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At least 1,513 records · Page 84

Different approaches to modeling the LANSCE H{sup −} ion source filament performance

An overview of different approaches to modeling of hot tungsten filament performance in the Los Alamos Neutron Science Center (LANSCE) H{sup −} surface converter ion source is presented. The most critical components in this negative ion source are two specially shaped wire filaments heated up to the working temperature range of 2600 K–2700 K during normal beam production. In order to prevent catastrophic filament failures (creation of hot spots, wire breaking, excessive filament deflection towards source body, etc.) and to improve understanding of the material erosion processes, we have simulated the filament performance using three different models: a semi-empirical model, a thermal finite-element analysis model, and an analytical model. Results of all three models were compared with data taken during LANSCE beam production. The models were used to support the recent successful transition from the beam pulse repetition rate of 60 Hz–120 Hz.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)

This dataset contains layer-wise powder bed images from three different powder bed printing technologies – laser powder bed fusion, electron beam powder bed fusion, and binder jetting. This dataset was collected and annotated using the internally-developed Peregrine software tool and is designed primarily to facilitate research into anomaly defect detection using image segmentation or similar techniques. A total of 20 layers are provided for each printing technology, with each layer of data consisting of one or more calibrated images and an annotation file containing pixel-wise ground truth labels. The ground truths were labeled by domain experts, typically printer technicians. Data in this release were collected at Oak Ridge National Laboratory between 2016 and 2020 and were compiled in March 2021.

36 MATERIALS SCIENCE↗

A Comparative Study of the Efficacy of Local/Global and Parametric/Nonparametric Machine Learning Methods for Establishing Structure–Property Linkages in High-Contrast 3D Elastic Composites

Reduced-order structure–property (S-P) linkages play a pivotal role in the tailored design of materials for advanced engineering components. There is a critical need to distill these from the simulation datasets aggregated using sophisticated, computationally expensive, physics-based numerical tools (e.g., finite element methods). The recent emergence of materials data science approaches has opened new avenues for addressing this challenge. In this paper, we critically compare the relative merits of the application of four distinct machine learning approaches for their efficacy in extracting microstructure-property linkages from the finite element simulation data aggregated on high-contrast elastic composites with different microstructures. The machine learning approaches selected for the study have included different combinations of local/global and parametric/nonparametric approaches. Furthermore, the nonparametric approaches selected for this study are based on Gaussian Process (GP) models that allow for a formal treatment of uncertainty quantification in the predicted values. The predictive performances of these different approaches have been compared against each other using rigorous cross-validation error metrics. Furthermore, their sensitivity to both the dataset size and dimensionality has been investigated.

36 MATERIALS SCIENCE↗

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report October 1–December 31, 2012

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real-time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, we calculate the ratio of the actual number of processed data records received daily at the Data Archive to the expected number of data records. The results are tabulated by (1) individual datastream, site, and month for the current year and (2) site and fiscal year dating back to 1998.

54 ENVIRONMENTAL SCIENCES↗

Scanning structural mapping at the Life Science X-ray Scattering Beamline

This work describes the instrumentation and software for microbeam scattering and structural mapping at the Life Science X-ray Scattering (LiX) beamline at NSLS-II. Using a two-stage focusing scheme, an adjustable beam size between a few micrometres and a fraction of a millimetre is produced at the sample position. Scattering data at small and wide angles are collected simultaneously on multiple Pilatus detectors. A recent addition of an in-vacuum Pilatus 900k detector, with the detector modules arranged in a C-shaped configuration, has improved the azimuthal angle coverage in the wide-angle data. As an option, fluorescence data can be collected simultaneously. Fly scans have been implemented to minimize the time interval between scattering patterns and to avoid unnecessary radiation damage to the sample. For weakly scattering samples, an in-vacuum sample environment has been developed here to minimize background scattering. Data processing for these measurements is highly sample-specific. To establish a generalized data process workflow, first the data are reduced to reciprocal coordinates at the time of data collection. The users can then quantify features of their choosing from these intermediate data and construct structural maps. As examples, results from in-vacuum mapping of onion epidermal cell walls and 2D tomographic sectioning of an intact poplar stem are presented.

