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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

On the non-existence of stepped-pressure equilibria far from symmetry

The Stepped Pressure Equilibrium Code (SPEC) (Hudson et al 2012 Phys. Plasmas 19 112502) has been successful in the construction of equilibria in 3D configurations that contain a mixture of flux surfaces, islands and chaotic magnetic field lines. In this model, the plasma is sliced into sub-volumes separated by ideal interfaces, and in each volume the magnetic field is a Beltrami field. In the cases where the system is far from possessing a continuous symmetry, such as in stellarators, the existence of solutions to a stepped-pressure equilibrium with given constraints, such as a multi-region relaxed MHD minimum energy state, is not guaranteed but is often taken for granted. Using SPEC, we have studied two different scenarios in which a solution fails to exist in a slab with analytic boundary perturbations. Here we found that with a large boundary perturbation, a certain interface becomes fractal, corresponding to the break up of a Kolmogorov–Arnold–Moser (KAM) surface. Moreover, an interface can only support a maximum pressure jump while a solution of the magnetic field consistent with the force balance condition can be found. An interface closer to break-up can support a smaller pressure jump. We discovered that the pressure jump can push the interface closer to being non-smooth through force balance, thus significantly decreasing the maximum pressure it can support. Our work shows that a convergence study must be performed on a SPEC equilibrium with interfaces close to break-up. These results may also provide insights into the choice of interfaces and have applications in finding out the maximum pressure a machine can support.

3D equilibrium↗
DOE OSTI2022

Photometric redshifts from SDSS images with an interpretable deep capsule network

ABSTRACT Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on ugriz images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of ∼400 000 Sloan Digital Sky Survey galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets (r ≤ 17.8 and zspec ≤ 0.4) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a two-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g. size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g. magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale

Watersheds are the fundamental Earth surface functioning units that connect the land to aquatic systems. Many watershed-scale models represent hydrological processes but not biogeochemical reactive transport processes. This has limited our capability to understand and predict solute export, water chemistry and quality, and Earth system response to changing climate and anthropogenic conditions. Here we present a recently developed BioRT-Flux-PIHM (BioRT hereafter) v1.0, a watershed-scale biogeochemical reactive transport model. The model augments the previously developed RT-Flux-PIHM that integrates land-surface interactions, surface hydrology, and abiotic geochemical reactions. It enables the simulation of (1) shallow and deep-water partitioning to represent surface runoff, shallow soil water, and deeper groundwater and of (2) biotic processes including plant uptake, soil respiration, and nutrient transformation. The reactive transport part of the code has been verified against the widely used reactive transport code CrunchTope. BioRT-Flux-PIHM v1.0 has recently been applied in multiple watersheds under diverse climate, vegetation, and geological conditions. This paper briefly introduces the governing equations and model structure with a focus on new aspects of the model. It also showcases one hydrology example that simulates shallow and deep-water interactions and two biogeochemical examples relevant to nitrate and dissolved organic carbon (DOC). These examples are illustrated in two simulation modes of complexity. One is the spatially lumped mode (i.e., two land cells connected by one river segment) that focuses on processes and average behavior of a watershed. Another is the spatially distributed mode (i.e., hundreds of cells) that includes details of topography, land cover, and soil properties. Whereas the spatially lumped mode represents averaged properties and processes and temporal variations, the spatially distributed mode can be used to understand the impacts of spatial structure and identify hot spots of biogeochemical reactions. The model can be used to mechanistically understand coupled hydrological and biogeochemical processes under gradients of climate, vegetation, geology, and land use conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗
DOE OSTI2023

