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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Sensitivity and Uncertainty of the IFR-1 BISON Benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This report summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment. For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. The resulting variations in benchmark predictions were normalized to calculate sensitivities. The strongest sensitivities were identified and used to inform input selections for the UQ. The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because of the wide confidence intervals associated with the benchmark predictions. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark development and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Sensitivity and uncertainty of the IFR-1 BISON benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered for adoption by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This paper summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment.For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. Here, the resulting variations in benchmark predictions were normalized to calculate sensitivities. These sensitivities were then used to inform input selections for the UQ.The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of the benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because the confidence intervals associated with benchmark predictions were wide. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2000

Latitudinal Density Dependence of Magnetic Field Lines Inferred from Polar Plasma Wave Data

Using observations of the electron density, n(sub e), based on measurement of the upper hybrid resonance frequency by the Polar spacecraft Plasma Wave Instrument, we have examined the radial density dependence along field lines in the outer plasmasphere and the near plasmatrough. Sampled L values range from 2.5 to 6.6. Our technique depends on the fact that Polar crosses particular L values at two different points with different radial distance R. In our plasmaspheric data set (n(sub e) > 100/cm3), we find that on average n(sub e) is flat along field lines from the equator up to the latitudes sampled by Polar (R approximately equal to or > 2.0). In the plasmatrough data set (n(sub e) < 100/cm-3), there is on average a mild radial dependence n(sub e) varies as R(exp -1.7).

Goldstein, J.↗
NASA NTRSDate not supplied

A New Statistical Estimate of the Radar Coverage of the Low Earth Orbit Debris Environment

For over three decades, the NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar, Haystack Ultrawideband Satellite Imaging Radar (HUSIR), and Haystack Auxiliary (HAX) radar assets to collect data on the low Earth orbit (LEO) debris environment. Each radar, with its unique beamwidth, altitude and inclination coverage, and limiting size threshold, operates in a beam park mode to statistically sample the orbital debris population in LEO. Provided that these assets are shared with other users, the orbital debris data collection is not continuous; rather, intermittent data collects are acquired and sent to the NASA ODPO. To understand the sampling process conducted by each radar over time and any related observational biases, a Statistical Confirmation of Radar Uniformity or Bias (SCRUB) code has been implemented to model the coverage of these assets for informing future operations, as well as usage of the data collected from these ground-based sensors. For this analysis, Right Ascension of the Ascending Node (RAAN) is used as a metric to measure statistical coverage. A complete survey of the LEO environment is understood to be measurements that sufficiently sample all values of RAAN for each altitude-inclination pair visible from the radar asset. Regions of incompleteness or statistical bias can help inform future observation campaigns. The SCRUB tool evaluates the coverage of the LEO environment, not by examining individual objects that may pass through a sensor’s field of view (FOV), but by determining which orbit planes pass through the FOV. Once a pointing geometry for a radar site, observation time, and range extent are configured by the user, SCRUB computes the inclinations and altitudes that are visible by the sensor. For each inclination-altitude pair, there is a distinct pair of possible RAAN values, corresponding to the ascending and descending orbit passing through that point in the sensor cone. Repeating this process for all points in the beam, and for multiple time periods during an observation window, creates a matrix of all inclination-altitude-RAAN combinations that are visible during a sensor run. This process can then be repeated for all observations within a year (for an annual survey), propagating all the RAAN values to a common epoch, typically the start of a calendar year, and combining the observations to assemble a full estimate of the RAAN coverage of the LEO environment. This RAAN coverage can then be analyzed for uniformity of sampling, within a certain inclination-altitude pair, or between larger regions of the space environment. This paper provides a general overview of the radar assets utilized by ODPO, typical analysis data products assuming circular orbits, and a discussion of the algorithms that feed between modeling and measurement operations. Following the description of the algorithm, estimates of coverage using HUSIR radar data collected from multiple years are developed and compared.