36 MATERIALS SCIENCE↗

Augmented Topological Descriptors of Pore Networks for Material Science

One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO 2 in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. As a result, we also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material.

36 MATERIALS SCIENCE↗

Lidar - ESRL WindCube 200s, Wasco Airport - Processed Data

The available "Readme" file introduces the basics of the Doppler lidar data and offers a detailed description of the variables present in the data files. For those with any further questions about the data and its interpretation, contact either Alan Brewer ( ) or Sunil Baidar ( ). It is highly recommended to discuss any planned use of the data with National Oceanic and Atmospheric Administration-Chemical Sciences Division (NOAA-CSD) scientists. For more information, refer to the Readme file: "noaa-esrl-wascolidar-readme.docx."

17 WIND ENERGY↗

THE MEASUREMENT, TREATMENT, AND IMPACT OF SPECTRAL COVARIANCE AND BAYESIAN PRIORS IN INTEGRAL -FIELD SPECTROSCOPY OF EXOPLANETS

The recovery of an exoplanet’s atmospheric parameters from its spectrum requires accurate knowledge of the spectral errors and covariances. Unfortunately, the complex image processing used in high-contrast integral-field spectrograph (IFS) observations generally produces spectral covariances that are poorly understood and often ignored. In this work, we show how to measure the spectral errors and covariances and include them self-consistently in parameter retrievals. By combining model exoplanet spectra with a realistic noise model generated from the Gemini Planet Imager (GPI) early science data, we show that ignoring spectral covariance in high-contrast IFS data can both bias inferred parameters and lead to unreliable confidence regions on those parameters. This problem is made worse by the common practice of scaling the χ {sup 2} per degree of freedom to unity; the input parameters then fall outside the 95% confidence regions in as many as ∼80% of noise realizations. The biases we observe can approach the typical levels of precision achieved in high-contrast spectroscopy. Accounting for realistic priors in fully Bayesian retrievals can also have a significant impact on the inferred parameters. Plausible priors on effective temperature and surface gravity can vary by an order of magnitude across the confidence regions appropriate for objects with weak age constraints; priors for objects with good age constraints are dominated by modeling uncertainties. Our methods are directly applicable to existing high-contrast IFSs including GPI and SPHERE, as well as upcoming instruments like CHARIS and, ultimately, WFIRST-AFTA.

79 ASTRONOMY AND ASTROPHYSICS↗

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗

Dissolution zone model of the oxide structure in additively manufactured dispersion-strengthened alloys

The structural evolution of oxides in dispersion-strengthened superalloys during laser-powder bed fusion is considered in detail. Alloy chemistry and process parameter effects on oxide structure are assessed through a parameter study on the model alloy Ni-20Cr, doped with varying concentrations of Y 2 O 3 and Al. Small angle neutron scattering measurements of the dispersoid size distribution show the dispersoid size increases with higher laser power, slower scan speed, and increasing Y 2 O 3 and Al content. Complementary electron microscopy measurements reveal reactions between Y 2 O 3 and Al, even in nanoscale dispersoids, and the presence of micron-scale oxide slag inclusions in select specimens. A scaling analysis of mass and momentum transport within the melt pool, presented here, establishes that diffusional structural evolution mechanisms dominate for nanoscale dispersoids, while fluid forces and advection become significant for larger slag inclusions. These findings are developed into a theory of dispersoid structural evolution, integrating quantitative models of diffusional processes – dispersoid dissolution, nucleation, growth, coarsening – with a reduced order model of time-temperature trajectories of fluid parcels within the melt pool. Calculations of the dispersoid size in single-pass melting reveal a zone in the center of the melt track in which the oxide feedstock fully dissolves. Within this zone the final Y 2 O 3 size is independent of feedstock size and determined by nucleation and growth kinetics. If the dissolution zones of adjacent melt tracks overlap sufficiently with each other to dissolve large oxides, formed during printing or present in the powder feedstock, then the dispersoid structure throughout the build volume is homogeneous and matches that from a single pass within the dissolution zone. Gaps between adjacent dissolution zones result in oxide accumulation into larger slag inclusions. Predictions of final dispersoid size and slag formation using this dissolution zone model match the present experimental data and explain process-structure linkages speculated in the open literature.