Progress in the validation of rotor aerodynamic codes using field data

Within the framework of the fourth phase of the International Energy Agency (IEA) Wind Task 29, a large comparison exercise between measurements and aeroelastic simulations has been carried out featuring three simulation cases in axial, sheared and yawed inflow conditions. Results were obtained from more than 19 simulation tools originating from 12 institutes, ranging in fidelity from blade element momentum (BEM) to computational fluid dynamics (CFDs) and compared to state-of-the-art field measurements from the 2 MW DanAero turbine. More than 15 different variable types ranging from lifting-line variables to blade surface pressures, loads and velocities have been compared for the different conditions, resulting in over 250 comparison plots. The result is a unique insight into the current status and accuracy of rotor aerodynamic modeling. For axial flow conditions, a good agreement was found between the various code types, where a dedicated grid sensitivity study was necessary for the CFD simulations. However, compared to wind tunnel experiments on rotors featuring controlled conditions, it remains a challenge to achieve good agreement of absolute levels between simulations and measurements in the field. For sheared inflow conditions, uncertainties due to rotational and unsteady effects on airfoil data result in the CFD predictions standing out above the codes that need input of sectional airfoil data. However, it was demonstrated that using CFD-synthesized airfoil data is an effective means to bypass this shortcoming. For yawed flow conditions, it was observed that modeling of the skewed wake effect is still problematic for BEM codes where CFD and free vortex wake codes inherently model the underlying physics correctly. The next step is a comparison in turbulent inflow conditions, which is featured in IEA Wind Task 47. Doing this analysis in cooperation under the auspices of the IEA Wind Technology Collaboration Program (TCP) has led to many mutual benefits for the participants. The large size of the consortium brought ample manpower for the analysis where the learning process by combining several complementary experiences and modeling techniques gave valuable insights that could not be found when the analysis is carried out individually.

17 WIND ENERGY↗
DOE OSTI2026

NGEE Arctic Authorship Guidelines

Authorship Guidelines were developed to help facilitate trust among team members as we span multiple institutions, scientific disciplines, and career stages. NGEE Arctic was built on a foundation of open science, data sharing, and collaboration. In Phase 4 of the project, it was particularly important to keep this foundation in mind as we develop new collaborations across the Arctic. Included in this package is one *.pdf. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

Iversen, Colleen [ORNL] (ORCID:0000000182933450)↗
DOE OSTI2022

On the perturbation effect and LET dependence of beam quality correction factors in carbon ion beams

Background: In a recent study, we reported beam quality correction factors, f Q , in carbon ion beams using Monte Carlo (MC) methods for a cylindrical and a parallel-plate ionization chamber (IC). A non-negligible perturbation effect was observed; however, the magnitude of the perturbation correction due to the specific IC subcomponents was not included. Furthermore, the stopping power data presented in the International Commission on Radiation Units and Measurements (ICRU) report 73 were used, whereas the latest stopping power data have been reported in the ICRU report 90. Purpose: The aim of this study was to extend our previous work by computing f Q correction factors using the ICRU 90 stopping power data and by reporting IC-specific perturbation correction factors. Possible energy or linear energy transfer (LET) dependence of the f Q correction factor was investigated by simulating both pristine beams and spread-out Bragg peaks (SOBPs). Methods: The TOol for PArticle Simulation (TOPAS)/GEANT4 MC code was used in this study. A 30 × 30 × 50 cm 3 water phantom was simulated with a uniform 10 × 10 cm 2 parallel beam incident on the surface. A Farmer-type cylindrical IC (Exradin A12) and two parallel-plate ICs (Exradin P11 and A11) were simulated in TOPAS using the manufacturer-provided geometrical drawings. The f Q correction factor was calculated in pristine carbon ion beams in the 150–450 MeV/u energy range at 2 cm depth and in the middle of the flat region of four SOBPs. The k Q correction factor was calculated by simulating the f Qo correction factor in a 60 Co beam at 5 cm depth. The perturbation correction factors due to the presence of the individual IC subcomponents, such as the displacement effect in the air cavity, collecting electrode, chamber wall, and chamber stem, were calculated at 2 cm depth for monoenergetic beams only. Additionally, the mean dose-averaged and track-averaged LET was calculated at the depths at which the f Q was calculated. Results: The ICRU 90 f Q correction factors were reported. The p dis correction factor was found to be significant for the cylindrical IC with magnitudes up to 1.70%. The individual perturbation corrections for the parallel-plate ICs were <1.0% except for the A11 p cel correction at the lowest energy. The f Q correction for the P11 IC exhibited an energy dependence of >1.00% and displayed differences up to 0.87% between pristine beams and SOBPs. Conversely, the f Q for A11 and A12 displayed a minimal energy dependence of <0.50%. The energy dependence was found to manifest in the LET dependence for the P11 IC. A statistically significant LET dependence was found only for the P11 IC in pristine beams only with a magnitude of <1.10%. Conclusions: The perturbation and k Q correction factor should be calculated for the specific IC to be used in carbon ion beam reference dosimetry as a function of beam quality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Particle-based modelling of axisymmetric tandem mirror devices

