SEARCH · Engineering Papers

Results for “sampling variability”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,675 records · Page 93

All sources NASA NTRS DOE OSTI

DOE OSTI2025

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Surface water nitrogen and sediment potential nitrate reduction rates, nutrient stocks, and stable isotopes from nine wetlands at the Tanglewood Biological Station, Alabama

This dataset supports a broader study investigating wetland hydrologic and biogeochemical responses to inundation disturbances. Bimonthly surface water and sediment sampling events were conducted at nine wetland sites situated within the Tanglewood Biological Station in Alabama from April 2023 to February 2024. The contents included in the data package include surface water nitrogen (nitrogen oxides and ammonium) and sediment potential nitrate reduction rates (measured as potential denitrification and dissimilatory nitrate reduction to ammonium processing), nutrient stocks (total carbon, total nitrogen, and organic matter), and stable isotopes (carbon and nitrogen). Water level data related to each wetland location can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/2530253 (Kirker et al., 2024) and related water geochemistry data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3001967 (Forbes et al., 2025). In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata and international generic sample numbers (IGSNs); (4) readme; (5) the field protocol; and (6) a subfolder with sample data. The sample data subfolder contains (1) sediment potential denitrification rate, (2) sediment potential dissimilatory nitrate reduction to ammonium (DNRA) rate, (3) sediment total carbon and nitrogen content, (4) sediment stable isotopes (delta nitrogen-15 and delta carbon-13), (5) sediment percent organic matter, (6) surface water nitrous oxides, (7) surface water ammonium, and (8) methods codes. All files are .csv or .pdf.

Ammonium↗

DOE OSTI2025

Compact in situ probe for magnetotransport measurements of 2D materials under variable tensile strain

The recent development of freestanding oxide membranes has opened new opportunities for strain engineering of transition metal oxides beyond values accessible in bulk samples. While a number of studies have been performed with fixed strain, the ability to dynamically control the strain state during measurement would be greatly enabling. To this end, we present an in situ uniaxial strain probe optimized for transport measurements of tensile-strained 2D or quasi-2D materials down to 2 K. Utilizing a flexible polyimide substrate as the stress transfer medium, our platform simplifies the sample preparation process and allows precise alignment of strain fields relative to the crystalline axes. An in situ optical microscope monitors the macroscopic strain state operando and makes it possible to complete an entire magnetotransport study at cryogenic temperatures under continuous strain variations. We demonstrate the capabilities of the probe on a freestanding LaNiO 3 membrane, where we induce tensile strain up to 8% and observe a corresponding strong transport anisotropy. In view of the rapid developments in low-dimensional materials synthesis and the plethora of novel quantum phenomena they exhibit, this strain probe provides general instrumentation for examining and controlling these properties via strain.

2D materials↗

DOE OSTI2024

First Report and Molecular Variability of Belonolaimus longicaudatus Associated with Turfgrass in Maryland

Abstract Turfgrass is a crop used extensively in athletic fields and golf courses in Maryland. A soil sample collected in July 2023 from an athletic field in Baltimore County, Maryland, part of a turfgrass nematode survey, containedBelonolaimus longicaudatus. In the southeastern United States,B. longicaudatusis an economically important pathogen of warm season turfgrass. The density was four individuals/100 cm 3 of soil, and no visual symptoms were observed in the bermudagrass field. Morphological features and morphometrics of males and females were consistent withB. longicaudatusand placed the Maryland population in a subclade that was geographically represented by populations from north and west Florida, Texas, and South Carolina. Sequencing of the internal transcribed spacer region ITS1 and ITS2 and 28S large ribosomal subunit D2-23 expansion region confirmed the species' identity. Phylogenetic trees and parsimony network analysis placed the Maryland isolate in a large grouping ofB. longicaudatuspopulations including those from Alabama, Delaware, Florida, Indiana, Mississippi, South Carolina, and Texas. To our knowledge, this is the first report ofB. longicaudatusin Maryland.

