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At least 1,297 records · Page 72

SU-D-BRD-01: An Automated Physics Weekly Chart Checking System Supporting ARIA

Purpose: A software tool was developed in this study to perform automatic weekly physics chart check on the patient data in ARIA. The tool accesses the electronic patient data directly from ARIA server and checks the accuracy of treatment deliveries, and generates reports which summarize the delivery history and highlight the errors. Methods: The tool has four modules. 1) The database interface is designed to directly access treatment delivery data from the ARIA database before reorganizing the data into the patient chart tree (PCT). 2) PCT is a core data structure designed to store and organize the data in logical hierarchies, and to be passed among functions. 3) The treatment data check module analyzes the organized data in PCT and stores the checking results into PCT. 4) Report generation module generates reports containing the treatment delivery summary, chart checking results and plots of daily treatment setup parameters (couch table positions, shifts of image guidance). The errors that are found by the tool are highlighted with colors. Results: The weekly check tool has been implemented in MATLAB and clinically tested at two major cancer centers. Javascript, cascading style sheets (CSS) and dynamic HTML were employed to create the user-interactive reports. It takes 0.06 second to search the delivery records of one beam with PCT and compare the delivery records with beam plan. The reports, saved in the HTML files on shared network folder, can be accessed by web browser on computers and mobile devices. Conclusion: The presented weekly check tool is useful to check the electronic patient treatment data in Varian ARIA system. It could be more efficient and reliable than the manually check by physicists. The work was partially supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗

Contribution to the Development of DOE ARM Climate Best Estimate Data (ARMBE) Products: Land Surface Forcing and Evaluation Data Set (ARMBE-LAND) from the ARM SGP Site

To support the LLNL ARM Best Estimate Data Products (ARMBE) data development, the San Jose State University (SJSU)’s group will provide the LLNL team yearly data files (in a format consistent with ARMBE) that contain variables from the instruments defined in Table 1 for the ARM SGP site during the available period. The ARMBE-Land data product will blend multiple ARM observations including the Energy Balance Bowen Ratio Station (EBBR), Soil Water and Temperature System (SWATs) and CO2 Flux (CO2FLX) data sets. The SJSU group will process these datasets with stringent quality controls to remove suspicious data points and average quality-controlled data over a desired temporal resolution (one hour). A qc-flag will be assigned to each variable to indicate how many valid data points are used to get the hourly mean data, consistent with other ARMBE fileds.

54 ENVIRONMENTAL SCIENCES↗

INTEGRATED WORKFLOW MANAGEMENT FOR PARTICLE ACCELERATOR SIMULATION

Supercomputing systems are used for a wide range of computationally demanding tasks in many fields of science and engineering. They play a key role in numerical simulation, in which mathematical models are computed in order to simulate the behavior of physical systems. Scientists and engineers that use supercomputers for numerical simulation often have their productivity limited by the need to manually organize and manage extremely large amounts of data that are often produced and consumed by the software programs run on these systems. Recognizing these limitations, Kitware Inc. (Clifton Park, NY) and SLAC National Accelerator Laboratory (Menlo Park, CA) are developing an advanced software platform that can reduce the cognitive overhead required by knowledge workers when using supercomputers for numerical simulation. Phase I of the project is complete and includes the development of new capabilities for organizing simulation project files, improvements to the user interface and overall usability, and deployment of a “middle tier” server to sit between user desktop machines and supercomputers to offload much of the data management workload. The project also developed prototype software for executing sequences of numerical simulations, and a prototype for migrating supercomputing software to cloud-based computing systems to provide a potential alternative to supercomputers with different logistical and price-to-performance tradeoffs.

Tourtellott, John↗

Optimized Data Transfers Based on the OpenCL Event Management Mechanism

In standard OpenCL programming, hosts are supposed to control their compute devices. Since compute devices are dedicated to kernel computation, only hosts can execute several kinds of data transfers such as internode communication and file access. These data transfers require one host to simultaneously play two or more roles due to the need for collaboration between the host and devices. The codes for such data transfers are likely to be system-specific, resulting in low portability. Here, this article proposes an OpenCL extension that incorporates such data transfers into the OpenCL event management mechanism. Unlike the current OpenCL standard, the main thread running on the host is not blocked to serialize dependent operations. Hence, an application can easily use the opportunities to overlap parallel activities of hosts and compute devices. In addition, the implementation details of data transfers are hidden behind the extension, and application programmers can use the optimized data transfers without any tricky programming techniques. The evaluation results show that the proposed extension can use the optimized data transfer implementation and thereby increase the sustained data transfer performance by about 18% for a real application accessing a big data file.