In this work, we describe the use of a 1D-2V quasi-neutral hybrid electrostatic PIC with Monte-Carlo Coulomb collisions and non-uniform magnetic field to model the parallel transport and confinement in an axisymmetric tandem mirror device. End-plugs, based on simple-mirrors, are positioned at each end of the device and fueled with neutral beams (25 and 100 keV) to produce a sloshing ion population and increase the density of the end-plugs relative to the central cell. Results show the formation of a potential difference barrier between the central cell and the end-plugs. This potential confines a large fraction of the low energy thermal ions in the central cell which would otherwise be lost in a simple mirror, demonstrating the advantage of the beam-driven tandem mirror configuration relative to simple mirrors. In addition, we explore the effect of end-plug electron temperature on the confinement time of the device and compare it with theoretical estimates. Finally, we discuss the limitations of the code in its present form and describe the next logical steps to improve its predictive capability such as a fully nonlinear Fokker–Planck collision operator, multiply nested flux surface solutions and modeling the exhaust region up to the wall.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Evidence for an Early Formation of Serenitatis Basin at 4.25 Ga Shifts Lunar Chronology

Troctolite sample 76535, collected in Serenitatis basin during Apollo 17, formed at least 50 km deep, experienced maximum shock pressures of 6 GPa, and has a 40 Ar/ 39 Ar excavation age of 4.25 Ga. Previous work attributed 76535 to the South Pole-Aitken (SPA) basin, presumably dating the SPA-impact and constraining lunar bombardment history. Here we use the iSALE-2D shock-physics code and gravity inversion modeling to determine if instead the Serenitatis impact event excavated 76535. We find nearly 140,000 km 3 of material (∼2% of near-surface ejecta) matching the depth and pressure constraints of 76535 is displaced to the surface during crater collapse of a Serenitatis-like impact event. We conclude that the Serenitatis impact event possibly excavated 76535, redefining its age to 4.25 Ga, 300 My older than the consensus age based on Apollo 17 samples. This finding would provide an important anchor point where lunar chronology where bombardment flux is especially uncertain.

Bjonnes, Evan [Lawrence Livermore National Laborat↗
DOE OSTI2020

An extended moments model of quantum efficiency for metals and semiconductors

The complexity of photocathode designs and detector materials, and the need to model their performance for short pulse durations, response to high frequency photons, presence of coatings and/or thinness of the absorptive layer, necessitates modifications to three-step and moments models of photoemission that are used in simulation codes. Here, methods to include input from computationally intensive approaches, such as density functional theory to model optical properties and transfer matrix approaches to treat emission from the surface or transport past coatings, by means of parametric models are demonstrated. First, a technique to accurately represent optical behavior so as to model reflectivity and penetration depth is given. Second, modifications to bulk models arising from the usage of thin film architectures, and a means to rapidly calculate them, is provided. Third, a parameterization to model the impact of wells associated with coatings and surface layers on the transmission probably is given. In all cases, the methods are computationally efficient and designed to allow for including input from numerically intensive approaches that would otherwise be unavailable for simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

ELM sputter erosion modeling of a tungsten coated small angle slot divertor in DIII-D

