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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.

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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Control of the external photoluminescent quantum yield of emitters coupled to nanoantenna phased arrays

Optical losses in metals represent the largest limitation to the external quantum yield of emitters coupled to plasmonic antennas. These losses can be at the emission wavelength, but they can be more important at shorter wavelengths, i.e., at the excitation wavelength of the emitters, where the conductivity of metals is usually lower. We present accurate measurements of the absolute external photoluminescent quantum yield of a thin layer of emitting material deposited over a periodic nanoantenna phased array. Emission and absorptance measurements of the sample are performed using a custom-made setup including an integrating sphere and variable angle excitation. The measurements reveal a strong dependence of the external quantum yield on the angle at which the optical field excites the sample. Such behavior is attributed to the coupling between far-field illumination and near-field excitation mediated by the collective resonances supported by the array. Numerical simulations confirm that the inherent losses associated with the metal can be greatly reduced by selecting an optimum angle of illumination, which boosts the light conversion efficiency in the emitting layer. This combined experimental and numerical characterization of the emission from plasmonic arrays reveals the need to carefully design the illumination to achieve the maximum external quantum yield.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Oxaliplatin and irinotecan induce heterogenous changes in the EMT markers of metastasizing colorectal carcinoma cells

Highlights: • Significant variability and lower expression uniformity in lymph node metastatic cells. • Heterogeneity of cell response partially determined by cancer cell microenvironment. • Metastatic cells proved to be less sensitive to chemotherapy treatment compared to primary site cancer cells. • Irinotecan and oxaliplatin affected EMT markers in primary cell lines. In patients with advanced colorectal cancer (CRC), surgery is complemented with systemic therapy – chemotherapy and radiochemotherapy. Although the patients’ overall survival has been significantly improved, tumor resistance is still a frequent cause of chemotherapy failure. Several factors contribute to chemoresistance of tumor cells including changes related with epithelial-mesenchymal transition (EMT). The present study was designed to verify the presence of EMT markers in paired CRC primary cell lines obtained from primary tumor sites and lymph node metastases of three patients and to investigate the effect of irinotecan and oxaliplatin treatment on these markers as well. The samples of the higher stage of CRC and positive for angioinvasion were selected and qPCR, western blot analysis, migration assay, cytotoxicity testing was performed. Results confirmed the increased expression of several markers characteristic of EMT and invasiveness in lymph node metastatic cells, with a significant variability between individual samples. Irinotecan and oxaliplatin decreased migration activity of the cells and to the varying degree affected the expression of EMT and invasiveness markers. In conclusion, in CRC EMT is present in metastatic cells over a phenotypic continuum whose expression is altered heterogeneously upon irinotecan and oxaliplatin treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling

Global Sensitivity Analysis (GSA) aims to understand the relative importance of uncertain input variables to model response. Conventional GSA involves calculating sensitivity (Sobol’) indices for a model with known model parameter distributions. However, model parameters are affected by aleatory and epistemic uncertainty, with the latter often caused by lack of data. In this paper, we propose a new framework to quantify uncertainty in probability model-form and model parameters resulting from small datasets and integrate these uncertainties into Sobol’ index estimates. First, the process establishes, through Bayesian multimodel inference, a set of candidate probability models and their associated probabilities. Imprecise Sobol’ indices are calculated from these probability models using an importance sampling reweighting approach. This results in probabilistic Sobol’ indices, whose distribution characterizes uncertainty in the sensitivity resulting from small dataset size. The imprecise Sobol’ indices thus provide a measure of confidence in the sensitivity estimate and, moreover, can be used to inform data collection efforts targeted to minimize the impact of uncertainties. Through an example studying the parameters of a Timoshenko beam, we show that these probabilistic Sobol’ indices converge to the true/deterministic Sobol’ indices as the dataset size increases and hence, distribution-form uncertainty reduces. The approach is then applied to assess the sensitivity of the out-of-plane properties of an E-glass fiber composite material to its constituent properties. This second example illustrates the approach for an important class of materials with wide-ranging applications when data may be lacking for some input parameters.