Chris L Ostrom↗
NASA NTRS2024

Preliminary Analyses of Asteroid Bennu Samples Returned by NASA’s OSIRIS-REx Mission

NASA’s OSIRIS-REx mission returned ~122 g of pristine carbonaceous regolith from Bennu on September 24, 2023. The science team is performing analyses of the mineralogy, chemical and isotopic compositions, and physical properties of the samples. The returned samples consist of particles ranging up to 3.5 cm in size with angular and hummocky morphologies predominating. Reflectance spectra over the visible and infrared wavelengths collected during the spacecraft encounter contained features indicating abundant hydrated phyllosilicates, carbonates, magnetite, organic matter, and rare anhydrous silicates. Laboratory analyses confirmed these detections and identified several other major and minor phases including abundant FeNi sulfides, minor hydrated Mg-rich phosphates as encrustations and in veins, and presolar grains. The Bennu samples show evidence for extensive aqueous alteration and resemble the rare and chemically primitive CI carbonaceous chondrites and samples returned from Ryugu by JAXA’s Hayabusa2 mission. Samples of Bennu’s uppermost surface, collected by contact pads, help us to understand how recent impacts and irradiation processes have changed the optical properties of Bennu surface materials measured by remote sensing. The analyses thus far highlight the value of sample return by illustrating the pristine nature of the samples compared to meteorites that have been compromised and altered by exposure to the terrestrial environment.

Lindsay P Keller↗
DOE OSTI2022

Search of strong lens systems in the Dark Energy Survey using convolutional neural networks

We present our search for strong lens, galaxy-scale systems in the first data release of the Dark Energy Survey (DES), based on a color-selected parent sample of 18 745 029 luminous red galaxies (LRGs). We used a convolutional neural network (CNN) to grade this LRG sample with values between 0 (non-lens) and 1 (lens). Our training set of mock lenses is data-driven, that is, it uses lensed sources taken from HST-COSMOS images and lensing galaxies from DES images of our LRG sample. A total of 76 582 cutouts were obtained with a score above 0.9, which were then visually inspected and classified into two catalogs. The first one contains 405 lens candidates, of which 90 present clear lensing features and counterparts, while the other 315 require more evidence, such as higher resolution imaging or spectra, to be conclusive. A total of 186 candidates are newly identified by our search, of which 16 are among the 90 most promising (best) candidates. The second catalog includes 539 ring galaxy candidates. This catalog will be a useful false positive sample for training future CNNs. For the 90 best lens candidates we carry out color-based deblending of the lens and source light without fitting any analytical profile to the data. This method is shown to be very efficient in the deblending, even for very compact objects and for objects with a complex morphology. Finally, from the 90 best lens candidates, we selected 52 systems with one single deflector to test an automated modeling pipeline that has the capacity to successfully model 79% of the sample within an acceptable computing runtime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Stable Water Isotope Data for the East River Watershed, Colorado (2014-2025)

The stable water isotope data for the East River Watershed, Colorado, consists of delta2H (hydrogen) and delta18O (oxygen) values from samples collected at multiple, long-term monitoring sites including streams, groundwater wells, springs, and a precipitation collector used to establish a local meteoric water line (LMWL) for the watershed. These locations represent important and/or unique end-member locations for which stable isotope values can be diagnostic of the connection between precipitation inputs as snow and rain and riverine export. Such locations include drainages underline entirely or largely by shale bedrock, land covered dominated by conifers, aspens, or meadows, and drainages impacted by historic mining activity and the presence of naturally mineralized rock. Developing a long-term record of water isotope values from a diversity of environments is a critical component of quantifying the impacts of both climate change and discrete climate perturbations, such as drought, forest mortality, and wildfire, on water export. Such data may be combined with stream gaging stations co-located at each surface water monitoring site to relate seasonal variations in water export to their stable isotopic signature. Data for liquid water delta2H and delta18O values are reported in units of parts per thousand (per-mil; ‰). This data package contains (1) a zip file (isotope_data_2014-2025.zip) containing a total of 95 files: 96 data files of isotope data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (v6_20260901_flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (v6_20260901_dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type. Missing values within the anion data files are noted as either "-9999" or "0.0" for not detectable (N.D.) data. There are a total of 43 locations containing isotope data. Update on 2022-06-10: versioned updates to this dataset was made along with these changes: (1) updated isotope data for all locations up to 2021-12-31 and (2) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format. Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv). Update on 2023-08-08: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-03-13. The file level metadata and data dictionary files were updated to reflect the additional data added. Update on 2024-03-11: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2024-02-19. Further, revisions to the data files were made to remove incorrect data points (from 1970 and 2001). The reporting format specific files were updated to reflect the additional data added. Update on 2025-05-15: Updates were made to both the data files and reporting format specific files. New available isotope data was added, up until the end of WY2024 (September 30, 2024). International Generic Sample Numbers (IGSNs), when registered, were added to the data files. The reporting format specific files were updated to reflect the additional data added. Update on 2026-09-01: Updates were made to both the data files and reporting format specific files. New available isotope data was added, up until the end of WY2025 (September 30, 2025).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗
DOE OSTI2024