We modeled plasma edge localized mode (ELM) sputter erosion for a Small Angle Slot divertor with a tungsten coated region (SAS-VW), designed for experiments in the DIII-D tokamak, and proposed for use in future advanced tokamaks. The simulations use a free-streaming, 1000 eV, C +6 and D +1 ELM impingement model, with SOLPS-ITER, ITMC-DYN, and REDEP/WBC code packages for background plasma, material response, and erosion/redeposition respectively. The results show ELM'ing plasma gross and net tungsten erosion fluxes of the mixed-material C/W surface peaking at the slot entrance region, and an order of magnitude higher than for non-ELMs. The per-pulse erosion, however, remains low, of order 0.5 nm, due to expected moderate ELM frequencies and duration in DIII-D. Here, the ELMs result in a ~25x higher peak sputtered W current leaving the divertor slot region, towards the core plasma, compared to the ELM-free plasma case. The time-integrated escape current, however, may not significantly affect core plasma high-Z contamination concerns, for a 1% ELM duty factor, but may be an issue for higher frequency ELMs. In general, the modeling results appear favorable for effective testing of the SAS-VW divertor in DIII-D, and extrapolation to innovative divertor designs in future ITER-like and DEMO fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Influence of Agricultural Managed Aquifer Recharge (AgMAR) and Stratigraphic Heterogeneities on Nitrate Reduction in the Deep Subsurface

This data package contains input files for TOUGHREACT for a modeling study examining the effects of managed aquifer recharge on agricultural lands on nitrate cycling and transport in the Central Valley of CA near Modesto. The files contain all the geochemical species, reactions, and hydrological parameters for the model. The files are text files used for the TOUGH family of code created by LBNL. To use the files a license is required. https://tough.lbl.gov/licensing-download/toughreact-licensing-download/Accompanying Paper Abstract: Agricultural managed aquifer recharge (AgMAR) is a proposed management strategy whereby surface water flows are used to intentionally flood croplands with the purpose of recharging underlying aquifers. However, legacy nitrate (NO3-) contamination in agriculturally-intensive regions poses a threat to groundwater resources under AgMAR. To address these concerns, we use a reactive transport modeling framework to better understand the effects of AgMAR management strategies (i.e., by varying the frequency, duration between flooding events, and amount of water) on N leaching to groundwater under different stratigraphic configurations and antecedent moisture conditions. In particular, we examine the potential of denitrification and nitrogen retention in deep vadose zone sediments (~15 m) using variable AgMAR application rates on two-dimensional representations of differently textured soils, soils with discontinuous bands/channels, and soils with preferential flow paths characteristic of typical agricultural field sites. Our results indicate that finer textured sediments, such as silt loams, alone or embedded within high flow regions, are important reducing zones providing conditions needed for denitrification. Simulation results further suggest that applying water all-at-once rather than in increments for a fixed volume of recharge transports higher concentrations of NO3- deeper into the profile, which has the potential to exacerbate groundwater quality. This transport into deeper depths can be aggravated by wetter antecedent soil moisture conditions. However, applying water all-at-once also increases denitrification within the vadose zone by promoting anoxic conditions. We conclude that AgMAR management strategies can be designed to enhance denitrification in the subsurface and reduce N leaching to groundwater, while specifically accounting for lithologic heterogeneity, antecedent soil moisture conditions, and depth to the water table. Our findings are potentially relevant to other systems that experience flooding inundation such as riparian corridors, floodplains, wetlands, and other managed landscapes like dedicated recharge basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Measurement and Simulation of Ultra-Low-Energy Ion–Solid Interaction Dynamics

Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here, we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low-energy ion implants can be achieved by either lowering the column voltage or decelerating ions using bias while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found, which is due to lattice enrichment with high-stopping-power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way towards much lower implantation energies while maintaining high spatial resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Demonstration and Automation of Reflected Target Optical Measurement for Heliostats

Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. Since 2022, NREL has been developing a measurement method called the Reflected Target Non-intrusive Assessment (ReTNA) system. This system differs from most established methods in that we perform deflectometry with a pattern of coded targets, identified in space with photogrammetry. Reflected target systems have several advantages over traditional fringe deflectometry systems. Firstly, they can be operated in bright or ambient lighting, a challenge for fringe systems that use a projector and screen. Reflected target systems also can use a much lighter and less expensive target than projector-based systems. Lastly, 2D slope measurement can be solved from a single image, which leads to several advantages for accommodating faster measurements and smaller sized targets. These advantages make ReTNA particularly well-suited for applications where there are space or lighting constraints, like performing heliostat quality assurance on an assembly line. It's also useful when a lightweight, flexible system is needed, like for heliostat developers to quickly measure a new heliostat design at different orientations, to observe gravitational effects on the mirror surface shape. In the last year, significant improvements were made to this tool to make it more useful for these applications. These improvements were focused around validation of the ReTNA measurement system, and automation of the setup and measurement process. First, we present an improved ReTNA layout, for use on the heliostat assembly line. Next, we detail the various changes to the ReTNA software and computer vision methods to automate data collection in this new setup, and lessons learned from this process. The goal with this new setup is to perform a full heliostat surface characterization without removing the mirror from the assembly line. Lastly, we share results from several ReTNA validation studies undertaken over the last year. These include repeated ReTNA measurement on demonstration mirror facets, comparisons with other optical measurement tools, and some studies aimed at quantifying the uncertainty of ReTNA measurement under various constraints (mirror-target spacing, camera resolution, etc.). These results are compared with 2024 HelioCon performance targets, and our planned next steps for the ReTNA measurement system are presented.