42 ENGINEERING↗
DOE OSTI2016

Alpha1 LASSO data bundles Lamont, OK

A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input includes model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

LASSO Data Bundles

The Alpha 2 release is the second release from the LASSO Pilot Phase that builds upon the Alpha 1 release. Alpha 2 contains additional diagnostics in the data bundles and focuses on cases from spring-summer 2016. A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input include model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Empirically assessing the potential release of rare earth elements from black shale under simulated hydraulic fracturing conditions

Rare earth elements (REEs) are economically important to modern society and the rapid growth of technologies dependent on REEs has placed considerable economic pressure on their sourcing. This study addresses whether REEs could be released as a byproduct of natural gas extraction from a series of experiments that were designed to simulate hydraulic fracturing of black shale under various pressure (25 and 27.5 MPa) and temperature (50, 90, 130 °C) conditions. The dissolved REEs in the reacted fluids displayed no propensity for the REEs to be released from black shale under high pressure and temperature conditions, a result that is consistent across the different types of fluids investigated. Overall, there was a net loss of REEs from the fluid. These changes in dissolved REEs were greatest at the moment the fluids first contacted the shale and before the high temperature and high pressure conditions were imposed, although the magnitude of these changes (10 -4 μg/g) were small compared to the magnitude of the total REE content present in the solid shale samples (10 2 μg/g). These results highlight the variability and complexity of hydraulic fracturing systems and indicate that REE may not serve as robust tracers for fracturing fluid-shale reactions. Additionally, the results suggest that significant quantities of REEs may not be byproducts of hydraulically fractured shales.

03 NATURAL GAS↗
DOE OSTI2014

Radiation-induced complications in prostate cancer patients treated with radiotherapy

The purpose of the study is to determine the relationship between radiation-induced complications with dosimetric and radiobiological parameters for prostate cancer patients that underwent the conformal radiotherapy treatment. 17 prostate cancer patients that have been treated with conformal radiotherapy were retrospectively analysed. The dosimetric data was retrieved in the form of dose-volume histogram (DVH) from Radiotherapy Treatment Planning System. The DVH was utilised to derived Normal Tissue Complication Probability (NTCP) in radiobiological data. Follow-up data from medical records were used to grade the occurrence of acute gastrointestinal (GI) and genitourinary (GU) complications using Radiation Therapy Oncology Group (RTOG) scoring system. The chi-square test was used to determine the relationship between radiation-induced complication with dosimetric and radiobiological parameters. 8 (47%) and 7 (41%) patients were having acute GI and GU complications respectively. The acute GI complication can be associated with V60{sub rectum}, rectal mean dose and NTCP{sub rectum} with p-value of 0.016, 0.038 and 0.049 respectively. There are no significant relationships of acute GU complication with dosimetric and radiobiological variables. Further study can be done by increase the sample size and follow up duration for deeper understanding of the factors that effecting the GU and GI complication in prostate cancer radiotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

On filament structure and propagation within a commercial plasma globe

The filamentary discharge seen within commercial plasma globes is commonly enjoyed yet not well understood. Here, we investigate the discharge properties of a plasma globe using a variable high voltage amplifier. We find that increasing voltage magnitude increases the number of filaments while leaving their individual structure basically unchanged, a result typical of dielectric barrier discharges. The frequency of the voltage also affects filament population but more significantly changes filament structure, with more diffuse filaments seen at lower frequencies. Voltage polarity is observed to be important, especially at lower frequencies, where for negative-gradient voltages the discharge is more diffuse, not filamentary. At late stages of the discharge circular structures appear and expand on the glass boundaries. We find no trend of discharge speed with respect to voltage variables, though this may be due to manufacturer sample-to-sample variation. Each voltage cycle the discharge expands outward at ∼10–15 km/s, a speed significantly higher than the estimated electron drift yet considerably lower than that observed for most streamers. We discuss the physics of these observations and their relation to similar discharges that can be found within nature and industry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Study of interface correlation in W/C multilayer structure by specular and non-specular grazing incidence X-ray reflectivity measurements

W/C/W tri-layer thin film samples have been deposited on c-Si substrates in a home-built Ion Beam Sputtering system at 1.5 × 10{sup −3} Torr Ar working pressure and 10 mA grid current. The tri-layer samples have been deposited at different Ar{sup +} ion energies between 0.6 and 1.2 keV for W layer deposition and the samples have been characterized by specular and non-specular grazing incidence X-ray reflectivity (GIXR) measurements. By analyzing the GIXR spectra, various interface parameters have been obtained for both W-on-C and C-on-W interfaces and optimum Ar{sup +} ion energy for obtaining interfaces with low imperfections has been found. Subsequently, multilayer W/C samples with 5-layer, 7-layer, 9-layer, and 13-layer have been deposited at this optimum Ar{sup +} ion energy. By fitting the specular and diffused GIXR data of the multilayer samples with the parameters of each interface as fitting variables, different interface parameters, viz., interface width, in-plane correlation length, interface roughness, and interface diffusion have been estimated for each interface and their variation across the depth of the multilayers have been obtained. The information would be useful in realizing W/C multilayers for soft X-ray mirror application in the <100 Å wavelength regime. The applicability of the “restart of the growth at the interface” model in the case of these ion beam sputter deposited W/C multilayers has also been investigated in the course of this study.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Phase transformations in oxides above 2000°C: experimental technique development