Zoology↗

DOE OSTI2025

Pyrogenic Organic Matter Laboratory Experiment: Aerobic Respiration and Geochemistry from Variably Inundated Stream Sediments (v3)

This dataset supports a broader study examining the effects of variable inundation and pyrogenic organic matter on ecosystem respiration. The dataset provides data generated from a laboratory batch experiment investigating the interaction between variable inundation conditions (wet and dry sediment) and pyrogenic organic matter (burned and unburned treatments). The contents include time series dissolved oxygen, sediment geochemistry data, and field metadata (including qualitative information on instream and river corridor characteristics). This data package was originally published in November 2025. It was updated in April 2026 (v2; new and modified files) and May 2026 (v3; modified files). See the change history section in the readme for more details For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) international generic sample number (IGSN) mapping file; (5) readme; (6) field protocol; (7) sample name metadata; (8) an environmental context picture for the dry and inundated sampling locations; and (9) a subfolder with sample data from the sediment incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) gravimetric moisture; (4) partial pressure and production rates of carbon dioxide, methane, and nitrous oxide; (5) field wet sediment mass, dry sediment mass, water mass, and field wet sediment volume in incubation and sediment NPOC/TN vials; (6) methods codes; (7) respiration rates, pH, and temperature from after the incubation, raw time series dissolved oxygen and temperature, and a subfolder containing associated plots and scripts; (8) ions; (9) FTICR-MS methods; and (10) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains the CoreMS processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Evaluating Composite Sampling Methods of Bacillus Spores at Low Concentrations

Restoring facility operations after the 2001 Amerithrax attacks took over three months to complete, highlighting the need to reduce remediation time. The most time intensive tasks were environmental sampling and sample analyses. Composite sampling allows disparate samples to be combined, with only a single analysis needed, making it a promising method to reduce response times. We developed a statistical experimental design to test three different composite sampling methods: 1) single medium single pass composite: a single cellulose sponge samples multiple coupons; 2) single medium multi-pass composite: a single cellulose sponge is used to sample multiple coupons; and 3) multi-medium post-sample composite: a single cellulose sponge samples a single surface, and then multiple sponges are combined during sample extraction. Five spore concentrations of Bacillus atrophaeus Nakamura spores were tested; concentrations ranged from 5 to 100 CFU/coupon (0.00775 to 0.155CFU/cm 2 , respectively). Study variables included four clean surface materials (stainless steel, vinyl tile, ceramic tile, and painted wallboard) and three grime coated/dirty materials (stainless steel, vinyl tile, and ceramic tile). Analysis of variance for the clean study showed two significant factors: composite method (p-value < 0.0001) and coupon material (p-value = 0.0008). Recovery efficiency (RE) was higher overall using the post-sample composite (PSC) method compared to single medium composite from both clean and grime coated materials. RE with the PSC method for concentrations tested (10 to 100 CFU/coupon) was similar for ceramic tile, painted wall board, and stainless steel for clean materials. RE was lowest for vinyl tile with both composite methods. Statistical tests for the dirty study showed RE was significantly higher for vinyl and stainless steel materials, but significantly lower for ceramic tile. These results suggest post-sample compositing can be used to reduce sample analysis time when responding to a Bacillus anthracis contamination event of clean or dirty surfaces.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2005

Aerodynamics of an Axisymmetric Missile Concept Having Cruciform Strakes and In-Line Tail Fins From Mach 0.60 to 4.63

An experimental study has been performed to develop a large force and moment aerodynamic data set on a slender axisymmetric missile configuration having cruciform strakes and in-line control tail fins. The data include six-component balance measurements of the configuration aerodynamics and three-component measurements on all four tail fins. The test variables include angle of attack, roll angle, Mach number, model buildup, strake length, nose size, and tail fin deflection angles to provide pitch, yaw, and roll control. Test Mach numbers ranged from 0.60 to 4.63. The entire data set is presented on a CD-ROM that is attached to this paper. The CD-ROM also includes extensive plots of both the six-component configuration data and the three-component tail fin data. Selected samples of these plots are presented in this paper to illustrate the features of the data and to investigate the effects of the test variables.