97 MATHEMATICS AND COMPUTING↗

Final Report UCLA-Thermochemical Storage with Anhydrous Ammonia

In ammonia-based thermochemical energy storage (TCES), ammonia is dissociated endothermically as it absorbs solar energy during the daytime. When energy is required, the reverse reaction releases energy to heat a working fluid such as steam, to produce electricity. Ammonia-based TCES has great advantages of simplicity, low cost reactants, and a strong industrial base in the conventional ammonia industry. The concept has been demonstrated over three decades of research at Australian National University, achieving a 24-hour demonstration of a complete system. At the start of this project, three challenges were identified that would have to be addressed to show that the system is technically and economically viable for incorporation into a CSP plant with an advanced, high temperature power block. All three of these challenges have now been addressed: 1. The ammonia synthesis reaction had not, to our knowledge, been carried out at temperatures consistent with modern power blocks (i.e., ~650°C). The technical feasibility of operating a reactor under high-temperature, near-equilibrium conditions was an unknown, and was therefore a technical risk. The project has successfully demonstrated steam heating to 650°C and energy recovery to steam at the 5 kWt level. 2. The ammonia system has a relatively low enthalpy of reaction combined with gas phase reactants. This is not a direct disadvantage since the reactants themselves are low cost. The challenge lies in storing the required volume of reactants cost effectively. Therefore, a second key goal was to show, through techno-economic analysis, that underground storage technologies can be used to store the energy-rich gas at a cost that is consistent with the SunShot cost goal. We have identified two promising technologies for gas storage: storage in salt caverns has an estimated cost of 1(USD)/kWht and storage in drilled shafts could be on the order of 7(USD)/kWht. Together these two options answer the technical challenge associated with storage of gas phase components. 3. While this project is primarily concerned with high-temperature heat recovery and methods to store the gaseous components, it is also important to consider the feasibility of the entire system. Consequently, an additional goal was to perform analysis to show the feasibility of integrating endothermic reactors within a tower receiver. A conceptual design of an ammonia dissociation receiver/reactor has been developed that fits into the same size cylindrical envelope as the molten salt receiver in SAM, and has the same design thermal capacity. The calculated thermal efficiency of this receiver is 94.6%. Thus, this investigation has established the technical feasibility of a surround field tower system using ammonia dissociation. With these challenges addressed, we proceeded to design a full-scale synthesis and heat recovery system. A model was developed and validated by comparison with our experimental data. A parametric study showed, among other things, the importance of using small tube diameters and spacing to enhance heat transfer. Multi-parameter optimization was used to find a design that minimizes the wall material volume. Finally, cost estimation shows that the ammonia system has good prospects of meeting the Sunshot 15(USD)/kWht target: estimated costs of the entire synthesis system for the 220 MWt plant with 6 hours of storage are 13(USD)/kWht using salt cavern storage and 18(USD)/kWht using shaft drilling. Costs per kWht are even lower with more hours of storage. With the established technology of ammonia synthesis as a starting point, the successes of the project have mitigated technical risks associated with high-temperature synthesis reaction, underground storage, and tower receiver design. Estimated costs are less than 15(USD)/kWht with salt cavern storage. It is now possible to map a time line to commercial deployment that is likely to be shorter and less risky than other thermochemical cycles under active investigation. UCLA has filed a patent that protects the new ideas developed during this project. Discussions are ongoing with potential investors with the aim of partnering for further work. As well as immediate improvements and extra work with the existing experimental system, a key goal is to extend it to a small solar-driven project at an early opportunity.

14 SOLAR ENERGY↗

A Python Tool for Aqueous Plutonium Nitrate Density Law Input Preprocessing in MCNP6

Here, this work develops a predictive density tool in Python, named Plutonium Nitrate Solutions (PuNS), to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer method and an empirical method were implemented into the PuNS tool to generate atom densities for use in MCNP6 material cards. These material cards are directly prepared into an MCNP6 input text file and are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, and plutonium isotope weight percentages. The PuNS tool is validated and verified against the International Criticality Safety Benchmark Evaluation Project Handbook experiments and is observed to predict densities within a root mean square error of 0.89% for the Pitzer method and 1.82% for the empirical method. These errors in density lead to up to 1569 pcm difference in MCNP6 calculated k eff for the Pitzer method and up to a 1751 pcm difference for the empirical method when compared to experimental benchmarks. Simultaneous work is also being performed at Los Alamos National Laboratory and the University of New Mexico to create a similar tool for plutonium chloride solutions, named Plutonium Chloride Solution, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also facilitate an improved understanding of solution systems and a potential relaxation in the conservatism of current aqueous plutonium processing criticality safety limits.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