Here, the oxidation of boride and carbide-based ultra-high-temperature ceramics is the primary limiting factor for their use as aerodynamic surfaces. Understanding the behaviour of the oxides that can result from oxidation of metal borides and carbides at very high temperatures is essential to optimise and tailor the performance of these materials; yet experimental thermodynamic and structural data for refractory oxides above 2000°C are mostly absent. The following techniques that can be applied to fill this gap are discussed: (i) commercial ultra-high-temperature differential thermal analysis for investigation of phase transformations and melting in inert environments to 2500°C, (ii) a combination of laser heating with a splittable nozzle aerodynamic levitator for splat quenching and drop calorimetry from temperatures limited only by sample evaporation, (iii) synchrotron X-ray and neutron diffraction on laser-heated aerodynamically levitated oxide samples for in situ observation of phase transformations in variable atmospheres, refinement of high-temperature structures and thermal expansion. Recent experimental findings include anomalous thermal expansion of the defect fluorite phase of YSZ, thermodynamics of pyrochlore–fluorite transformation from high-temperature structure refinements, and measurement of thermal expansion to the melting temperatures and fusion enthalpies of Zr, Hf, La, Yb and Lu oxides. These methods provide temperatures, enthalpies and volume change for phase transformations above 2000°C, which are required for thermodynamic assessments and calculation of phase diagrams of multicomponent systems.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Deciphering the 3D structure of the old galactic bulge from the OGLE RR Lyrae stars

We have analyzed a sample of 27,258 fundamental-mode RR Lyrae variable stars (type RRab) detected recently toward the Galactic bulge by the Optical Gravitational Lensing Experiment (OGLE) survey. The data support our earlier claim that these metal-poor stars trace closely the barred structure formed of intermediate-age red clump giants. The distance to the Galactic center (GC) inferred from the bulge RR Lyrae stars is R{sub 0}=8.27±0.01(stat)±0.40(sys) kpc. We show that their spatial distribution has the shape of a triaxial ellipsoid with a major axis located in the Galactic plane and inclined at an angle of i=20{sup ∘}±3{sup ∘} to the Sun–GC line of sight. The obtained scale-length ratio of the major axis to the minor axis in the Galactic plane and to the axis vertical to the plane is 1:0.49(2):0.39(2). We do not see evidence for the bulge RR Lyrae stars forming an X-shaped structure. Based on the light curve parameters, we derive metallicities of the RRab variables and show that there is a very mild but statistically significant radial metallicity gradient. About 60% of the bulge RRab stars form two very close sequences on the period–amplitude (or Bailey) diagram, which we interpret as two major old bulge populations: A and B. Their metallicities likely differ. Population A is about four times less abundant than the slightly more metal-poor population B. Most of the remaining stars seem to represent other, even more metal-poor populations of the bulge. The presence of multiple old populations indicates that the Milky Way bulge was initially formed through mergers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE WISE LIGHT CURVES OF POLARS

We have extracted the WISE (Wide-field Infrared Survey Explorer) single-exposure data for a sample of 72 polars, which are highly magnetic cataclysmic variables (CVs). We combine these data with both published and unpublished optical and infrared data to explore the origins of the large amplitude variations seen in these systems. In nearly every case, we find evidence for cyclotron emission in the WISE bandpasses. We find that the derived magnetic field strengths for some polars are either too high, or cyclotron emission from lower field components, located spatially coincident to the main accreting poles, must be occurring. We have also estimated field strengths for a number of polars where no such values exist. In addition, contrary to expectations, we find that emission from the fundamental cyclotron harmonic (n = 1) appears to be nearly always present when the magnetic field is of the appropriate strength that it falls within a WISE bandpass. We find that the light curves for RBS 490, an ultrashort-period (46 minutes) CV, suggest that it is a polar. Modeling its spectrum indicates that its donor star is much hotter than expected. Nearly all of the detected polars show 11.5 μm (“W3 band”) excesses. The general lack of variability seen in the W3 bandpass light curves for higher-field polars demonstrates that these excesses are probably not due to cyclotron emission. There is circumstantial evidence that these excesses can be attributed to bremsstrahlung emission from their accretion streams. Reduction of the Spitzer 24 μm image of V1500 Cyg shows that it appears to be located at the center of a small nebula.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Simulating PV System Performance with Component Reliability Distributions