Jerry M Allen↗

NASA NTRS2005

Aerodynamics of an Axisymmetric Missile Concept Having Cruciform Strakes and In-Line Tail Fins From Mach 0.60 to 4.63, Supplement

Jerry M Allen↗

DOE OSTI2018

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang–Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1975

Multirate sampled-data systems analysis via vector operators

The primary difficulties of both the time-domain switch decomposition method and the frequency-domain decomposition method are overcome by introducing certain matrix operators and performing spectral factorization of resulting matrices of polynomials in the z-transform variable. Topological operations of the switch-decomposition method are simplified. This new approach eliminates the need to solve a system of equations with rational polynomial coefficients such as arises in the frequency-decomposition method. The determination of a multirate sampled-data system's characteristic polynomial no longer requires the evaluation of a determinant of rational polynomial elements. New results on obtaining modified z-transforms from standard z-transforms at a faster rate and vice versa are presented.

Boykin, W. H.↗

DOE OSTI2023

Simultaneous isotopic analysis of fission product Sr, Mo, and Ru in spent nuclear fuel particles by resonance ionization mass spectrometry

Abstract Fission product Sr, Mo, and Ru isotopes in six 10-μm particles of spent fuel from a pressurized water reactor were analyzed by resonance ionization mass spectrometry (RIMS) and evaluated for utility in nuclear material characterization. Previous measurements on these same samples showed widely varying U, Pu, and Am isotopic compositions owing to the samples’ differing irradiation environments within the reactor. This is also seen in Mo and Ru isotopes, which have the added complication of exsolution from the UO 2 fuel matrix. This variability is a hindrance to interpreting data from a collection of particles with incomplete provenance since it is not always possible to assign particles to the same batch of fuel based on isotopic analyses alone. In contrast, the measured 90 Sr/ 88 Sr ratios were indistinguishable across all samples. Strontium isotopic analysis can therefore be used to connect samples with otherwise disparate isotopic compositions, allowing them to be grouped appropriately for interpretation. Strontium isotopic analysis also provides a robust chronometer for determining the time since fuel irradiation. Because of the very high sensitivity of RIMS, only a small fraction of material in each of the 10 μm samples was consumed, leaving the vast majority still available for other analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Wildfire Mapping in Interior Alaska Using Deep Neural Networks on Imbalanced Datasets

Wildfires are the dominant disturbance impacting many regions in Alaska and is expected to intensify due to climate change. Accurate tracking and quantification of wildfires are important for climate modeling and ecological studies in this region. Remote sensing platforms (e.g., MODIS, Landsat) are an important tool for mapping wildfires in Alaska at varying spatial and temporal scales. Deep neural networks (DNN) have shown superior performance in many classification problems such as high-dimensional remote sensing data. Detection of wildfires is an imbalanced classification problem where one class contains a much smaller or larger sample size and DNNs performance can decline. We take a known weight-selection strategy during DNN training and apply them to MODIS variables (e.g., NDVI, surface reflectance) for a binary classification (i.e., wildfire or no-wildfire) across Alaska during the 2004 wildfire year, which is one of the largest on record. The method splits the input training data into sets, one for training the DNN to update weights and the other that splits into a validation set that is equally balanced between the wildfire and no-wildfire class. The performance is monitored on the validation set to select the weights based on the best validation-loss score. This approach was applied to two sampled datasets, such as where the no-wildfire class can significantly outweigh the wildfire class. The normal DNN training strategy was unable to map wildfires for the highly imbalanced dataset, however, the weight-selection strategy was able to map wildfires very accurately (0.96 recall score for 78,702 wildfire pixels (500×500 m)).