36 MATERIALS SCIENCE↗

Persistence and Plasticity in Conifer Water–Use Strategies

The selective use of seasonal precipitation by vegetation is critical to understanding the residence time and flow path of water in watersheds, yet there are limited datasets to test how climate alters these dynamics. Here, we use measurements of the seasonal cycle of tree ring δ 18 O for two widespread conifer species in the Rocky Mountains of North America to provide a multi-decadal depiction of the seasonal origins of forest water use. The results show that while the conifer tree stands had a dominant preference for use of snowmelt, there were multi-annual periods over the last four decades when use of summer precipitation was preferential. Utilization of summer rain emerged during years with increased snowfall and tree growth, suggesting that summer rain enhanced the transpiration stream only during the periods of highest water use. We hypothesize this could be explained through shallowing of the root profile during wetter periods and/or through the influence of changing water table depths on the residence time of summer precipitation in the root zone. We suggest the tree ring proxy approach used here could be applied in other watersheds to provide critical insight into the temporal dynamics of plant water use that could not be inferred from short measurement campaigns. Furthermore, these data on the seasonal origins of forest water are critical for understanding forest vulnerability to drought, the processes that affect precipitation pathways and residence time in watersheds and the interpretation of tree ring proxy data.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic switching by the Lac repressor is based on two-state Monod–Wyman–Changeux allostery

High-resolution NMR spectroscopy enabled us to characterize allosteric transitions between various functional states of the dimeric Escherichia coli Lac repressor. In the absence of ligands, the dimer exists in a dynamic equilibrium between DNA-bound and inducer-bound conformations. Binding of either effector shifts this equilibrium toward either bound state. Analysis of the ternary complex between repressor, operator DNA, and inducer shows how adding the inducer results in allosteric changes that disrupt the interdomain contacts between the inducer binding and DNA binding domains and how this in turn leads to destabilization of the hinge helices and release of the Lac repressor from the operator. Based on our data, the allosteric mechanism of the induction process is in full agreement with the well-known Monod–Wyman–Changeux model.

59 BASIC BIOLOGICAL SCIENCES↗

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering↗

Microdosing and Other Phase 0 Clinical Trials: Facilitating Translation in Drug Development

A number of drivers and developments suggest that microdosing and other phase 0 applications will experience increased utilization in the near-to-medium future. Increasing costs of drug development and ethical concerns about the risks of exposing humans and animals to novel chemical entities are important drivers in favor of these approaches, and can be expected only to increase in their relevance. An increasing body of research supports the validity of extrapolation from the limited drug exposure of phase 0 approaches to the full, therapeutic exposure, with modeling and simulations capable of extrapolating even non-linear scenarios. An increasing number of applications and design options demonstrate the versatility and flexibility these approaches offer to drug developers including the study of PK, bioavailability, DDI, and mechanistic PD effects. PET microdosing allows study of target localization, PK and receptor binding and occupancy, while Intra-Target Microdosing (ITM) allows study of local therapeutic-level acute PD coupled with systemic microdose-level exposure. Applications in vulnerable populations and extreme environments are attractive due to the unique risks of pharmacotherapy and increasing unmet healthcare needs. Lastly, all phase 0 approaches depend on the validity of extrapolation from the limited-exposure scenario to the full exposure of therapeutic intent, but in the final analysis the potential for controlled human data to reduce uncertainty about drug properties is bound to be a valuable addition to the drug development process.

60 APPLIED LIFE SCIENCES↗

NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest near Crested Butte, CO with remotely sensed data including imaging spectroscopy. The flight box design encompassed the watersheds, and flight design targeted a minimum of 30% overlap between adjacent flight lines. The total area surveyed was 334 km2 across 72 lines. Flight lines were oriented north-south for consistency in solar illumination geometry. Seven days were required to cover the flight area. Some areas were flown additional times to improve data quality or temporal coincidence between airborne acquisitions and field sampling. In total, 102 lines were collected and can be downloaded here: https://portal.nersc.gov/wfsfa/doi-10-15485-1617204/. The instrument used for the acquisition was an Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), which records radiance within 426 contiguous spectral bands in the wavelength range from 380 to 2510 nm. The instrument was flown at a target aboveground altitude of 1000 m for a processed data spatial resolution of 1 m. These data are non-orthorectified, radiance data that require further processing prior to use as a surface reflectance data set.