CSP↗
DOE OSTI2020

Genomic adaptations of the green alga Dunaliella salina to life under high salinity

Life in high salinity environments poses challenges to cells in a variety of ways: maintenance of ion homeostasis and nutrient acquisition, often while concomitantly enduring saturating irradiances. Dunaliella salina has an exceptional ability to thrive even in saturated brine solutions. This ability has made it a model organism for studying responses to abiotic stress factors. Here we describe the occurrence of unique gene families, expansion of gene families, or gene losses that might be linked to osmoadaptive strategies. We discovered multiple unique genes coding for several of the homologous superfamily of the Ser-Thr-rich glycosyl-phosphatidyl-inositol-anchored membrane family and of the glycolipid 2-alpha-mannosyltransferase family, suggesting that such components on the cell surface are essential to life in high salt. Gene expansion was found in families that participate in sensing of abiotic stress and signal transduction in plants. One example is the patched family of the Sonic Hedgehog receptor proteins, supporting a previous hypothesis that plasma membrane sterols are important for sensing changes in salinities in D. salina. We also investigated genome-based capabilities regarding glycerol metabolism and present an extensive map for core carbon metabolism. We postulate that a second broader glycerol cycle exists that also connects to photorespiration, thus extending the previously described glycerol cycle. Further genome-based analysis of isoprenoid and carotenoid metabolism revealed duplications of genes for 1-deoxy-D-xylulose-5-phosphate synthase (DXS) and phytoene synthase (PSY), with the second gene copy of each enzyme being clustered together. Moreover, we identified two genes predicted to code for a prokaryotic-type phytoene desaturase (CRTI), indicating that D. salina may have eukaryotic and prokaryotic elements comprising its carotenoid biosynthesis pathways. In brief, our genomic data provide the basis for further gene discoveries regarding sensing abiotic stress, the metabolism of this halophilic alga, and its potential in biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Leveraging MARVEL and SPHERE to Demonstrate NEAMS Thermal Hydraulics Codes

The Single Primary Heat Extraction and Removal Emulator (SPHERE) and Microreactor Applications Research Validation and Evaluation (MARVEL) were utilized to demonstrate thermal hydraulics codes of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. A recent long-duration test of a sodium heat pipe conducted at the SPHERE facility was utilized for the validation of the heat pipe code Sockeye. The first 10 hours of operation featured a startup of the heat pipe from room temperature; this portion was modeled with Sockeye and compared to the experimental data. Measurements included several thermocouple measurements across the length of the heat pipe surface. Two of Sockeye’s heat pipe models were applied to experiment, as well as several models of the cooling at the condenser end of the heat pipe. Sockeye results gave a decent match to the experimental data, with notable discrepancy in the condenser section, where experimental data indicated a significant inactive length of the heat pipe. The MARVEL microreactor was modeled through a coupled simulation of System Analysis Module (SAM) and SubChannel Module (SCM). This multiscale coupled simulation was performed as an exercise to demonstrate the compatibility and applicability of these codes for thermal-hydraulic analysis of microreactors. The coupling between the SCM and SAM codes for multiscale modeling of MARVEL, was achieved through a domain overlapping approach. In this example a transient SAM simulation provided boundary conditions to SCM, and SCM provided pressure drop to SAM.

97 - MATHEMATICS AND COMPUTING↗