Langford, Zach↗

DOE OSTI2026

Soil nitrogen mineralization rates, nutrient stocks, stable isotopes, and water volumetric measurements across terrestrial-aquatic interfaces from three wetlands at the Tanglewood Biological Station, Alabama

This dataset supports a broader study investigating wetland hydrologic and biogeochemical responses to inundation events. Soil samples were collected across four sampling events along terrestrial-aquatic gradients at three wetland sites located within the Tanglewood Biological Station in Alabama from April 2024 to June 2025. The contents in this data package include soil in-situ nitrogen mineralization rates (measurements of net nitrification, net ammonification, and net mineralization), nutrient stocks (total carbon, total nitrogen, and organic matter), stable isotopes (carbon and nitrogen), and water volumetric measurements (water-filled pore space). Water level data related to each wetland location can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/2530253 (Kirker et al., 2024), related water geochemistry data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3001967 (Forbes et al., 2025), and related surface water sediment chemistry data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3377325 (Molina Serpas et al., 2026). In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata and international generic sample numbers (IGSNs); (4) readme; (5) the field protocol; and (6) a subfolder with sample data. The sample data subfolder contains (1) net nitrification rate, (2) net ammonification rate, (3) areal net mineralization rate, (4) percent organic matter, (5) water-filled pore space, (6) total carbon content, (7) total nitrogen content, (8) stable carbon isotope (delta carbon-13), and (9) stable nitrogen isotope (delta nitrogen-15), and (10) methods codes. All files are .csv or .pdf.

13-C↗

NASA NTRS1996

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

Rafael, Qihang Li↗

NASA NTRS2015

Impact of Drilling Operations on Lunar Volatiles Capture: Thermal Vacuum Tests

In Situ Resource Utilization (ISRU) enables future planetary exploration by using local resources to supply mission consumables. This idea of 'living off the land' has the potential to reduce mission cost and risk. On the moon, water has been identified as a potential resource (for life support or propellant) at the lunar poles, where it exists as ice in the subsurface. However, the depth and content of this resource has yet to be confirmed on the ground; only remote detection data exists. The upcoming Resource Prospector mission (RP) will 'ground-truth' the water using a rover, drill, and the RESOLVE science package. As the 2020 planned mission date nears, component level hardware is being tested in relevant lunar conditions (thermal vacuum). In August 2014 a series of drilling tests were performed using the Honeybee Robotics Lunar Prospecting Drill inside a 'dirty' thermal vacuum chamber at the NASA Glenn Research Center. The drill used a unique auger design to capture and retain the lunar regolith simulant. The goal of these tests was to investigate volatiles (water) loss during drilling and sample transfer to a sample crucible in order to validate this regolith sampling method. Twelve soil samples were captured over the course of two tests at pressures of 10(exp-5) Torr and ambient temperatures between -80C to -20C. Each sample was obtained from a depth of 40 cm to 50 cm within a cryogenically frozen bed of NU-LHT-3M lunar regolith simulant doped with 5 wt% water. Upon acquisition, each sample was transferred and hermetically sealed inside a crucible. The samples were later baked out to determine water wt% and in turn volatile loss by following ASTM standard practices. Of the twelve tests, four sealed properly and lost an average of 30% of their available water during drilling and transfer. The variability in the results correlated well with ambient temperature (lower the temperature lower volatiles loss) and the trend agreed with the sublimation rates for the same temperature. Moisture retention also correlated with quantity of sample: a larger amount of material resulted in less water loss. The drilling process took an average of 10 minutes to capture and transfer each sample. The drilling power was approximately 20 Watt with a Weight on Bit of approximately 30 N. The bit temperature indicated little heat input into formation during the drilling process.

drilling↗

DOE OSTI2025

Temporal Variability in Reservoir Surface Area Is an Important Source of Uncertainty in GHG Emission Estimates

