Engineering Papers⌕ Search

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.

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

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Response Variability in Commercial MOSFET SEE Qualification

Single-event effects (SEE) evaluation of five different part types of next generation, commercial trench MOSFETs indicates large part-to-part variation in determining a safe operating area (SOA) for drain-source voltage (V DS ) following a test campaign that exposed >50 samples per part type to heavy ions. These results suggest a determination of a SOA using small sample sizes may fail to capture the full extent of the part-to-part variability. An example method is discussed for establishing a Safe Operating Area using a one-sided statistical tolerance limit based on the number of test samples. Finally, burn-in is shown to be a critical factor in reducing part-to-part variation in part response. Implications for radiation qualification requirements are also explored.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Machine-to-machine variability of roughness and corrosion in additively manufactured 316L stainless steel

Numerous studies on the corrosion response of metal AM have been conducted. Nonetheless, the specimens being tested are commonly ground or polished to remove the outer as-built surface. If metal AM is truly going to be employed as a transformative technology that can produce complex shapes that do not require traditional machining, then the material needs to be evaluated in the as-built state. The reality is that AM alloys have shown significant inconsistencies regarding as-built surface texture, topology, and residual stress. One metric that has shown significant unpredictability in the literature is the susceptibility to localized corrosion of typically passive alloys, such as stainless steel (SS). There are a large number of studies that have attempted to understand the corrosion response of metal AM materials, but these studies are typically performed on materials that have been printed on a single machine and often mechanically polished to a smooth finish. This study compares the corrosion response of as-built AM, laser-beam powder bed fusion (LB-PBF), 316L SS parts that have been fabricated on five different machines. The majority of this work focused on understanding the susceptibility to localized corrosion of AM metals with respect to machine-dependent variables, namely surface roughness, and build angle. Surface roughness data was collected using scanning white light triangulation, laser scanning confocal microscopy, and coherence scanning interferometry. The results show that there is significant variability (p two-tail < 0.05) in the susceptibility to local corrosion initiation of LB-PBF 316L SS samples built on different machines. Surface oxides were probed with electron dispersive spectroscopy and revealed that variations in local corrosion susceptibility likely arise from differences in the stability of the passive film caused by chemical segregation, unique microstructure, and tortuous roughness features at the as-built surfaces. The variability of roughness and corrosion properties from test samples printed on different machines was corroborated by property measurements performed at five different testing sites, proving reproducibility of the data. Most importantly, this study shows that if the as-built surface layer is removed through grinding or electropolishing the machine-to-machine variation observed in the corrosion susceptibility is reduced.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Laser-Induced Spectrochemical Assay for Uranium Enrichment (LISA-UE)

Uranium hexafluoride (UF6) is the uranium compound typically involved in uranium enrichment process. As the first line of defense against nuclear proliferation, accurate determinations of the uranium enrichment ratio in UF6 are critical for materials verification, accounting and safeguards. Shipping gaseous UF6 samples off-site for analysis with mass spectrometry is cumbersome and costly, and results are not available for some time (months). In-field UF6 enrichment assay has the potential to substantially reduce the time, logistics and expense of sample handling. At present, COMPUCEA is the only accepted method for UF6 enrichment assay in the field. Laser-Induced Spectrochemical Assay for Uranium Enrichment (LISA-UE) is an all-optical (based on laser induced plasma emission) analytical technique intended for fieldable, accurate, precise and rapid UF6 enrichment assay. In its operation, laser induced plasma is created directly in the gaseous UF6 sample. Because different U isotopes emit at slightly different wavelengths, the isotopic information of the UF6 sample is inherently encoded in the atomic emission from the plasma. Isotopic emissions from 235U and 238U are measured simultaneously, which eliminate correlated noise from the laser induced plasma. Isotopic information of the UF6 sample can be extracted from the acquired spectrum with theoretical multi-variable non-linear spectral fitting. To date, advances made by the LISA-UE research team include optimization of the spectral window for direct gaseous UF6 enrichment assay with laser induced plasma, development of data reduction algorithms, and demonstrations of the LISA-UE technique with gaseous UF6 samples. In this presentation, the technical aspect of LISA-UE will be overviewed, the data reduction algorithm will be described, and performance of the technique will be discussed.