CO2 and CH4 Fluxes across Polygon Geomorphic Types, Barrow, Alaska, 2006-2010

Carbon flux data are reported as Net Ecosystem Exchange (NEE), Gross Ecosystem Exchange (GEE), Ecosystem Respiration (ER), and Methane (CH4) flux. Measurements were made at 82 plots across various polygon geomorphic classes at research sites on the Barrow Environmental Observatory (BEO), the Biocomplexity Experiment site on the BEO, and the International Biological Program (IBP) site a little west of the BEO. ArcView GIS files available of the Land Cover Type Classifications.This product is a compilation of data from 27 plots as presented in Lara et al. (2012), data from six plots presented in Olivas et al. (2010); and from 49 plots described in (Lara et al. 2014). Measurements were made during the peak of the growing seasons during 2006 to 2010. At each of the measurement plots (except Olivas et al., 2010) four different thicknesses of shade cloth were used to generate CO2 light response curves. Light response curves were used to normalize photosynthetically active radiation that is diurnally variable to a peak growing season average ~400 umolm-2sec-1. At the Olivas et al. (2010) plots, diurnal patterns were characterized by repeated sampling. CO2 measurements were made using a closed-chamber photosynthesis system and CH4 measurements were made using a photo-acoustic multi-gas analyzer. In addition, plot-level measurements for thaw depth (TD), water table depth (WTD), leaf area index (LAI), and normalized difference vegetation index (NDVI) are summarized by geomorphic polygon type. Citations can be found within the related references field. This dataset includes one zipped file, one pdf, and one .txt file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Active Layer and Moisture Measurements for Intensive Site 0 and 1, Utqiagvik (Barrow), Alaska

Thaw depth, relative dielectric permittivity, and soil temperature were collected along three transects within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) near Utqiagvik (Barrow), Alaska. Measurements were acquired along the transect at 3 m intervals on 2011-09-25, 2011-09-26, 2012-07-18, 2012-09-30, 2014-07-02, 2014-08-15, and 2014-09-14 for the L2 transect (intensive site 0), which is about 470 m long. Similarly, measurements were collected every 3 m on 2012-09-30, 2013-09-30, 2014-07-02, 2014-08-14, and 2014-09-23, and every 1 m on 2013-09-30 along the AB transect (intensive site 1) which is about 500 m long. File types in the package are all csv spreadsheets, following the ESS-DIVE csv guidelines (ESS-DIVE CSV v1), organized by transect name, with accompanying data dictionary files containing the filename suffix "_dd" (also csv format). Data collection details can be found in the Methods description of the metadata record. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗

Hydroboost

HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. HydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files. HydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.

Phillips, TylerB. [Idaho National Laboratory (INL)↗

The Role of the U.S. Electric Distribution System in Serving Data Center and Other Large Loads

The rapid expansion of data centers in the United States is reshaping how the electric distribution system must plan for and accommodate large load interconnections. This report evaluates the role of the distribution grid in serving these loads, from small edge facilities to hyperscale campuses. Using national datasets, utility filings, and industry studies, we assess demand growth, reliability requirements, interconnection thresholds, and infrastructure needs at substations and feeders. The analysis highlights the mismatch between fast data center development timelines and slower utility planning and construction cycles, as well as strategies such as phased energization, on-site generation, hosting capacity maps, and structured interconnection frameworks. While focused on data centers, the insights also apply to other high-density loads such as advanced manufacturing, hydrogen production, and electrified transportation. The report concludes with approaches to align planning processes, transparency tools, and regulatory frameworks so utilities can manage new large loads in ways that support a reliable and resilient grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Characterization of Soil Thermal and Electrical Properties along Multiple Hillslope Transects at Teller Road Site, Seward Peninsula, Alaska, 2017