Establishing performance metrics for quantitative non-targeted analysis: a demonstration using per- and polyfluoroalkyl substances

Abstract Non-targeted analysis (NTA) is an increasingly popular technique for characterizing undefined chemical analytes. Generating quantitative NTA (qNTA) concentration estimates requires the use of training data from calibration “surrogates,” which can yield diminished predictive performance relative to targeted analysis. To evaluate performance differences between targeted and qNTA approaches, we defined new metrics that convey predictive accuracy, uncertainty (using 95% inverse confidence intervals), and reliability (the extent to which confidence intervals contain true values). We calculated and examined these newly defined metrics across five quantitative approaches applied to a mixture of 29 per- and polyfluoroalkyl substances (PFAS). The quantitative approaches spanned a traditional targeted design using chemical-specific calibration curves to a generalizable qNTA design using bootstrap-sampled calibration values from “global” chemical surrogates. As expected, the targeted approaches performed best, with major benefits realized from matched calibration curves and internal standard correction. In comparison to the benchmark targeted approach, the most generalizable qNTA approach (using “global” surrogates) showed a decrease in accuracy by a factor of ~4, an increase in uncertainty by a factor of ~1000, and a decrease in reliability by ~5%, on average. Using “expert-selected” surrogates ( n = 3) instead of “global” surrogates ( n = 25) for qNTA yielded improvements in predictive accuracy (by ~1.5×) and uncertainty (by ~70×) but at the cost of further-reduced reliability (by ~5%). Overall, our results illustrate the utility of qNTA approaches for a subclass of emerging contaminants and present a framework on which to develop new approaches for more complex use cases. Graphical Abstract

Pu, Shirley (ORCID:0000000201223797)↗
NASA NTRS1985

Role of Hydrogen and Structure on CMSX-2

The goal was to characterize and understand the detailed effect of hydrogen on the tensile and fatigue behavior of single crystals of CMSX-2. Specimens were solutionized, air cooled, and then aged in one of two ways. The resultant macro and microstructure included a pronounced dendritic structure with numerous low angle boundaries in the interdendritic region and on the average a high level of porosity with a large variation in size and distribution. Hydrogen permeability and diffusivity in this material was found to be very low at room temperature. Hydrogen concentration studies on thin samples yielded values significantly higher than found for similar charging conditions in nickel and stainless steels. The tensile mechanical properties were found to depend on hydrogen concentration. SEM observations of the brittle subsurface zone revealed a strong correlation between crack initiation sites and voids just beneath the surface. The hollow and solid samples were compared to better understand the influence of increased charged volume on the fatigue behavior.

Baker, C. L.↗
DOE OSTI2025

NLR HPC Eagle GPU Node Metrics

Ganglia node metrics and iLO (Integrated Lights Out) power data captured from six representative Eagle GPU nodes The Eagle HPC operated at NLR from 2019 through 2024. Eagle was a 2,000-node, 8-petaflop system. This dataset is a representative sample of metrics for 6 of the GPU nodes. Each GPU node contained 2 CPUs and 2 GPUs. Data provided in compressed CSV format. Ganglia and iLO Power Time Series Fields ts: Timestamp dv: Device / Node - Rack and Unit - r103u17 == r(ack)103u(nit)17 mt: Metric (only present for Ganglia) vl: Value - Value in watts for iLO power (instantaneous value at sampling time) or specified Ganglia metric below Ganglia Metrics Metric name -- Metric description -- Unit cpu_aidle -- Percent of time since boot idle CPU -- Percent cpu_idle -- Percent CPU idle -- Percent cpu_nice -- Percent CPU nice -- Percent cpu_speed -- Speed in MHz of CPU -- MHz cpu_user -- Percent CPU user -- Percent cpu_wio -- The percentage of CPU Wait I/O -- Percent gpu0_bar1_memory -- Used GPU bar1 memory -- MB gpu0_decoder_util -- GPU decoder utilization -- Percent gpu0_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu0_encoder_util -- GPU encoder utilization -- Percent gpu0_fan -- Fan speed -- RPM gpu0_fb_memory -- Used GPU framebuffer memory -- MB gpu0_graphics_clock_report -- Current clock speeds for the device -- MHz gpu0_mem_total -- Memory total -- MB gpu0_mem_util -- Memory utilization -- Percent gpu0_power_usage_report -- Power usage report -- Watts gpu0_temp -- GPU 1 temperature -- Celsius gpu1_bar1_memory -- Used GPU bar1 memory -- MB gpu1_decoder_util -- GPU decoder utilization -- Percent gpu1_ecc_db_error -- Total ECC error counts for the GPU -- Number gpu1_encoder_util -- GPU encoder utilization -- Percent gpu1_fan -- Fan speed -- RPM gpu1_fb_memory -- Used GPU framebuffer memory -- MB gpu1_graphics_clock_report -- Current clock speeds for the GPU -- MHz gpu1_mem_total -- Memory total -- MB gpu1_mem_util -- Memory utilization -- MB gpu1_power_usage_report -- Power usage report -- Watts gpu1_temp -- GPU 1 temperature -- Celsius ipmi_cpu1_temp -- CPU 1 temperature -- Celsius ipmi_cpu2_temp -- CPU 2 temperature -- Celsius ipmi_inlet_ambient_temp -- Temperature measured at intake -- Celsius ipmi_vr_p1_temp -- CPU 1 voltage regulator temperature -- Celsius ipmi_vr_p2_temp -- CPU 2 voltage regulator temperature -- Celsius mem_buffers -- Amount of buffered memory -- Bytes mem_cached -- Amount of cached memory -- Bytes mem_free -- Amount of available memory -- Bytes mem_shared -- Amount of shared memory -- Bytes mem_total -- Amount of available memory -- Bytes