Chan, George↗
DOE OSTI2016

NEW PHOTOMETRICALLY VARIABLE MAGNETIC CHEMICALLY PECULIAR STARS IN THE ASAS-3 ARCHIVE

The magnetic Ap or CP2 stars are natural atomic and magnetic laboratories. Strictly periodic changes are observed in the spectra and brightness of these stars, which allow the derivation of rotational periods. Related to this group of objects are the He-weak (CP4) and He-rich stars, some of which also undergo brightness changes due to rotational modulation. Increasing the sample size of known rotational periods among CP2/4 stars is important and will contribute to our understanding of these objects and their evolution in time. We have compiled an extensive target list of CP2/4 stars from the General Catalog of Ap, HgMn, and Am stars, including several early-type (spectral types B/A) variables of undetermined type from the International Variable Star Index. We investigated our sample stars using publicly available observations from the ASAS-3 archive. Our previous efforts in this respect led to the discovery of 323 variable stars. Using a refined analysis approach, we were able to identify another 360 stars exhibiting photometric variability in ASAS-3 data. Summary data, folded light curves and, if available, information from the literature are presented for our final sample, which is composed of 334 bona-fide α{sup 2} Canum Venaticorum (ACV) variables, 23 ACV candidates, and 3 eclipsing binary systems. Interesting and unusual objects are discussed in detail. In particular, we call attention to HD 66051 (V414 Pup), which is an eclipsing binary system showing obvious rotational modulation of the light curve due to the presence of an ACV variable in the system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Exploring the spatial variability of soil properties in an Alfisol Catena

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzed for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.

Geo-statistical analysis↗
DOE OSTI2016

Uncertainty quantification of microstructural properties due to variability in measured pole figures

Experimental pole figures are an important input for microstructure homogenization models. In this paper, we derive an exact analytical formulation to quantify the uncertainties in homogenized properties due to uncertainty in the experimentally measured pole figures. The pole figures are acquired from a set of Ti-7Al alloy samples. These samples were obtained from the same process: by compressing a beta forged ingot at room temperature followed by annealing. The samples were taken from different regions of the original ingot, and this created variability in the resulting pole figures. The joint multivariate probability distributions of the computed orientation distribution function (ODF) is then found using the method of characteristic functions based on a Gaussian model of the pole figures. Engineering properties such as elastic modulus can be obtained by volume averaging over the ODF. We also show that uncertainty in elastic properties can be analytically obtained using direct transformation of random variables in the homogenization approach.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Pilot Implementation of a Field Study Design to Evaluate the Impact of Source Control Measures on Indoor Air Quality in High Performance Homes