This dataset has been acquired along five-119 m long transects located on the bottom part of the watershed hillslope at the NGEE Arctic Teller Road site at mile marker 27 (TL_MM27) on the Seward Peninsula, Alaska in July and September 2017. The Distributed Temperature Profiling (DTP) system dataset consist in vertically-resolved profile of soil temperature covering the top 0.8 m of soil with 8 cm interval. In addition to DPT data, electrical resistivity tomography (ERT) data, soil moisture, depth to rock or thaw layer thickness (no differentiation) and ground elevations data have been acquired along each of the transects. A UAV-based geotiff mosaic of the investigated site is also provided. The four data types provided with this dataset of 37 files (*.csv, *.tif, *.DATA): (1) soil temperature profiles, (2) ERT data, (3) the physical measurements of the thaw layer, and (4) an orthomosaic GeoTIFF of the transect study area.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

ParCAT: Parallel Climate Analysis Toolkit

Climate science is employing increasingly complex models and simulations to analyze the past and predict the future of Earth's climate. This growth in complexity is creating a widening gap between the data being produced and the ability to analyze the datasets. Parallel computing tools are necessary to analyze, compare, and interpret the simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools to efficiently use parallel computing techniques to make analysis of these datasets manageable. The toolkit provides the ability to compute spatio-temporal means, differences between runs or differences between averages of runs, and histograms of the values in a data set. ParCAT is implemented as a command-line utility written in C. This allows for easy integration in other tools and allows for use in scripts. This also makes it possible to run ParCAT on many platforms – from laptops to supercomputers. ParCAT outputs NetCDF files so it is compatible with existing utilities such as Panoply and UV-CDAT. This paper describes ParCAT and presents results from some example runs on the Titan system at ORNL.

97 MATHEMATICS AND COMPUTING↗

OT Emulation Data Broker

The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-11479 O

Hahn, Andrew↗

OT Emulation Data Broker v.2.0

SAND2021-11479 O The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hahn, Andrew↗

Sun-induced chlorophyll fluorescence/eddy covariance measurements at NGEE Arctic Council site, Seward Peninsula, Alaska, 2022

Sun-induced chlorophyll fluorescence (SIF) is emitted from the chlorophyll antenna complexes during the light harvesting and photophysical reactions of photosynthesis. It is directly coupled with and therefore can be used to estimate photosynthetic electron transport and CO2 assimilation. SIF, when observed at the ecosystem level, provides information about ecosystem functions that complements the net ecosystem exchange (NEE) of CO2, CH4, water vapor, and sensible heat. NEE observations have been conducted with the eddy covariance (EC) approach at the NGEE Arctic Council, Alaska site for years. However, concurrent SIF observations have not been available. In June 2022, we installed the fluorescence automated measurement equipment (FAME) at the NGEE Arctic Council site. The zip file contains 3,187 *.dat files that can be opened with a text editor or in *.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Thaw Depth, Oxyanion Concentrations, and Soil Moisture from Elevated Microtopographic Polygonal Features, Utqiagvik (Barrow), Alaska, 2016 and 2017

Data include results from elevated macrotopographic features soil pore-water oxyanion concentrations, soil moisture, and for samples collected from the Barrow Environmental Observatory and the broader Barrow Peninsula near Utqiagvik, Alaska during September 2016 and July 2017. Samples were collected from the top 20 cm of elevated polygonal tundra microtopograpic features including high-centered polygon centers, flat-centered polygon centers, low-centered polygon rims, the outer edges of drain-thaw lake basins (DTLB), and high centered polygons that underwent accelerated drying due to anthropogenic disturbance (ACC-HCP). This dataset contains two *.csv data files and one *.pdf user guide and is used in Arendt, et.al.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Iron and Phosphorus Geochemistry in High-Centered and Low-Centered Polygon Soils from the Barrow Environmental Observatory, Utqiagvik, Alaska, 2015

This dataset provides chemical characterization of soil cores obtained in triplicate from center and trough positions of a high-centered polygon and center, ridge, and trough positions of a low-centered polygon in the NGEE Arctic research area within the Barrow Environmental Observatory, Utqiagvik, Alaska. Photographs of the 15 collected cores are provided. Cores were collected to thaw depth in early October 2015 and subsequently divided into subsamples for analysis, which included bulk soil horizons (organic or mineral) and finer scale depth increments (minimum 4 cm thickness per increment). Bulk horizons and depth increments were characterized using sequential chemical extractions for Fe and P and with Fe K-edge x-ray absorption spectroscopy. Additional soil parameters such as loss-on-ignition, gravimetric water content, and carbon and nitrogen concentrations were also quantified for bulk horizons. This dataset includes four csv files, one pdf user guide, and one zip folder of *.jpg photos.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