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2017

Priority Science Targets for Future Sample Return Missions within the Solar System Out to the Year 2050

The Astromaterials Acquisition and Curation Office (henceforth referred to herein as NASA Curation Office) at NASA Johnson Space Center (JSC) is responsible for curating all of NASA's extraterrestrial samples. JSC presently curates 9 different astromaterials collections: (1) Apollo samples, (2) LUNA samples, (3) Antarctic meteorites, (4) Cosmic dust particles, (5) Microparticle Impact Collection [formerly called Space Exposed Hardware], (6) Genesis solar wind, (7) Star-dust comet Wild-2 particles, (8) Stardust interstellar particles, and (9) Hayabusa asteroid Itokawa particles. In addition, the next missions bringing carbonaceous asteroid samples to JSC are Hayabusa 2/ asteroid Ryugu and OSIRIS-Rex/ asteroid Bennu, in 2021 and 2023, respectively. The Hayabusa 2 samples are provided as part of an international agreement with JAXA. The NASA Curation Office plans for the requirements of future collections in an "Advanced Curation" program. Advanced Curation is tasked with developing procedures, technology, and data sets necessary for curating new types of collections as envisioned by NASA exploration goals. Here we review the science value and sample curation needs of some potential targets for sample return missions over the next 35 years.

McCubbin, F. M.↗
DOE OSTI2024

Total metal, carbon, anion, iron speciation, and sulfide concentrations; Slate River, East River, and Trail Creek surface water and floodplains, Crested Butte, CO; May 2023–August 2023

This data package comprises analytical results and metadata from stream and groundwater samples collected from the Slate River, East River, Trail Creek, and their respective floodplains. This dataset contains five files: (1) a samples file (2023_SFA_Field_samples.csv) that contains site information; (2) a chemical analysis data file (2023_FieldWaterSampleData_IC__ICPOES__ICPMS__TOC__Fe__S_chem_data.csv) that contains sample analysis values; (3) a file-level metadata file (flmd.csv) that lists each file contained in the dataset with associated metadata; (4) a data dictionary file (dd.csv) that contains column/row headers used throughout the files along with definitions, units, and data types; and (5) a methods file (methods.csv) that contains ID, type, description, instrument, and lab information for each method.The samples’ anion concentrations were measured using ion chromatography (IC), total metal concentrations using inductively coupled plasma emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS), non-purgeable organic carbon using total organic carbon (TOC) analysis, dissolved sulfide concentration using methylene blue spectrophotometry, and iron speciation using the ferrozine assay. To support bulk chemical analyses and colloid characterization, samples were collected from multiple depths ranging from the surface to 3.5 meters below ground.Update on 2024-10-18: Updates were made to the 2023_FieldWaterSampleData_IC__ICPOES__ICPMS__TOC__Fe__S_chem_data.csv and dd.csv files to correct units (ppb instead of ppm).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Electron Scattering from 1-Methyl-5-Nitroimidazole: Cross-Sections for Modeling Electron Transport through Potential Radiosensitizers