To improve the indoor air quality in new, high performance homes, a variety of standards and rating programs have been introduced to identify building materials that are designed to have lower emission rates of key contaminants of concern and a number of building materials are being introduced that are certified to these standards. For example, the U.S. Department of Energy (DOE) Zero Energy Ready Home program requires certification under the U.S. Environmental Protection Agency (EPA) Indoor airPLUS (IaP) label, which requires the use of PS1 or PS2 certified plywood and OSB; low-formaldehyde emitting wood products; low- or no-VOC paints and coatings as certified by Green Seal Standard GS-11, GreenGuard, SCS Indoor Advantage Gold Standard, MPI Green Performance Standard, or another third party rating program; and Green Label-certified carpet and carpet cushions. However, little is known regarding the efficacy of the IAP requirements in measurably reducing contaminant exposures in homes. The goal of this project is to develop a robust experimental approach and collect preliminary data to support the evaluation of indoor air quality (IAQ) measures linked to IAP-approved low-emitting materials and finishes in new residential homes. To this end, the research team of Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (LBNL) developed a detailed experimental plan to measure IAQ constituents and other parameters, over time, in new homes constructed with materials compliant with IAP’s low-emitting material and ventilation requirements (i.e., section 6.1, 6.2, 6.3, and 7.2) and similar homes constructed to the state building code with conventional materials. The IAQ in IAP and conventional homes of similar age, location, and construction style is quantified as the differences in the speciated VOC and aldehyde concentrations, normalized to dilution rates. The experimental plan consists of methods to evaluate the difference between low-emitting and “conventional” materials as installed in newly constructed residential homes using both (1) highly controlled, short-term active samples to precisely characterize the building-related chemical emissions and building contents and (2) a week-long passive sample designed to capture the impact of occupant behavior and related activities on measured IAQ contaminant levels indoors. The combination of detailed short-term measurements with the home under controlled/consistent conditions during pre- and post-occupancy and the week-long passive sampling data provide the opportunity to begin to separate the different emission sources and help isolate and quantify variability in the monitored homes. Between April and August 2014, the research team performed pre-occupancy and post-occupancy sampling in one conventional home and two homes built with low-emitting materials that were generally consistent with EPA’s Indoor airPLUS guidelines. However, for a number of reasons, the full experimental plan was not implemented. The project was intended to continue for up to three years to asses long-term changes in IAQ but the project was limited to one calendar year. As a result, several of the primary research questions related to seasonal impacts and the long-term trends in IAQ could not be addressed. In addition, there were several unexpected issues related to recruiting, availability of home types, and difficulty coordinating with builders/realtors/homeowners. Several field monitoring issues also came up that provide “lessons learned” that led to improvements to the original monitoring plan. The project produced a good experimental plan that is expected to be be useful for future efforts collecting data to support answering these same or similar research questions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2019

Statistics for Testing Under Adverse Conditions

Here we develop a statistical basis for limited adverse testing. This type of testing simultaneously evaluates system performances against minimum requirements and minimizes costs, particularly for large scale engineering projects. Because testing is often expensive and narrow in scope, the data obtained is relatively limited—precisely the opposite of the recent “large data” movement but no less compelling. Although a remarkably common approach for industrial and large-scale government projects, a statistical basis for adverse testing remains poorly explored. Here we prove mathematically, under specific conditions, that setting each independent variable to an adverse condition leads to a similar level of adversity in the dependent variable. For example, setting all normally distributed independent variables to at least their 95th percentile values leads to a result at the 95th percentile. The analysis considers sample size estimates to clarify the value of replicates in this type of testing, determines how many of the independent variables must be set to adverse condition values, and highlights the essential assumptions, so that engineers, statisticians, and subject matter experts know when this statistical framework may be applied successfully.

42 ENGINEERING↗
DOE OSTI2021

Cross-national analysis of food security drivers: comparing results based on the Food Insecurity Experience Scale and Global Food Security Index

Abstract The second UN Sustainable Development Goal establishes food security as a priority for governments, multilateral organizations, and NGOs. These institutions track national-level food security performance with an array of metrics and weigh intervention options considering the leverage of many possible drivers. We studied the relationships between several candidate drivers and two response variables based on prominent measures of national food security: the 2019 Global Food Security Index (GFSI) and the Food Insecurity Experience Scale’s (FIES) estimate of the percentage of a nation’s population experiencing food security or mild food insecurity (FI ). We compared the contributions of explanatory variables in regressions predicting both response variables, and we further tested the stability of our results to changes in explanatory variable selection and in the countries included in regression model training and testing. At the cross-national level, the quantity and quality of a nation’s agricultural land were not predictive of either food security metric. We found mixed evidence that per-capita cereal production, per-hectare cereal yield, an aggregate governance metric, logistics performance, and extent of paid employment work were predictive of national food security. Household spending as measured by per-capita final consumption expenditure (HFCE) was consistently the strongest driver among those studied, alone explaining a median of 92% and 70% of variation (based on out-of-sample R 2 ) in GFSI and FI , respectively. The relative strength of HFCE as a predictor was observed for both response variables and was independent of the countries used for model training, the transformations applied to the explanatory variables prior to model training, and the variable selection technique used to specify multivariate regressions. The results of this cross-national analysis reinforce previous research supportive of a causal mechanism where, in the absence of exceptional local factors, an increase in income drives increase in food security. However, the strength of this effect varies depending on the countries included in regression model fitting. We demonstrate that using multiple response metrics, repeated random sampling of input data, and iterative variable selection facilitates a convergence of evidence approach to analyzing food security drivers.