2018 NEON and 2025 CHESS Campaigns↗

FTICR-MS and Biochemical Transformation Data from Global Inland River Water and Sediment Associated with: "Organic Matter Transformations are Disconnected Between Surface Water and the Hyporheic Zone"

This data package is associated with the publication "Organic Matter Transformations are Disconnected Between Surface Water and the Hyporheic Zone" submitted to Biogeosciences (Stegen et al., 2022). The study aims to understand how the diversity of OM transformations varies across surface and subsurface components of river corridors using inland surface water and sediments collected along river corridors across the contiguous United States. Sediment extracts and water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This dataset is comprised of one folder (WHONDR_S19S) which contains (1) a subfolder with R scripts used to process the data and to calculate biochemical transformations, (2) processed FTICR-MS data as csv files, sample collection metadata and climate data as csv files, (3) biochemical transformations profile, classifications and database as csv files, and (4) a readme file with more information regarding WHONDRS raw FTICR-MS data and processing scripts. Outside of the main folders there is a csv containing file-level metadata and a csv data dictionary defining column headers for all csv files contained in the data package. The samples were part of a WHONDRS (https://whondrs.pnnl.gov) study. The raw, unprocessed FTICR-MS data with additional data can be found at doi:10.15485/1729719 for sediments and doi:10.15485/1603775 for water. This data package contains the processed data used in the associated manuscript.

54 ENVIRONMENTAL SCIENCES↗

A Mitigation Strategy for the Prediction Inconsistency of Neural Phase Pickers

Neural phase pickers—neural networks designed and trained to pick seismic phase arrivals—have proven to be a powerful tool for developing earthquake catalogs. However, these pickers suffer from prediction inconsistency in which the results they produce change, sometimes substantially, even under a small perturbation to the input waveform. This problem has not been addressed by the developers and users of these pickers. In this study, we show how prediction inconsistency can negatively affect the completeness of earthquake catalogs developed using neural phase pickers. Further, we show that simply using a small step size for the sliding window when processing continuous waveform data and aggregating the results significantly mitigates this problem. We also highlight the importance of training datasets for increasing the consistency and other performance metrics.

58 GEOSCIENCES↗

"Development and Commercialization of Alternative Carbon Precursors and Conversion Technologies" (CRADA Final Report)

The overall objective of the collaborative research performed by the Oak Ridge National Laboratory (ORNL) and the Dow Chemical Company under this Cooperative Research And Development Agreement (CRADA NFE-10-02991) was to develop and establish pathways to commercialize new carbon fiber precursor and conversion technology. This technology is to produce alternative polymer fiber precursor formulations as well as scaled energy-efficient advanced conversion technology to enable continuous mode conversion to obtain carbonized fibers that are technically and economically viable in industrial markets such as transportation, wind energy, infrastructure and oil drilling applications. There have been efforts in the past to produce a low cost carbon fiber. These attempts have to be interpreted against the backdrop of the market needs at the time, which were strictly military aircraft and high-end aerospace components. In fact, manufacturing costs have been reduced from those days to current practice, where both process optimization and volume production have enabled carbon fiber to become available at prices below $20/lb. However, the requirements of the lucrative aerospace market limits further price reductions from current practice. This approach is different because specific industrial applications are targeted, most specifically wind turbine blade and light vehicle transportation, where aircraft grade carbon fiber is not required. As a result, researchers are free to adjust both manufacturing process and precursor chemistry to meet the relaxed physical specifications at a lower cost. This report documents the approach and findings of this cooperative research in alternative precursors and advanced conversion for production of cost-effective carbon fiber for energy missions. Due to export control, proprietary restrictions, and CRADA protected data considerations, specific design details and processing parameters are not included in this report.

01 COAL, LIGNITE, AND PEAT↗