In this study, we present a complete set of electron scattering cross-sections from 1-Methyl-5-Nitroimidazole (1M5NI) molecules for impact energies ranging from 0.1 to 1000 eV. This information is relevant to evaluate the potential role of 1M5NI as a molecular radiosensitizers. The total electron scattering cross-sections (TCS) that we previously measured with a magnetically confined electron transmission apparatus were considered as the reference values for the present analysis. Elastic scattering cross-sections were calculated by means of two different schemes: The Schwinger multichannel (SMC) method for the lower energies (below 15 eV) and the independent atom model-based screening-corrected additivity rule with interferences (IAM-SCARI) for higher energies (above 15 eV). The latter was also applied to calculate the total ionization cross-sections, which were complemented with experimental values of the induced cationic fragmentation by electron impact. Double differential ionization cross-sections were measured with a reaction microscope multi-particle coincidence spectrometer. Using a momentum imaging spectrometer, direct measurements of the anion fragment yields and kinetic energies by the dissociative electron attachment are also presented. Cross-sections for the other inelastic channels were derived with a self-consistent procedure by sampling their values at a given energy to ensure that the sum of the cross-sections of all the scattering processes available at that energy coincides with the corresponding TCS. This cross-section data set is ready to be used for modelling electron-induced radiation damage at the molecular level to biologically relevant media containing 1M5NI as a potential radiosensitizer. Nonetheless, a proper evaluation of its radiosensitizing effects would require further radiobiological experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors

Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals’ health and ultimately the consequences of anthropogenic stressors on populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microhardness Distribution of Long Magnesium Block Processed through Powder Metallurgy

Powder metallurgy is a popular method of making raw powders into specific shaped samples. However, the pressure distribution and the microhardness difference within the sample are nonnegligible and unclear when the sample is long or exceeds a specific size. In this study, the long magnesium blocks, with a ratio of about 2.8 between the sample height and the sample side length, are successfully synthesized under three uniaxial and two biaxial conditions. Then, the sample hardness values on the outer surface and the center plane are tested to study the microhardness distribution. The modified analytical expression indicates that the normal pressure exponentially decreases along the compression direction, which is consistent with the hardness distribution trend. Because higher pressure leads to a more compact arrangement of the powders, more metal bonds are formed after sintering. During the first pressing, the sidewall pressure makes the surface hardness higher. The secondary reverse compression mainly improves the bottom and core hardness due to the re-orientation and re-location of the powders. The obtained relationship between the applied pressure and the hardness distribution is instructive in predicting and improving the sample quality.

Wang, Jiaying↗
NASA NTRS1996

Digital Fringe Counting for Intrinsic Fabry-Perot Interferometers

A digital dual-wavelength method of demodulating long (17cm) Intrinsic Fabry-Perot Interferometers (IFPI) is presented. The method builds upon previous techniques using small shifts in the lasing wavelength of a laser diode induced by changes in the driving current. The intensity of the light reflected from the IFPI is sampled at two carefully selected values of laser diode drive current. Digital logic is then used to count fringes based upon these two sampled values. Experimental verification of the method is described.

Froggatt, Mark↗
DOE OSTI2020

Long Term Assessment of Radiocesium in Deer, Fish, Soil, and Vegetation at the Savannah River Site

Throughout the Savannah River Site's (SRS) operational history, many radionuclides have been released into the environment. However, due to fallout from weapons testing, the amount released from SRS, its persistence in the environment, and the seclusion of the Site, radiocesium (Cs-137) is one of the most critical radionuclides in the SRS environment. The Effective half-life (Te) is the time it takes for a radionuclide in the environment to decrease by 50% of its initial amount. There are three means of radionuclide removal: Physical: Radioactive decay, sedimentation, and washout; Chemical: Changes in pH, oxidation state or adsorption; Biological: Changes in the food web or translocation. Effective half-life (T{sub e}) = log{sub e}2/λ{sub e} Where λ{sub e} is estimated from the slopes of loge-transformed Cs-137 activity concentrations regressed on year. The objective of this work was to calculate the effective half-life of Cs-137 in various biota at SRS and to perform an assessment of the changes in the effective half life over time. Compared to 2013 data, there is a slight increase in the effective half-lives for fish at most sampling locations. This effective half-life increase is an indication that the rate of Cs-137 loss is starting to plateau. The effective half-life of Cs-137 in SRS fish ranges from 4-11 years. The effective half-life of Cs-137 in soil at the Creek plantation is about 15 years. The effective half-life of Cs-137 in grassy vegetation at the Creek Plantation is about 14 years. The effective half-life of deer hunted on the SRS is about 15.5 years. After termination of all reactor activity by 1980, the Cs-137 activity began to drop drastically.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