42 ENGINEERING↗
DOE OSTI2020

Assessment of the Utility of the Oral Fluid and Plasma Proteome for Hydrocodone Usage

Non-medical use and abuse of prescription opioids is a growing problem in both the civilian and military communities, with minimal technologies for detecting hydrocodone use. This study explored the proteomic changes that occur in the oral fluid and blood plasma following controlled hydrocodone administration in twenty subjects. The global proteomic profile was determined for samples taken at four time points per subject of pre-exposure and 4, 6, or 168 hours post-exposure. The oral fluid samples analyzed herein provided greater differentiation between “baseline” and “response” time points than was observed with blood plasma, at least partially due to significant person-to-person variability in the plasma proteome. A total of 399 proteins were identified from oral fluid samples, and the abundance of 102 of those proteins was determined to be significantly different upon metabolism of hydrocodone (4 and 6 hour time points) as compared to baseline levels in the oral fluid (pre-dose and 168 hour). This is the first, to our knowledge, assessment of the oral fluid and blood plasma proteome following hydrocodone administration, which demonstrates the potential of oral fluid as a non-invasive sample that may reveal features of hydrocodone or other opioid use and/or misuse.

Kaiser, Brooke LD↗
DOE OSTI2018

No 182 W excess in the Ontong Java Plateau source

We report that small-scale W isotope variations in ancient and modern terrestrial rocks provide insights into Earth's accretion and early differentiation history as well as the long-term evolution of the Earth's mantle. Tungsten isotope studies on such rocks have exploited advances in mass spectrometry, both NTIMS and MC-ICPMS, which now permit the determination of W isotope ratios at unprecedented precision. While W isotope studies performed in different labs by MC-ICPMS and NTIMS generally exhibit excellent agreement, obtaining accurate W isotope data at this level of precision remains analytically challenging. For example, a recent NTIMS study reported a relatively large, +24 ppm excess in 182 W/ 184 W for a Phanerozoic sample from the Ontong Java Plateau (OJP), but no such 182 W/ 184 W anomaly was found in another study by MC-ICPMS. The present study aims to resolve the discrepancy between these two previous studies, and more generally to evaluate the agreement between different recent W isotope studies by NTIMS and MC-ICPMS. To this end, we report new W isotope data for OJP drill core samples obtained by MC-ICPMS. Additionally, the OJP samples analyzed here exhibit no resolvable 182 W/ 184 W excess relative to the standards and most terrestrial rocks. Moreover, the OJP samples as well as the terrestrial rock standards analyzed here exhibit small but variable W isotope variations for ratios involving 183 W, producing coupled variations in both ‘radiogenic’ (i.e., 182 W/ 183 W) and ‘non-radiogenic’ (i.e., 183 W/ 184 W) ratios. These W isotope variations are analytical in origin, induced during sample preparation, and very likely caused by a nuclear field shift isotope fractionation affecting primarily the odd isotope ( 183 W). The recently reported 182 W excess for an OJP sample may result from this nuclear field shift effect, as the NTIMS analyses had to rely on a double normalization involving the 183 W/ 184 W ratio. More generally, these results demonstrate that using 183 W data from any MC-ICPMS or NTIMS study requires a careful quantification of any potential analytical 183 W effect. Nevertheless, once such effects are taken into account, then both 182 W/ 184 W and 183 W/ 184 W can accurately be determined to a very high level of precision.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Operator Relaxation and the Optimal Depth of Classical Shadows