A feature developed by Sandia National Laboratories (SNL) for simulating PV system component reliability has been integrated into the National Renewable Energy Laboratory's System Advisor Model (SAM). The PV Reliability Performance Model (PV-RPM) uses fault/failure and repair distributions to estimate impacts to power, energy production and operational costs. Realization results include the number of failures per component, failure rate, O&M costs incurred based on maintenance strategies, and energy lost based on the failure estimates. As the inputs are inherently uncertain and based on probability distributions, the model realizations include statistical confidence intervals to help bracket the probability that the sample interval contains the true mean value of the variable in question. This paper presents the current validation efforts and provides detail on how this feature is utilized in a PV performance model.

14 SOLAR ENERGY↗
DOE OSTI2022

The air mycobiome is decoupled from the soil mycobiome in the California San Joaquin Valley

Abstract Dispersal is a key force in the assembly of fungal communities and the air is the dominant route of dispersal for most fungi. Understanding the dynamics of airborne fungi is important for determining their source and for helping to prevent fungal disease. This understanding is important in the San Joaquin Valley of California, which is home to 4.2 million people and where the airborne fungus Coccidioides is responsible for the most important fungal disease of otherwise healthy humans, coccidioidomycosis. The San Joaquin Valley is the most productive agricultural region in the United States, with the principal crops grown therein susceptible to fungal pathogens. Here, we characterize the fungal community in soil and air on undeveloped and agricultural land in the San Joaquin Valley using metabarcoding of the internal transcribed spacer 2 variable region of fungal rDNA. Using 1,002 individual samples, we report one of the most extensive studies of fungi sampled simultaneously from air and soil using modern sequencing techniques. We find that the air mycobiome in the San Joaquin Valley is distinct from the soil mycobiome, and that the assemblages of airborne fungi from sites as far apart as 160 km are far more similar to one another than to the fungal communities in nearby soils. Additionally, we present evidence that airborne fungi in the San Joaquin Valley are subject to dispersal limitation and cyclical intra‐annual patterns of community composition. Our findings are broadly applicable to understanding the dispersal of airborne fungi and the taxonomic structure of airborne fungal assemblages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The four trajectory data sets support aerosol, cloud, and planetary boundary-layer research. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The six trajectory data sets support aerosol, cloud, planetary boundary layer, and related research (aerosol-cloud interactions, etc.), as well as studies using ARM Aerial Facility (AAF) and tethered balloon system (TBS) measurements. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Summary Report on Synthetic Time History Development and Deployment

This report summarizes research work performed at the Colorado School of Mines (CSM) and George Washington University (GWU) in support of the DOE Office of Nuclear Energy Integrated Energy Systems (IES) program. In particular, the work focuses on improving and strengthening two fundamental steps in the mathematical and computational framework that is currently being developed to optimize the economic performance of Integrated Energy Systems. One of the innovative approaches taken by the IES program is that, rather than optimizing the system for a specific year or week or day, the optimization is performed using stochastic synthetic data. Synthetic data is generated by training artificial intelligence (AI) using available but limited data sets. The synthetic data should possess the same patterns as the original set and the same statistical properties, but never repeat the same set of values exactly. The work from CSM focuses on this first step; namely, investigating a methodology to determine the quality of the synthetic data and the right settings for properly training the AI. Once a large set of trustworthy data can be generated the problem of stochastic optimization can be tackled. The optimal IES configuration is highly dependent on the rare high peaks or deep depths of the net demand (grid electricity demand less variable renewable energy [VRE] production). Using an unbiased random sampling of the synthetic data, these extremes are very difficult to generate and therefore the optimization can be unrepresentative and inaccurate. GWU has started an approach to increase the likelihood of generating these rare events with the proper associated probabilistic weight. Both of these projects represent a step forward in achieving the capability to properly size the IESs and to properly capture the value that these systems can provide to the grid by absorbing volatility of net demand without disproportionately increasing the cost of maintaining grid reliability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