Ebullitive methane (CH 4 ) emissions in lentic ecosystems tend to concentrate at river-lake interfaces and within shallow littoral zones. However, inconsistent definitions of the littoral zone and static representations of the lake or reservoir surface area contribute to major uncertainties in greenhouse gas (GHG) emissions estimates, particularly in reservoirs with large water-level fluctuations. This study examines temporal variation in littoral and total surface areas of US reservoirs and demonstrates how different methods and data sources lead to discrepencies in reservoir GHG emissions at large scales and over time. We also explore variability in remotely sensed water occurrence according to maximum surface area, reservoir purposes, and hydrologic regions. Notably, the largest relative variability in surface area is exhibited by small reservoirs with a maximum surface area <1 km 2 and non-hydroelectric reservoirs. Additionally, we use a case study of measured CH 4 emissions from the southeastern United States (Douglas Reservoir) to illustrate the effects of varying surface area on reservoir-wide GHG estimates. Upscaled CH 4 emissions in Douglas Reservoir differed by nearly two-fold depending on the source of total surface area data and whether estimates accounted for seasonal fluctuations in surface area. During seasonal drawdown in Douglas Reservoir, relative littoral area varies non-linearly; periods of lower pool elevation (and thus larger relative littoral area) likely contribute disproportionately high CH 4 emission rates compared to the commonly sampled summer season when water levels are at full-pool elevation. Improved GHG monitoring and upscaling techniques require accounting for temporal variability in reservoir surface extent and littoral area.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Report on Status of Shipment of High Fluence Austenitic Steel Samples for Characterization and Stress Corrosion Crack Testing

The goal of the Mechanisms of Irradiation Assisted Stress Corrosion Cracking (IASCC) task in the LWRS Program is to conduct experimental research into understanding how multiple variables influence the crack initiation and crack growth in materials subjected to stress under corrosive conditions. This includes understanding the influences of alloy composition, radiation condition, water chemistry and metallurgical starting condition (i.e., previous cold work or heat treatments and the resulting microstructure) has on the behavior of materials. Testing involves crack initiation and growth testing on irradiated specimens of single-variable alloys in simulated Light Water Reactor (LWR) environments, tensile testing, hardness testing, microstructural and microchemical analysis, and detailed efforts to characterize localized deformation. Combined, these single-variable experiments will provide mechanistic understanding that can be used to identify key operational variables to mitigate or control IASCC, optimize inspection and maintenance schedules to the most susceptible materials/locations, and, in the long-term, design IASCC-resistant materials. In support of this research, efforts are currently underway to arrange shipment of “free” high fluence austenitic alloys available through Électricité de France (EDF) for post irradiation testing at the Oak Ridge National Laboratory (ORNL) and IASCC testing at the University of Michigan. These high fluence materials range in damage values from 45 to 125 displacements per atom (dpa). The samples identified for transport to the United States, which include nine, no-cost, 304, 308 and 316 tensile bars, were relocated from the Research Institute of Atomic Reactors (RIAR) in Dimitrovgrad, Ulyanovsk Oblast, Russia, and received at the Halden Reactor in Halden, Norway, on August 23, 2016. ORNL has been notified that a significant amount of work is required to prepare the samples for further shipment to Oak Ridge, Tennessee. The preliminary work for sample shipment between Halden and Oak Ridge includes fabrication of an inner cask sample container, decontamination and preparation of a Type A container, preparation of new activity calculations, all necessary paperwork, and handling. ORNL will continue to work to track progress of sample preparation and shipment status, and to work toward an agreement that covers material shipping costs between the Halden Reactor and the Oak Ridge National Laboratory.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Characterization of the VVV Survey RR Lyrae Population across the Southern Galactic Plane

Deep near-IR images from the VISTA Variables in the Vía Láctea (VVV) Survey were used to search for RR Lyrae stars in the Southern Galactic plane. A sizable sample of 404 RR Lyrae of type ab stars was identified across a thin slice of the fourth Galactic quadrant (295° < ℓ < 350°, −2.°24 < b < −1.°05). The sample’s distance distribution exhibits a maximum density that occurs at the bulge tangent point, which implies that this primarily Oosterhoff type I population of RRab stars does not trace the bar delineated by their red clump counterparts. The bulge RR Lyrae population does not extend beyond ℓ ∼ 340°, and the sample’s spatial distribution presents evidence of density enhancements and substructure that warrants further investigation. Indeed, the sample may be employed to evaluate Galactic evolution models, and is particularly lucrative since half of the discovered RR Lyrae are within reach of Gaia astrometric observations.

79 ASTRONOMY AND ASTROPHYSICS↗