Classical shadows are a powerful method for learning many properties of quantum states in a sample-efficient manner, by making use of randomized measurements. Here we study the sample complexity of learning the expectation value of Pauli operators via “shallow shadows,” a recently proposed version of classical shadows in which the randomization step is effected by a local unitary circuit of variable depth t. Here we show that the shadow norm (the quantity controlling the sample complexity) is expressed in terms of properties of the Heisenberg time evolution of operators under the randomizing (“twirling”) circuit—namely the evolution of the weight distribution characterizing the number of sites on which an operator acts nontrivially. For spatially contiguous Pauli operators of weight k, this entails a competition between two processes: operator spreading (whereby the support of an operator grows over time, increasing its weight) and operator relaxation (whereby the bulk of the operator develops an equilibrium density of identity operators, decreasing its weight). From this simple picture we derive (i) an upper bound on the shadow norm which, for depth t~log⁡(k), guarantees an exponential gain in sample complexity over the t=0 protocol in any spatial dimension, and (ii) quantitative results in one dimension within a mean-field approximation, including a universal subleading correction to the optimal depth, found to be in excellent agreement with infinite matrix product state numerical simulations. Our Letter connects fundamental ideas in quantum many-body dynamics to applications in quantum information science, and paves the way to highly optimized protocols for learning different properties of quantum states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Molybdenum isotope compositions of uranium ore concentrates by double spike MC-ICP-MS

The molybdenum (Mo) isotope composition of uranium ore concentrate (UOC) has been proposed as a nuclear forensic signature due to the ubiquitous presence of Mo in the nuclear fuel cycle and to the possibility that different UOC production pathways lead to characteristic Mo isotope fractionation. Furthermore, Mo forms a volatile hexafluoride which leads to the retainment of Mo in the nuclear fuel cycle through U enrichment and reactor operation processes. As a result, it is possible that the nuclear fuel cycle generates a rich array of Mo isotope signatures. The first step in interpreting Mo isotope signatures generated during the nuclear fuel cycle is to characterize the Mo isotope composition of starting materials. In this study, a suite of UOC samples were analyzed for their Mo isotope composition in order to constrain the range of Mo isotope compositions entering the front end of the nuclear fuel cycle. Analytical protocols were developed to purify Mo from a U rich matrix prior to Mo isotope analysis by double spike MC-ICP-MS. A >3‰ variation in the 98 Mo/ 95 Mo ratio was observed in the suite of UOC samples with δ 98 Mo ranging from -1.15 to +1.96‰ relative to the NIST 3134 Mo standard reference material. The δ98Mo range observed in the UOC samples is very similar to the δ 98 Mo range observed in crustal igneous rocks and Mo-bearing minerals, suggesting that Mo isotope variability in UOC is driven by variability in the parent U ores. However, Mo isotope fractionation during UOC production is evident with one of the UOC samples being isotopically heavy relative to its parent U ore by 0.75‰, suggesting that different UOC production processes also contribute to the total Mo isotope variability observed. Overall, it is expected that the Mo isotope signatures generated during enrichment and reactor process will be clearly discernible from those generated during UOC production.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Multicolor Variability of Young Stars in the Lagoon Nebula: Driving Causes and Intrinsic Timescales

Space observatories have provided unprecedented depictions of the many variability behaviors typical of low-mass, young stars. However, those studies have so far largely omitted more massive objects (~2 M {sub ⊙} to 4–5 M {sub ⊙}) and were limited by the absence of simultaneous, multiwavelength information. We present a new study of young star variability in the ~1–2 Myr old, massive Lagoon Nebula region. Our sample encompasses 278 young, late B to K-type stars, monitored with Kepler/K2. Auxiliary u, g, r, i, Hα time-series photometry, simultaneous with K2, was acquired at the Paranal Observatory. We employed this comprehensive data set and archival infrared photometry to determine individual stellar parameters, assess the presence of circumstellar disks, and tie the variability behaviors to inner disk dynamics. We found significant mass-dependent trends in variability properties, with B/A stars displaying substantially reduced levels of variability compared to G/K stars for any light-curve morphology. These properties suggest different magnetic field structures at the surface of early-type and later-type stars. We also detected a dearth of some disk-driven variability behaviors, particularly dippers, among stars earlier than G. This indicates that their higher surface temperatures and more chaotic magnetic fields prevent the formation and survival of inner disk dust structures corotating with the star. Finally, we examined the characteristic variability timescales within each light curve and determined that the day-to-week timescales are predominant over the K2 time series. These reflect distinct processes and locations in the inner disk environment, from intense accretion triggered by instabilities in the innermost disk regions to variable accretion efficiency in the outer magnetosphere.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Bayesian modeling of inconsistent plastic response due to material variability

