optimal matching of the rhabdophane solubility data between 25 and 100 °C requires modifying the Δ f G° 298 values of REE 3+ by 1–6 kJ/mol, whereas matching of the monazite solubility data between 100 and 300 °C requires modifying the Δ f G° 298 values of both REE 3+ and REEOH 2+ by ~15–31 kJ/mol and ~2–10 kJ/mol, respectively. For xenotime, adjustments of Δ f G° 298 values by 1–26 kJ/mol are only necessary for the REE 3+ species. The optimizations indicate that the solubility of monazite in acidic solutions is controlled by the light (L)REE 3+ species at <150 °C and the LREEOH 2+ species at >150 °C, whereas the solubility of xenotime is controlled by the heavy (H)REE 3+ species between 25 and 300 °C. Based on the optimization results, we conclude that the revised Helgeson-Kirkham-Flowers equation of state does not reliably predict the thermodynamic properties of REE 3+ , REEOH 2+ , and likely other REE hydroxyl species at hydrothermal conditions. We therefore provide an experimental database (ThermoExp_REE) as a basic framework for future updates, extensions with other ligands, and optimizations as new experimental REE data become available. As a result, the optimized thermodynamic properties of aqueous species and minerals are available open access to accurately predict the solubility of REE phosphates in fluid-rock systems.

58 GEOSCIENCES↗
DOE OSTI2025

1000 Soils Pilot Dataset, version 8, May 2025

This record hosts data generated by the 1000 Soils Pilot. Data will be updated as more become available. Please see the most recent data upload for current data. A beta visualization tool is available for some data types at https://shinyproxy.emsl.pnnl.gov/app/1000soils. Please submit any suggestions or comments through the 'contact' tab. We are actively working to improve visualizations and value all feedback. Data completed include: Geochemistry, texture, respiration, and enzyme activities FTICR-MS organic matter chemistry Microbial biomass C and N TOC/TDN of water-extractable OM X-ray computed tomography (derived metrics available here, raw data available upon request) Metagenomes; a variety of data formats are available upon request Soil hydraulic properties Data in progress: LC-MS/MS in development, timeline TBD, inquire for status 1000S_processed_BGC_summary.csv contains all available biogeochemical data; microbial biomass C and N; and TOC/TDN of water-extractable OM; and 1000S_Tomography.xslx contains a summary of data generated via X-ray computed tomography. icr_v2_corems2.csv contains FTICR-MS data processed by CoreMS version 2. These data are merged by formula across instrument runs to enable cross-sample comparisons. Technical replicates are merged by retaining peaks present in 2 out of 3 replicates. 1000Soils_Metadata_Site_Mastersheet_v1.csv contains site information. Soil Hydraulics_corrected_02042025.xlsx contains soil hydraulics information. Readme File_v4.xlsx is the readme file. Please contact the MONet project (monet.emsl@pnnl.gov) or Emily Graham (emily.graham@pnnl.gov) with questions. The following file and all raw data are available upon request: icr_by_mass_for_single_sample_analysis_only.csv contains FTICR-MS data processed by CoreMS and is intended for usage in the calculation of biochemical transformations within samples only. These data are not acceptable for cross-sample comparison of masses because they are from multiple instrument runs. For more information, please see: https://www.emsl.pnnl.gov/monet and https://sc-data.emsl.pnnl.gov/monet Acknowledgment: Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231. The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at https://sc-data.emsl.pnnl.gov/.

biogeochemistry↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