The advent of fabrication techniques such as additive manufacturing has focused attention on the considerable variability of material response due to defects and other microstructural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. To account for material response variability through variations in physical parameters, we adapt a recent Bayesian embedded modeling error calibration technique. We use Bayesian model selection to determine the most plausible of a variety of plasticity models and the optimal embedding of parameter variability. To expedite model selection, we develop an adaptive importance-sampling-based numerical integration scheme to compute the Bayesian model evidence. In conclusion, we demonstrate that the new framework provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2026

WHONDRS 2016 Sediment Organic Matter Characterization Data from Streams across HJ Andrews Experimental Forest, Oregon

This dataset supports a broader synoptic effort to map morphological, hydrological, chemical, and biological conditions across a fifth-order mountain stream network. Samples were generated through a collaborative synoptic sampling effort in 2016. The dataset provides sediment Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) from 60 sites across the HJ Andrews Experimental Forest, Oregon (https://andrewsforest.oregonstate.edu). Related data were collected as part of the event and were published separately in collaboration with other team members. The data are available at http://www.hydroshare.org/resource/ea6c0832885a46c3939e7bb22e48e754 and are described within https://doi.org/10.5194/essd-11-1567-2019 (Ward et al., 2019). The hydroshare data package contains processed FTICR-MS data from the samples included in this data package. The data were processed via Formultitude (previously called Formularity; https://github.com/PNNL-Comp-Mass-Spec/Formultitude). However, we have re-processed the data using Core-MS and included it in this data package. Additional related data collected in 2025 from a similar effort can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3023310 and http://www.hydroshare.org/resource/b274c4a234bf4b12b7cb8a54a696c629. 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) a folder of sample data; (2) data dictionary; (3) file-level metadata; (4); (5) coordinates; and (6) readme. The sample data subfolder contains 12 Tesla (12T) FTICR-MS data. This folder contains the 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, .Rmd, .py, .cal, or .json.

Biogeochemistry↗
DOE OSTI2014

THE CATALINA SURVEYS PERIODIC VARIABLE STAR CATALOG

We present ∼47,000 periodic variables found during the analysis of 5.4 million variable star candidates within a 20,000 deg{sup 2} region covered by the Catalina Surveys Data Release-1 (CSDR1). Combining these variables with type ab RR Lyrae from our previous work, we produce an online catalog containing periods, amplitudes, and classifications for ∼61,000 periodic variables. By cross-matching these variables with those from prior surveys, we find that >90% of the ∼8000 known periodic variables in the survey region are recovered. For these sources, we find excellent agreement between our catalog and prior values of luminosity, period, and amplitude as well as classification. We investigate the rate of confusion between objects classified as contact binaries and type c RR Lyrae (RRc's) based on periods, colors, amplitudes, metallicities, radial velocities, and surface gravities. We find that no more than a few percent of the variables in these classes are misidentified. By deriving distances for this clean sample of ∼5500 RRc's, we trace the path of the Sagittarius tidal streams within the Galactic halo. Selecting 146 outer-halo RRc's with SDSS radial velocities, we confirm the presence of a coherent halo structure that is inconsistent with current N-body simulations of the Sagittarius tidal stream. We also find numerous long-period variables that are very likely associated within the Sagittarius tidal stream system. Based on the examination of 31,000 contact binary light curves we find evidence for two subgroups exhibiting irregular light curves. One subgroup presents significant variations in mean brightness that are likely due to chromospheric activity. The other subgroup shows stable modulations over more than a thousand days and thereby provides evidence that the O'Connell effect is not due to stellar spots.

79 ASTRONOMY AND ASTROPHYSICS↗